Parasitism & Ecosystems
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Parasitism and
Ecosystems
EDITED BY
Frédéric Thomas
François Renaud
National Centre for Scientific Research, France
Jean-François Guégan
Institut de Recherches pour le Développement, France
1
1
Great Clarendon Street, Oxford OX2 6DP
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Printed in Great Britain
on acid-free paper by
Antony Rowe, Chippenham
ISBN 0 19 852986 4 (Hbk)
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In the memory of Louis Thaler
Professor of Palaeontology at the University of Montpellier (France),
Louis Thaler was convinced that a multidisciplinary approach to the
study of evolution would benefit all biological sciences. To this aim,
he incessantly encouraged collaborations between disciplines, and
promoted the need to combine available techniques and methodologies. His communicative enthusiasm, his sustained guidance, his
grasp of new ideas fashioned the present research landscape in
Montpellier. His involvement as President of scientific committees in
many French research institutions (University of Montpellier, CNRS,
INRA, IRD, CIRAD, BRG, . . . ), inflected the thinking of the whole
French research community. He was once the mentor of the co-editors
of this book; no doubt, its topic would have enthralled him.
Nicole Pasteur
Directeur de l’Institut des Sciences de l’Evolution,
founded by Louis by Thaler in 1980
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Contents
Contributors
Introduction—Parasites, diversity, and the ecosystem
Peter Hudson
1 Linking ecosystem and parasite ecology
Michel Loreau, Jacques Roy, and David Tilman
2 Are there general laws in parasite community
ecology? The emergence of spatial parasitology
and epidemiology
J.-F. Guégan, S. Morand, and R. Poulin
ix
1
13
22
3 Parasitism and the regulation of host populations
Anders Pape Møller
43
4 Food web patterns and the parasite’s perspective
Michael V.K. Sukhdeo and Alexander D. Hernandez
54
5 Ecosystems and parasitism: the spatial dimension
Robert Holt and Thierry Boulinier
68
6 Parasitism and hostile environments
Richard C. Tinsley
85
7 Parasitism and environmental disturbances
Kevin D. Lafferty and Armand M. Kuris
113
8 Parasitism, biodiversity, and conservation
Frédéric Thomas, Michael B. Bonsall, and Andy P. Dobson
124
9 Subverting hosts and diverting ecosystems: an
evolutionary modelling perspective
Sam P. Brown, Jean-Baptiste André, Jean-Baptiste
Ferdy, and Bernard Godelle
10 Parasitism in man-made ecosystems
François Renaud, Thierry De Meeüs, and Andrew F. Read
140
155
viii
CONTENTS
Conclusion—Parasites, communities, and ecosystems:
conclusions and perspectives
Gary G. Mittelbach
171
References
177
Index
217
Contributors
Jean-Baptiste André Laboratoire Génome,
Populations, Interactions, Adaptation,
UMR 5171, USTL—CC. 105, Bât. 24,
Place Eugène Bataillon, 34095 Montpellier
Cedex 5, France.
Michael B. Bonsall Department of Biological
Sciences, Imperial College London, Silwood
Park Campus, Ascot Berks, SL5 7PY, UK.
Thierry Boulinier Laboratoire d'Ecologie,
CNRS—UMR 7625, Université Pierre & Marie
Curie, 7 Quai St Bernard, F-75005 Paris, France.
Robert Holt Department of Zoology,
223 Bartram Hall, P.O. Box 118525, University
of Florida, Gainesville, Florida 32611-8525.
Peter Hudson Center for Infectious Disease
Dynamics, Biology Department, Penn State
University, University Park, PA 16802.
Armand M. Kuris Department of Ecology,
Evolution and Marine Biology, Marine Science
Institute, University of California, Santa Barbara
California.
Sam P. Brown Department of Zoology,
University of Cambridge, Downing Street,
Cambridge CB2 3EJ.
Kevin D. Lafferty USGS Western Ecological
Research Center. Marine Science Institute,
University of California, Santa Barbara California,
USA.
Andy P. Dobson Department of Ecology and
Evolutionary Biology, Eno Hall, Princeton
University, Princeton, NJ 08544-1003.
Michel Loreau Laboratoire d’Ecologie,
UMR 7625, Ecole Normale Supérieure,
46 rue d’Ulm, F–75230 Paris Cedex 5, France.
Jean-Baptiste Ferdy Laboratoire Génome,
Populations, Interactions, Adaptation, UMR 5171,
USTL—CC 105, Bât. 24, Place Eugène Bataillon,
34095 Montpellier Cedex 5, France.
Thierry De Meeüs Génétique et Evolution de
Maladies Infectieuses GEMI/UMR CNRS-IRD
2724, Equipe: "Evolution des Systèmes
Symbiotiques", IRD, 911 Avenue Agropolis,
B.P. 5045, 34032 Montpellier Cedex 1, France.
Bernard Godelle Laboratoire Génome,
Populations, Interactions, Adaptation, UMR 5171,
USTL—CC 105, Bât. 24, Place Eugène Bataillon,
34095 Montpellier Cedex 5, France.
J.-F. Guégan GEMI, UMR IRD-CNRS 2724,
Centre IRD de Montpellier, 911 Avenue Agropolis
BP 64501, 34394 Montpellier Cedex 5, France.
Alexander D. Hernandez Department of
Ecology, Evolution and Natural Resources,
Rutgers University, Cook College, New
Brunswick, NJ 08901.
Gary G. Mittelbach W. K. Kellogg Biological
Station and Department of Zoology Michigan
State University, Hickory Corners, MI.
Anders Pape Møller Laboratoire de
Parasitologie Evolutive, CNRS UMR 7103,
Université Pierre et Marie Curie, Bât. A, 7ème
étage, 7 quai St. Bernard, Case 237, F-75252
Paris Cedex 5, France.
S. Morand CBGP, UMR INRA-IRD-CIRADAgro.M., Campus International de Baillarguet,
x
C O N T R I B U TO R S
CS-30016, 34988 Montferrier sur
Lez cédex, France.
R. Poulin Department of Zoology, University of
Otago, P.O. Box 56, Dunedin, New Zealand.
Andrew F. Read Institute of Evolution,
Immunology and Infection Research, University of
Edinburgh, EH 93 JT Edinburgh, Scotland, UK.
François Renaud Génétique et Evolution de
Maladies Infectieuses GEMI/UMR CNRS-IRD
2724, Equipe: "Evolution des Systèmes
Symbiotiques", IRD, 911 Avenue Agropolis,
B.P. 5045, 34032 Montpellier Cedex 1, France.
Jacques Roy Centre d’Ecologie Fonctionnelle
et Evolutive, UMR 5175, CNRS
F-34293 Montpellier Cedex 5, France.
Michael V.K. Sukhdeo Department of Ecology,
Evolution and Natural Resources, Rutgers
University, Cook College, New Brunswick,
NJ 08901.
Frédéric Thomas Génétique et Evolution de
Maladies Infectieuses GEMI/UMR CNRS-IRD
2724, Equipe: "Evolution des Systèmes
Symbiotiques", IRD, 911 Avenue Agropolis,
B.P. 5045 34032 Montpellier Cedex 1, France.
David Tilman Department of Ecology, Evolution
and Behavior, University of Minnesota,
St. Paul, MN 55108.
Richard C. Tinsley School of Biological
Sciences, University of Bristol,
Bristol BS8 1UG, UK.
INTRODUCTION
Parasites, diversity, and the
ecosystem
Peter Hudson
The dualities of parasitism
Dualism is a dominant theory of life that considers
reality to be a balance between two independent and
fundamental principles: good and evil, mind and
matter, nature and nurture. In the same manner we
see the thread of dualism run through the ecology of
parasitism: they can generate diversity but cause
extinction, they may castrate a host but increase its
growth rate, and they can stimulate an immune
response but at the same time encourage a secondary chronic infection. Parasites inhabit individual
hosts that are distributed as discrete patches, much
like a metapopulation but these hosts are also
nested within a spatially structured metapopulation
and these within a meta-community of competent
hosts. They often divert the host’s resources to
themselves and away from other consumers and so
change energy flow patterns, the use of critical
resources, and so influence ecosystem functioning.
The majority of living organisms are parasitic and
their role as specialist consumers and their influence
on biodiversity may well make them important
players in many ecosystems.
Given the rather special and probably pivotal
role parasites may play in many ecosystems, it is
somewhat surprising that few workers have considered the role of parasitism at the ecosystem
level. Probably the central question is to ask, how
do parasites influence ecosystem functioning? Or
more specifically, what are the consequences of
parasite removal for the community and energy
Center for Infectious Disease Dynamics, Biology Department,
Penn State University, University Park, PA 16802.
flow in the ecosystem? What is the biomass of
parasites within the ecosystem and how does this
compare with other natural enemies? How do the
parasites influence the flow of specific chemicals
and minerals through the system? How do parasites influence biodiversity? And how does biodiversity influence parasitism? Questions that we are
only just starting to get vague answers to but nevertheless the questions that are the underlying driving force behind the production of this book. There
is a common assumption that parasite biomass is
negligible (e.g. Polis 1999) but is this assumption
really correct? To illustrate the sheer significance of
parasites in an ecosystem let me tell you about a
comment made by my friend and colleague,
Armand Kuris. He once asked me what I thought
was the biomass of parasites on the Carpinteria salt
marsh (about 70 ha) where he and Kevin Lafferty
have studied the trematodes of the gastropod and
bird fauna for many years. I had not a clue, looked
deep into my glass of wine and fumbled with kilograms. ‘Our provisional estimate is in the order of
several elephants (if they weigh 3 tons maybe as
many as 7–10) with a reproductive rate equivalent
of several babies per year (maybe as high 1–2 baby
elephants per day) for the 200 warmest days of the
year’ he replied. Astonishing, absolutely amazing
and as a card carrying parasitologist, I was embarrassed by my lack of comprehension. Just imagine a
small herd of elephants on a wetland in Southern
California, they would be considered a dominant
feature and if they were just consuming vegetation
they would have a fantastic impact on the environment, especially in that small area of habitat. But
1
2
PA R A S I T I S M A N D E C O S YS T E M S
these parasites are living off snails and birds and
with their high reproductive rate they must be having a huge impact on the growth rate of their hosts,
influencing the flux of energy to other trophic levels
and shaping community structure by reducing
competitive abilities of their hosts and vulnerability
to predation. Of course, this is only part of the
potential impact of the parasites on the ecosystem
since Kuris and Lafferty have not estimated the
biomass of the plant pathogens, many of the parasites in the crustacean or in the tertiary consumers.
Asking good questions and making estimates of
parasite biomass can help us to get the role of parasites in perspective, but the answers to the questions
are far from easy and we should appreciate the
amount of hard work that has gone behind the
studies of parasites in the Carpenteria salt marshes
of Californian. To make some of the questions
answerable, we may need to restructure them into
a form that can be answered, perhaps by starting at
the level of the individual and then using this
foundation of understanding to explore issues at
population, community, and ecosystem level.
Hence we may ask, if parasites have an impact on
the individual host and what are the emergent
properties we may observe at the population and
community level? How does the parasite interact
with other natural enemies and then what are the
consequences of these interactions to ecosystem
functioning? This approach is based on undertaking insightful experiments at the lower level,
monitoring changes in the intensity of parasites
and age related effects and then integrating our
understanding through models and identifying the
patterns and emergent features we would predict
to observe at the higher levels. Another approach is
to examine an ecosystem that is subject to an
epidemic. For example, what happened to the
marine ecosystem of the North sea when Phocine
distemper virus reduced the population of seals?
Did fish survival change? Did seabirds compensate
with improved breeding production and survival
or were such events so transitory as to have little
influence? Again modelling and understanding can
provide insights. Another dominant approach for
examining ecosystems effects is to apply the
comparative method to identify patterns and
then dissect the data to propose the putative
mechanisms. The chapters in this book use all of
theses techniques and together provide an
integrated and clear examination of parasites at the
ecosystem level.
This short chapter serves as an introduction. I
shall try to lay the scene for the role of parasites in
ecosystems and in doing this I have to admit I face
the tensions of my own inner duality. On the one
hand I find the task daunting, our knowledge
vague, and the scale of the issue massive, and I am
aware that focusing on the parasite component of
an ecosystem may inadvertently trivialize other
critical components. On the other hand, the task is
exciting and a challenge that we should rise to:
pathogens and parasites have not been included in
the theories of trophic structure and are frequently
ignored from ecosystem ecology (Polis and Strong
1996; Polis 1999), we have a growing understanding
of the role of parasites, some excellent modelling
approaches and the time is ripe for a book like this. So
to set the scene for the book I will look at a
specialist parasite and a generalist parasite in two
contrasting food webs to examine how they influence
community structure and the ecosystem. I shall pick
some fundamental questions that examine the role
of parasites in ecosystems and illustrate those with
a few examples, selecting some examples that are
not used by others in the book, and of course,
shamelessly referring to my own work.
Specialist and generalist parasites in the
ecosystem
While the study of parasites was once the sole
domain of the specialist parasitologist, often
focused on the difficult and challenging task of
working out the life cycle and taxonomic position
of parasites, it is now apparent that this fundamental biological knowledge has allowed parasitology
to come of age so that a wide range of scientists and
disciplines are now addressing parasitological
questions. The issues scale from the molecular to
the ecosystem and to my mind, the challenge for
the future is to ensure that the discipline becomes
integrated vertically so that an understanding of
the processes of infection and persistence at the
INTRODUCTION
molecular level can be incorporated in making
predictions about the temporal and spatial spread
of diseases and in identifying how parasitism
influences ecosystem functioning. For example,
parasites often weaken their hosts, making them
morbid, and thus susceptible to predation (Hudson
et al. 1992a; Packer et al. 2003). How does this influence the way energy flows through the food web?
the consequences on the demographics of the host,
the predator, the parasite, and the competitors
in the system?
Understanding the importance of species and
groups within an ecosystem is one of the central
challenges to ecology and so if we are to investigate
the role of parasites, the design of the question is
important. Probably one of the most important
questions would be to ask: if we were to remove the
parasite from the system what would be the consequences? You may predict that host population
growth rates would rise and would then lead to an
increase in the growth rate of the other consumers
of that host but then maybe they would suppress
our host through the classic process of the paradox
of enrichment. Alternatively, you may predict that
the parasites keep the prey unhealthy allowing the
predators to catch and obtain a feed so the removal
of parasites makes the prey healthy and the predators starve so the host population would rise to be
regulated by some other factor such as food availability. On the other hand, some other parasite may
invade the niche and perhaps one that used the
predator as an obligate host and then changed the
dynamics of the whole community. So this apparently simple question is not trivial but we can quite
quickly see there are a suite of mutually exclusive
hypotheses to test in the wild. I suspect the true
answer to the role of the parasite depends on how
the parasite–host relationship is embedded in the
food web and more specifically whether the parasite is a generalist, shared between species, or a specialist. In a simple food web when we have a single
host infection that shapes the population dynamics
of the host then this can be dominating and have
far-reaching repercussions to the whole community. I will try to illustrate using studies on red
grouse and their caecal nematode, Trichostrongylus
tenuis. If grouse lived in a more complex ecosystem
3
then the effects of this specialist parasite may well
be buffered by the other interactions. Much to my
dismay, grouse do not live in the Serengeti, one of
the more fascinating ecosystems in the world and
one with a relatively complex food web. I know of
no detailed studies on a specialist parasite in this
system but there have been studies on a number of
interesting generalist parasites. Rinderpest infected
many of the ungulate species and appeared to have
led to a dramatic and far-reaching change in the
ecosystem, so we shall examine this system as a
contrast to the grouse system.
Rinderpest in African ungulates
Rinderpest is a disease of ungulates caused by a
morbillivirus and an equivalent of a ‘buffalo
measles’ transmitted through an aerosol of virus
during coughing and sneezing. This is an infection
of domestic animals that invaded Africa in about
1889 and then spread at a frightening pace across
the continent to reach the Cape within just 8 years
(more details in Chapter 8). The impact on wild
ungulate populations was dramatic, Buffalo and
Wildebeest were decimated by about 95% and local
populations of greater kudu, bongo, and eland
were totally wiped out. Here was a huge ‘experimental’ perturbation to the ecosystem of the
African savannah that is probably still influencing
the functioning of several ecosystems today, more
than 100 years later.
We probably know most about the situation in the
Serengeti than elsewhere since the disease became
endemic in the park (Dobson 1995a). In the 1960s
there was a heavy vaccination programme that
eventually ringed the whole park and by 1968 the
disease was eradicated. At that time there was a
series of detailed and fascinating scientific studies
that have since followed changes in the population
of ungulates and the ecology of the area and so
recorded the recovery of the ungulates and changes
in the ecosystem since rinderpest. Over this period,
the wildebeest and buffalo exhibited what the
Serengeti workers describe as ‘an eruption’: wildebeest and buffalo increased dramatically, at a rate of
about 10% per annum, so wildebeest numbers were
up 7-fold in 17 years and buffalo showed a parallel
4
PA R A S I T I S M A N D E C O S YS T E M S
increase. There is a circumstantial evidence that this
increase was a consequence of rinderpest since other
grazing species like the zebra (not an ungulate) were
unaffected. Furthermore, subsequent epidemics all
provide good evidence that rinderpest was a significant factor limiting the size of several ungulate
species. The interesting feature is the effect this must
have had on the rest of the ecosystem. Sinclair
(1979a) examined the effect that the eruption of
wildebeest had on the Serengeti ecosystem; the
increase in the wildebeest changed the seasonal
grazing pattern and the abundance of the grasses
and the herbs, reduced the combustible material and
reduced fires that in turn allowed tree regeneration
and through these processes influenced the whole
community of herbivores. The wildebeest compete
with the buffalo so while buffaloes increased after
the removal of rinderpest, the population subsequently levelled off, probably because of competition for food from the wildebeest. They probably
influenced the other grazers such as zebra (⫺ve:
direct competition) Grants gazelle (⫹ve: herbs
increased) and giraffe (⫹ve: trees increased). While
there was some evidence that the predator populations responded to the increased prey base
(Spinage 1962) the evidence is not clear, probably
because wildebeest are seasonal migrants and the
predator populations are regulated by the prey base
during the intervening periods but also because a
subsequent increase in predators led to the outbreak
of other diseases (see Dobson 1995a; and Chapter 8).
While these data are limited and the story is
pieced together from anecdotal evidence, Sinclair’s
deep understanding of the natural history of the
Serengeti and Dobson’s analysis, illustrate well how
the removal of a pathogen can shape the processes
within an ecosystem. Essentially the pathogen acted
to reduce the abundance of the primary consumers
and so influenced competition with other grazers,
the vegetation structure and no doubt the flow of
energy through the ecosystem.
Parasitic worms in British grouse
Red grouse inhabit the open, semi-natural moor
lands characteristic of the British uplands where
the vegetation is dominated by heather (Calluna
vulgaris), the primary food plant of the red grouse.
While the red grouse is the only species that relies
solely on the heather, the habitat is home to a number of other species including the mountain hare,
red deer, roe deer, and an avifauna that is predominantly migratory. These large tracts of heather
moorland are managed by keepers to produce a
harvestable surplus of grouse each year and provide grazing for the sheep farmers. The grouse are
preyed on by foxes, golden eagles, hen harriers,
short eared owls, and peregrines, but the keepers
legally control the foxes and frequently interfere or
kill the protected raptors (Thirgood et al. 2000).
The grouse exhibit unstable population dynamics
with oscillations in abundance and a period usually
between 5 and 12 years. The maximum growth rate
the grouse is determined by the quality of the main
food plant but subsequent changes in abundance
are a tension between the natural enemies of the
grouse (Hudson et al. 2002). Grouse are infected
with a caecal nematode which reduces their condition and breeding production and these demographic effects coupled with the low degree of
parasite aggregation in the host population generates instability in the population that can account
for the cyclic fluctuations in red grouse abundance
recorded in harvesting records (Dobson and
Hudson 1992; Hudson et al. 1992b). Large-scale
experiments that have removed parasites at the
population level effectively stop the periodic
crashes in abundance indicating that parasites play
an important role in the cyclic nature of this species
(Hudson et al. 1998). So while the direct interaction
between parasite and host plays a major role in generating the cyclic fluctuations in abundance, we
should now ask how this parasite–host interaction
shapes the effects of other natural enemies in the
ecosystem.
The parasites major influence on the host is to
reduce body condition and make the host morbid,
thus less able to produce young (Hudson 1986a),
defend territories (Fox and Hudson 2001), and
become more vulnerable to predation (Hudson et al.
1992a). The grouse emit a characteristic scent which
trained pointing dogs can smell at remarkable distances, when the hens commence incubation they
close off their caeca and no longer produce caecal
INTRODUCTION
faeces and at the same time stop emitting scent the
trained dogs can locate. It is here, in the caeca, that
the parasitic worm lives and interferes with the
workings of the caeca (Watson et al. 1987). Highly
infected grouse have difficulties controlling their
scent emission and the dogs, searching by scent,
can locate these grouse significantly more frequently than individual who have had their worms
experimentally removed (Hudson et al. 1992a).
Incorporating this selective predation into a model
of parasite–host interaction predicts an increase in
the host population (Hudson et al. 1992a; Packer
et al. 2003); initially a counterintuitive finding since
we would not expect the addition of predation
mortality to increase prey abundance (Fig. 0.1).
However, since the predation is selective, the predator is removing the heavily infected individuals
from the population, thus reducing the regulatory
(a)
5
role of the parasite, dampening the oscillatory
behaviour of the population, and leading to an overall increase in the population. Interestingly, one may
predict that harvesting by humans is another form
of predation, and should also remove parasites and
lead to dampening of the cycles but an examination
of the time series data shows this is clearly not the
case (Hudson and Dobson 2001). In fact what seems
to be happening is that much of the infection
process has already taken place prior to the start of
harvesting. The infective stages are on the ground
before the harvesting commences so the ‘dye is cast’
and the infection process will continue irrespective
of any removal of grouse by the hunters although
reduced density over an extended period will of
course lead to reduced infection levels.
Grouse are also infected with a tick borne virus
that causes the disease louping-ill, a significant
300
Numbers of grouse
250
200
150
100
50
0
2
7
4
17
12
35
25
45
55 75
65
Predation pressure
(b)
4 Predators
10 Predators
75 Predators
Numbers of grouse
No Predators
0
5
10
15
Predation pressure
20
Figure 0.1 Consequences of selective predation
on the dynamics of red grouse as predicted from
modelling (a) Bifurcation figure showing an
Increase in host density with increasing predation
pressure that reduces the effects of parasite
regulation and dampens oscillations (b)
simulation runs showing reduction in oscillations
with increasing predation.
Source: After Hudson et al. (2002).
6
PA R A S I T I S M A N D E C O S YS T E M S
cause of mortality in populations where it is
prevalent. The ticks themselves cause little mortality unless numbers are high, but in areas like the
North Yorkshire Moors the grouse pick up the ticks
from bracken dominated ground, a habitat that provides high humidity and assists tick survival
(Hudson 1986b). In the past, bracken was cut for
livestock bedding and these activities restricted the
bracken beds to the steep slopes but poor heather
burning practices coupled with heavy grazing has
allowed the bracken to escape from these slopes
and invade the heather moorland, thus bringing
the ticks into the habitat used by the grouse and
exposing them to infection. The tick life cycle is
dependent on the presence of a large mammalian
host and the removal of these hosts should lead to
the eradication of the tick and the louping-ill. In
areas where the sole host is the sheep, they can be
treated with acaricides and the ticks eradicated. In
other areas, deer may be important hosts for tick
but (unlike the sheep) they are not competent hosts
for the virus, thus deer act as a ‘sink’ for virus but a
‘source’ for ticks (Gilbert et al. 2001). In effect, the
deer act as ‘dilution hosts’ for the virus.
Theoretically, if the deer host a large proportion of
the ticks then they can reach a point where more
virus is lost through these ‘wasted bites’ into the
dead-end deer host than is generated from the competent hosts the virus levels fall. However, there is
another interesting player in this ecosystem: the
mountain hare. Experimental studies have shown
that while mountain hares do not permit direct
viral amplification through the normal systemic
route (like deer) they do permit non-systemic transmission between co-feeding ticks, unlike the deer
(Jones et al. 1997). Laurenson et al. (2003) undertook
a large-scale experiment where they removed hares
from a large area of moorland habitat and showed
a significant decrease in the louping-ill seroprevalence in the grouse. Interestingly they were able to
show that much of this decline in infection was
because they removed the effects of co-feeding
transmission. In other words, the hares were the
key players that kept the virus persistent in this
ecosystem and while the hares were a source of
ticks the important role they played was in providing
a suitable habitat that permitted transmission
between ticks. The final outcome of the role played
by the virus is in the interplay between hares, deer,
and grouse as hosts for both ticks and louping-ill.
The whole vertebrate community plays a role in
determining louping-ill dynamics but the specialist
grouse–nematode interaction has far-reaching
repercussions to the predators and the balance
between these mortality factors and then the quality
of the vegetation moulds the grouse dynamics.
Both of these studies are interesting since they
illustrate the role of parasitism in the ecosystem. An
understanding of the simple parasite–host relationship at the individual level allowed an understanding of population dynamics, the interaction with
other natural enemies and how changes in the community structure influenced the ecology within the
ecosystem. The Serengeti is a unique and rich
ecosystem of international significance that rightly
provides a wildlife spectacular but is vulnerable to
invasive diseases. We just mentioned rinderpest but
we could also have a range of other infections such
as rabies, canine distemper virus, anthrax and
bovine tuberculosis and the ways these pathogens
influence ecosystem functioning. Dobson (1995a)
has suggested that these have changed in prevalence as a consequence of changes in the ungulate
population. This interplay between species composition, abundance, and disease prevalence is found in
both the Serengeti and the Heather moorlands of
Britain and together probably play an important
role in shaping community structure and ecosystem functioning. The North American equivalent is
Yellowstone with Bison, elk, wolves, and bears.
Here the Bison population has increased dramatically following the grooming of roads after snow
fall and so brucellosis has become a major concern,
not directly to the Bison population but indirectly
by the perceived threat wildlife pose as reservoirs
of infection to cattle on neighbouring ranches. In
the same vane, humans also interact with the seminatural heather moorland where grouse management is a dominant form of land use in the uplands
of Britain. The grouse management favours a multiple land use system that incorporates sheep
farming, conservation, and recreation but if the
economics of this collapses then this land is sold for
commercial forestry, a single land use system of
INTRODUCTION
little benefit to wildlife. But there is an irony here,
another one of the dualities of parasitism if you
like. The significance of the disease to the grouse
has arisen primarily because the keepers reduce the
predation pressure from the foxes so allowing
grouse numbers to rise and parasitism to become a
problem. This parasitism leads to highly unstable
dynamics so that every few years the disease forces
the grouse down to low levels. At this point if the
predators are allowed back then the grouse will be
held at this low level, the grouse no longer become
a viable crop to harvest and the land can be sold to
a single land use such as commercial forestry. The
parasites are quite capable of knocking the host
population down to a low density that inverse or
simple density-dependent effects prevent them
from rising.
These two examples show us that a specialist
parasite like the nematode worm in the grouse can
have important implications for the population
dynamics of the host and consequently other natural enemies. For a generalist pathogen like rinderpest or even louping-ill (a specialist pathogen but
with a generalist vector), there are also important
repercussions to the whole community. We have
evidence to suppose parasites should be important
to the ecosystem.
Does biodiversity affect parasitism?
There is increasing evidence that species composition and diversity influence ecosystem functioning
(Tillman et al. 1997a) and productivity (Tillman et al.
2001). These studies and others are showing us that
biodiversity really matters to the quality of our
environment and since we are losing biodiversity
fast we are changing ecosystem functioning. But
what are the processes involved in these effects?
There are two dominant explanations in the literature, the first is that with low diversity, the probability of having species with the key traits present in
the community is reduced and so productivity falls
(the sampling effect). An alternative explanation is
that at diversity falls, so fewer species utilize
resources less completely (niche complementarity).
Both of these hypotheses are focused on resource
acquisition and use, but nearly 50 years ago, Elton
7
(1958) proposed that reduced biodiversity would
increase the severity of diseases. An important
hypothesis and one very relevant to the objective of
this book. Does parasitism increase in severity with
reduced biodiversity? Can the influence of disease
be an important mechanism that reduces plant productivity? These are not trivial questions but questions that help us identify the role of parasites in the
ecosystem. Two recent studies have shown us that
that biodiversity really does influence disease
severity. The first examines the pathogen load of
grass swards and shows that biodiversity does
indeed reduce disease severity and influences productivity from an ecosystem. The second examines
the tick borne zoonotic Lyme disease and shows
that reduced wildlife biodiversity increases the risk
of infection to humans.
Fungal pathogens and plant biodiversity
Foliar fungal pathogen spores are spread by wind
and rain and are common among grass species;
they darken leaves, reduce leaf life span through
the loss of nutrients, and photosynthate and so
depress productivity. Mitchell (2003) demonstrated
experimentally that excluding these pathogens
from intact grassland with fungicide dramatically
increased root production and biomass by increasing leaf longevity and photosynthetic capability.
The interesting aspect of this work was that he also
undertook a factorial experiment that included
insect herbivores along with the pathogens and
showed that herbivory had relatively little impact
compared with pathogens and thus demonstrated
that pathogens were potentially the important
regulators of ecosystem processes.
The hypothesis that the severity of disease is
greater when diversity is reduced is explained in
plants because reduced biodiversity results in
increased abundance and in turn this facilitates specialist pathogen transmission. This is well illustrated by studies in agriculture where the impact of
a pathogen in a cereal system is reduced when mixtures of multiple genotypes of one crop species are
grown together (e.g. Zhu et al. 2000). In another
excellent study Mitchell et al. (2002) tested the
diversity–disease hypothesis by using experimental
8
PA R A S I T I S M A N D E C O S YS T E M S
communities of perennial grassland plants where
diversity was controlled directly by hand weeding.
They showed that decreased diversity increased
pathogen load to an extent that pathogen load was
three times greater in a monoculture than in a plot
with 24 grass species, the equivalent to a natural
system (Fig. 0.2). They showed that increased
pathogen load and the severity of the attack was
essentially the consequence of changes in host
abundance although they also noted that changes
in the relative species composition played an
important role.
These studies are interesting and important since
they show us that as species diversity increases
so the impact of the pathogens falls and plant productivity increases. At the current time it is not clear how
much these pathogens account for the total changes
in productivity observed and as Mitchell points out
the overall impact depends on species composition
and the presence of basal species. Nevertheless, one
point is clear, parasites are an important component
that have a dominating influence on ecosystem functioning and their presence should not be ignored.
Lyme disease and biodiversity
The previous section examined how pathogen load
changed with the diversity of grassland species and
showed that as diversity fell, so relative abundance
Pathogen load
12
8
4
0
12
4
6 8
12
Species richness treatment
Figure 0.2 Decrease in pathogen load with increasing species
richness of grassland plants as determined by experimental
manipulation.
Notes: p ⬍ 0.001; r2 ⫽ 0.181; and n ⫽ 147.
Source: After Mitchell et al. (2002).
24
of the few remaining species increased and this
resulted in increased transmission of the specialist
pathogens. However, one of the interesting findings
was that while the overall pattern was clear, there
was high variation between trials since the species
composition varied and certain species influenced
the pathogen load more than others. When species
richness falls, the order of loss is often not random,
we can predict that some species are more vulnerable to disturbance than others and these will be lost
first. If these species vulnerable to disturbance are
also less important in disease transmission, then this
will result in a relative increase in the pathogen load
over and above changes in relative density.
What happens when the less competent hosts are
lost first? LoGiudice et al. (2003) examined this
question in the zoonotic Lyme disease system of
North America, a disease caused by the spirochete,
Borrelia burgdorferi that is transmitted between hosts
by the tick, Ixodes scapularis. The immature stages of
the ticks are generalists and feed on a wide range of
mammalian, avian, and reptilian hosts but while
these hosts may provide a blood meal for the ticks
they are not all competent hosts for the transmission of the Lyme disease pathogen. In other words,
when an infected tick bites some hosts the
pathogen is introduced into a ‘dead end’ host and
lost from the system so that when naïve ticks bite
the host they do not become infected. The dominant competent host in the system is the white
footed mouse, they can infect up to 90% of larval
ticks depending on how many of the larvae are
feeding on the non-competent host. When woodland habitat is degraded from pristine woodland to
wood lots, the charismatic larger species (and those
not competent for Lyme disease transmission) are
often the first to go while the mice are invariably
the last species. As species richness falls so proportionately more ticks feed on the white footed mouse
and since the mouse is a competent host, and many
of the other hosts are not competent, the overall
level of prevalence in the ticks should increase and
the risk of infection to humans increase. LoGiudice
et al. (2003) tested this hypothesis by showing that
the non-mouse hosts are relatively poor reservoirs
for Lyme disease and dilute the disease by feeding
ticks but not infecting them with the spirochete.
INTRODUCTION
They captured the 10 main groups of hosts, estimated their relative density, counted the immature
stages of ticks on each, the proportion that
engorged and then moulted, and also estimated the
relative abundance of the host to transmit the
pathogen. These unique data provided a community level insight into the relative role of each vertebrate host species in the transmission of the disease.
Since they also knew the approximate order of
species loss (mice are lost last) from woodland
areas as they become degraded they were able to
show clearly that as species diversity increases so
the infection prevalence in the nymphs, and so the
risk of human infection falls. The mouse is so dominant that the effects depend strongly on what the
mouse density is within the study area. Even so,
squirrels had the highest dilution effect reducing
prevalence by about 58% whereas shrews provided
a rescue effect; they acted to dilute the effects of the
most competent mouse hosts but could also maintain the spirochete in the community when mouse
density was low.
This study shows that the buffering of disease
prevalence is an interesting and important function
provided by high biodiversity. The finding is important since it shows us that while the presence of the
ticks is important, we must consider the biological
role of the different host species. While changes in
climate may influence the development and survival of vectors when they are not on the host, it
may also influence the distribution and abundance
of host species that may have a large effect on
disease prevalence and risk of infection to humans.
How does parasitism affect biodiversity?
Parasite mediated competition
I now want to turn the biodiversity and parasitism
question on its head and ask the inverse of the previous question: how does parasitism affect biodiversity. There are well-defined hypotheses that a
major driving force behind the evolution of species
diversity is parasitism (e.g. Janzen 1970; Connel
1978). Rather than consider this in detail I wanted
to introduce an important threat of parasitism to
biodiversity and conservation: the effects of a
reservoir host on the abundance and existence of a
9
more vulnerable species through the process of
apparent competition, sometimes referred to as
parasite mediated competition (Price 1980; Hudson
and Greenman 1998). The evidence that parasites
may drive some populations to extinction is frail.
There is the clear example of a microsporidian
parasite killing the last-known individual snail
Partula turgida (Cunningham and Daszak 1998) but
there are few documented cases where parasites
alone have driven a species to extinction.
General theory assumes, logically, that the transmission of most parasites can be considered density
dependent; so if a virulent pathogen is introduced
into a susceptible host population it will reduce
density but once density is reduced, transmission
will fall and the population will not be extirpated.
However, parasites could lead to local extinction
when transmission is frequency dependent, independent of density but dependent on the contact
rate between conspecifics. So, for example, when
wild dog density fell in the Serenegti, they still
lived in packs and held their social structure with
daily contact rates and the reduced overall density
did not mean the few remaining individuals were
spread independent of each other. Sexually transmitted diseases depend on the frequency of partner
exchange and not host density so HIV or syphilis
increases with the number of partners each infected
individual has a sexual relationship with and not
the total density of hosts in the population. HIV
would fade out in a dense community of strictly
monogamous couples unless maintained through
other forms of transmission such as blood transfusion. Similarly vector borne disease are frequency
dependent since transmission depends on being
bitten by a vector then the more often a host is
bitten the more likely they are of being infected,
irrespective of host density. Indeed vector borne
diseases often exhibit inverse density dependence
since as host density decreases, due to parasite
induced mortality, so the remaining vectors focus
on a smaller and smaller number of hosts thus
increasing the likelihood of them being exposed
and dying from the vector borne disease. In this
instance disease could drive species to extinction.
Another way in which parasites can reduce
biodiversity is in shared parasitism where two or
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PA R A S I T I S M A N D E C O S YS T E M S
more species share a parasite, in one the parasite
causes little mortality but this species sustains the
infection and there is between-species transmission
such that a second, more vulnerable species
receives the infection and suffers significant mortality and eventually becomes wiped out. This is
parasite mediated competition. A preliminary
glance at the literature and some of the reviews
indicates that parasite mediated competition may
indeed be rife. However few workers have examined the effects of parasites in detail and clearly
separated the effects of direct from parasite mediated competition in the wild. One of the classic
experiments sometimes referred to as parasite
mediated competition is the laboratory study of
Tribolium beetles by Park (1948) where he showed
that a competitive interaction between two species
was reversed when an Adelina parasite was added to
the system but this appears to be a special case
where the competitive ability of one species is
reduced by the parasite rather than indirect competition via a shared parasite. The clearest example is
the beautifully designed laboratory study by Bonsall
and Hassell (1997) summarized in Chapter 8, but
here I wish to highlight two field studies that
have examined parasite mediated competition in
the wild.
Squirrel invasion and parapox virus
Since its first introduction into Britain, the grey
squirrel has spread and replaced the red squirrel.
While the dominant theory was that resource competition was the underlying cause of the replacement, simulation modelling indicates that this
alone can not account for the rate and pattern of red
squirrel decline (Rushton et al. 1997). When the grey
squirrel was introduced, it brought with it a parapox virus that may have had a big impact on red
squirrels but not grey squirrels and may have had
at least a helping hand in the demise of the red
squirrel. A critical piece of evidence comes from the
study by Tompkins et al. (2002) who showed that
the virus caused a severe and deleterious disease in
the red squirrels but had very little effect on the
grey squirrels. Detailed modelling of the system
shows that the parapox virus was likely to have
had played a critical role in the demise of the red
squirrel even though the prevalence of infection
was low and may have led to previous workers dismissing its role (Tompkins et al. 2003). These studies show that parasite mediated competition could
be taking place but at this stage it is not clear
whether this acts alone or the pathogen may be
interfering with aspects of competitive ability.
Disentangling the effects of parasites on direct competition from parasite mediated competition is not
simple but the introduced squirrel appears to be
having an effect on the endemic species through the
effects of parasitism.
Game birds and gastrointestinal nematodes
One of the clearest examples of parasite mediated
competition are some detailed studies on the
shared nematode parasite Heterakis gallinarum that
infects both the ring necked pheasant and grey
partridges (Tompkins et al. 2000a). In this system it
would appear that there is little direct competition
between the two hosts, but the impact of the parasite on the grey partridge is enough to drive it to
localized extinction. Intensification of agriculture
in the British countryside has led to the loss of
weeds and the invertebrates associated with them
leading to the demise of the grey partridge (Potts
1986). Land owners and farmers faced with the loss
of a quarry species replaced the partridge by rearing
and releasing large numbers of pheasants. A number of farms and other areas have extensified their
land management practices, introduced conservation headlands, beetle banks, and encouraged the
habitat so partridges should recover. Unfortunately
many of these have failed and there appears to be
some other process acting that could be preventing
recovery and this may be parasite mediated
competition.
Tompkins et al. (2000b) infected pheasants and
partridges in captivity with 500 eggs of the gastrointestinal nematode H. gallinarum and then followed changes in body condition and worm egg
production. Both host species exhibited the classic
self-cure and after 100 days had cleared infection
but the fitness of the worms was roughly two
orders of magnitude greater in the pheasants in that
INTRODUCTION
each worm introduced into the pheasant produced
100 times more eggs than the in the partridge. What
was more, the impact of the worms was such that
the partridges lost condition while the pheasants
did not, in other words worms in pheasants produce more infective stages but only partridges
suffered from the infection indicating that the
pheasants are potentially an important reservoir of
infection. They then released partridges into five
different areas where they had monitored infections in wild pheasants and the uptake of infective
stages in the partridges was directly dependent on
the intensities in the pheasants (Tompkins et al.
2000b). This demonstrated that the partridges were
being infected through a common pool of infective
stages and the larger this was the more this
increased infection in the partridges and the bigger
the impact on partridge condition. By modelling
the multiple host system they were then able to
demonstrate that these effects were sufficient to
lead to the local demise of the partridges by the
pheasants through the process of parasite mediated
competition (Tompkins et al. 2000c). This is one of the
few field based studies to show clearly that parasite
mediated competition operates in the wild and that
parasites have an effect on biodiversity.
The role of parasites in ecosystems
In the first section of this chapter I looked at how a
specialist parasite (T. tenuis in red grouse) can influence host dynamics and so other natural enemies,
the complexities of a specialist pathogen with a
generalist vector (louping-ill), and then the farreaching repercussions of a generalist pathogen in a
relatively complex food web (rinderpest in the
Serengeti). I think that detailed studies on the
impacts and transmission of parasites provides us
with an understanding of how parasites influence
host dynamics and thus allows us to examine the
consequences of parasitism in an ecosystem. These
first order interactions are examined in more detail
in Chapter 3.
In the second section I touched on two of the
central questions to this book: how does biodiversity
affect parasitism? And how does parasitism affect
biodiversity? I have but scratched the surface and I
11
hope by doing so wetted your appetite for the main
meal of the tome that follows. The following chapter
(Chapter 1) takes this approach much further by
applying our understanding of ecosystem science to
the world of parasitism. One thing becomes abundantly clear, parasitism is a dominant part of many
ecosystems and while there maybe few measures of
the relative biomass of parasites in a system we
should appreciate that parasites often have a very
large turnover rate, so parasites may have a relatively large effect on energy flow. The whole idea
that parasites redirect energy away from other
trophic levels and how they operate within a spatially heterogeneous environment is explored fully
in Chapter 4. These discussions are never far from the
dominating concerns that many environmentalists, as
well as biologists, have about our ecosystems, the loss
of biodiversity and what we can do about it from a
conservation strategy, as examined in Chapter 8.
Perhaps we could take a few lessons from the few but
beautifully detailed studies that have been undertaken
in disturbed (Chapter 7) and hostile environments
(Chapter 6).
One key issue I was keen to address, but felt I
should leave for others more qualified, is the fact
that parasites and hosts are in a wonderful evolutionary tension where the host develops increased
resistance and the parasite generates the means of
avoiding the host’s response. The immune system is
a complex and highly adaptive system that must
outstrip the within host growth of the pathogen and
at the same time carry a memory. This memory can
have important implications to the way the infracommunity of the parasites develops and is
observed (e.g. Lello et al. 2004) and current levels of
infection within any mature vertebrate are the
ghosts of infection past. The whole manner in which
parasite communities are structured in ecosystems
is examined in detail in Chapter 2 and then examined in relation to the structure of the food web in
Chapter 4. The evolutionary tension I refer to, of
course, not only influences the host’s response but
also the response of the pathogen, this includes
features such as parasite induced susceptibility to
infection (explored in Chapter 9) and the important
effects of anthropogenic impacts on the environment, examined in Chapter 10. The integration of
12
PA R A S I T I S M A N D E C O S YS T E M S
evolutionary principles with those of epidemiology
and ecosystems is extremely exciting and I feel the
need to point you at a recent exciting paper by
Grenfell et al. (2004) that brings together an evolutionary, phylogenetic approach with our understanding of epidemiology into a new field of
investigation that has become known as phylodynamics. I suspect many of the dualities we
observe in parasite–host systems arise because of
the tensions between the evolutionary and
epidemiological characteristics of parasites.
There is little doubt that the whole concept of how
parasites fit into the ecosystem, how they interact
with the community of hosts and climatic changes is
rapidly becoming an exciting new field. One group
of workers calls this integrated discipline conservation medicine (Aguirre et al. 2002; Hudson 2004) and
there is now a new journal of EcoHealth which publishes papers on disease and ecosystem sustainability. This journal and study area examines in detail
how the emergence and effects of pathogens and
parasites interact with anthropogenic pollutants
and the environment to influence disease dynamics.
The vertical integration of the subject is essential; at
the subcellular level we need to understand the very
binding processes that allow a virus to enter a cell of
a specific host and in the case of zoonotic diseases a
second host that is phylogenetically distant (e.g.
Hanta virus in mice and humans, West Nile virus in
birds, humans, and horses). We need to embrace the
machinations that results in relatively high rates of
mutation in the RNA viruses, the genetic processes
of recombination that can lead to the evolution of
new strains, and how these interact with the complex arms of the hosts immune system. At the cellular level we need to examine how parasites locate
the organ they inhabit, the complexities and shifting
sands of antigen expression and then the consequences this can have for such subjects as assessing
optimal mates for sexual reproduction. At the
level of the individual host, we need to include
the patterns of the parasite communities within
and between hosts and how species interact and
can influence the within host selective forces that
occur during the course of infection. One major
development over the past 25 years has been the
production of logical, generic models that integrate
the findings at the individual level and then predict
the epidemiological consequences at the population
level (Anderson and May 1991; Hudson et al. 2002).
This approach has served to identify the means of
controlling infections in a number of important epidemics. We now need to extend these to the
community level to understand how and when
species may act as reservoirs, the means by which to
control them (vaccinate reservoir or target host?),
and the ecosystem consequences of our actions. The
final frontier is to combine the fundamental aspects
of ecology with immunology and evolutionary biology to understand the role of parasites in a dynamic
ecosystem.
I want to finish with one final and ironic duality;
the perceived importance of parasitism in natural
systems is a simple reflection of the importance of
disease in the human population. Before the 1950s
ecological workers often considered parasitism of
major importance in wild host systems. Later, the
development of penicillin and vaccination programmes reduced the threat of infectious disease to
humans and in the same manner the ecological
texts of the time played down and usually ignored
the role of parasites in population dynamics or
community structure. Since then we have seen
increased concern over emerging diseases, a series of
important epidemics (HIV, SARS, Foot & Mouth,
BSE, Avian Influenza, etc.), the development of
resistance to anthelmintic drugs, and the threats of
bioterrorism all of which have highlighted the role of
parasites. In parallel we have seen increased concern
and funding for disease related issues and modern
ecology texts include parasitism in natural systems
in at least one chapter. Modern parasitologists and
the ecological parasitologists that are the authors of
this book now see that the parasite–host relationship is
full of nonlinearities that need investigating if we are
to control the threats of infectious diseases, but at the
same time encourages us to appreciate the pivotal
role parasites can play in an ecosystem.
CHAPTER 1
Linking ecosystem and parasite
ecology
Michel Loreau,1 Jacques Roy,2 and David Tilman3
Parasites are rarely considered in ecosystem studies. The current interest in
the relationship between biodiversity and ecosystem functioning, however,
has stimulated the emergence of new synthetic approaches across the
traditional divide between population and ecosystem ecology. Here we
provide a brief introduction to ecosystem ecology, an overview of current
trends in the field of biodiversity and ecosystem functioning, and ideas about
how parasites should and could be brought into ecosystem ecology.
1.1 Introduction
Host–parasite interactions have traditionally been
approached from the viewpoint of population
dynamics and epidemiology. In contrast, ecosystem
ecology has traditionally focused on the ‘big
picture’ of stocks and flows of mass and energy at
the whole system level, in which parasites at first
sight seem irrelevant because they account for such
a low biomass. Parasites are rarely considered in
ecosystem studies. For example, since its launch in
1998, the journal Ecosystems has not published a
single paper containing the words parasite, parasitism, or parasitoid in its title, key words or even
abstract! This nearly complete separation between
parasites and ecosystems in modern ecology is
an expression of the broader separation between
population/community and ecosystem ecological
approaches. The current interest in the relationship
between biodiversity and ecosystem functioning,
however, has stimulated the emergence of new synthetic approaches across the traditional divide
1
Laboratoire d’Ecologie, UMR 7625, Ecole Normale Supérieure,
46 rue d’Ulm, F-75230 Paris Cedex 05, France.
2
Centre d’Ecologie Fonctionnelle et Evolutive, UMR 5175,
CNRS F-34293 Montpellier Cedex 5, France.
3
Department of Ecology, Evolution and Behavior, University of
Minnesota, St. Paul, MN 55108 USA.
between community and ecosystem ecology (Jones
and Lawton 1995; Kinzig et al. 2002; Loreau et al.
2002). In this chapter we provide a brief introduction to ecosystem ecology, an overview of current
trends in the field of biodiversity and ecosystem
functioning, and ideas about how parasites should
and could be brought into the ‘big picture’ of
ecosystem ecology.
1.2 Ecosystem ecology, an integrative
science in need of further integration
Because of its central role in ecological thinking, the
ecosystem concept has been extensively analysed
by ecologists, historians, philosophers, and linguists (e.g. Hagen 1992; Golley 1993; Dury 1999;
Pickett and Cadenasso 2002). A historical overview
of this concept helps to grasp the fundamentals of
ecosystem science, its progress in half a century of
existence and its current challenges.
1.2.1 The ecosystem concept in a historical
perspective
Since it was first introduced by Tansley (1935), the
ecosystem concept has designated not only the sum
of the organisms and their abiotic environment, but
also the ‘constant interchange of the most various
13
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PA R A S I T I S M A N D E C O S YS T E M S
kinds within each system, not only between the
organisms but between the organic and the inorganic’ (Tansley 1935). Lindeman (1942) and Odum
(1959, 1969) also stressed the exchange of energy
and materials between the living and non-living
parts in their definitions of the ecosystem. Odum
(1959) recognized ‘four constituents as comprising
the ecosystem: (1) abiotic substances, basic inorganic and organic compounds of the environment;
(2) producers, autotrophic organisms, largely green
plants [ . . . ]; (3) consumers (or macro-consumers),
heterotrophic organisms, chiefly animals [ . . . ];
(4) decomposers (micro-consumers, saprobes or
saprophytes), heterotrophic organisms, chiefly bacteria and fungi, which [ . . . ] release simple substances
usable by the producers.’ With these constituents,
an ecosystem is a ‘life-support system [ . . . ] functioning within whatever space we chose to consider
whether it be a culture vessel, a space capsule, a
crop field, a pond, or the Earth’s biosphere’ (Odum
1964). These initial views are still prevailing among
current ecosystem ecologists. Thus, for Chapin et al.
(2002), ‘ecosystem ecology addresses the interactions between organisms and their environment as
an integrated system. [ . . . ] The flow of energy and
materials through organisms and the physical
environment provides a framework for understanding the diversity of form and functioning of
Earth’s physical and biological processes’.
Some authors, however, gave extended, more
abstract definitions of the ecosystem. Evans (1956)
suggested that the ecosystem concept could be
used at any organizational level of life. On this
view, any organism with its micro-environment
could potentially constitute an ecosystem. Higashi
and Burns (1991) distinguished two ecosystem
concepts: ‘the ecosystem as a physical entity’ following Tansley (1935), and ‘the ecosystem as a paradigm for science: an entity–environment unit’.
With such extended definitions, a host and its
parasites could be viewed as an ecosystem (as in
Thomas et al. 1999a, see also Chapter 8). Pickett and
Cadenasso (2002) emphasized the flexibility of the
definition, the ecosystem concept being scale independent and free of narrow assumptions such as
equilibrium. This general concept can then be
applied to an array of models whose characteristics
depend on the issue being addressed and on the
nature of the system under study. Depending on
the model, energy, nutrient, biodiversity, or economics can be the focus of the study (Pickett and
Cadenasso 2002).
For a large majority of ecologists, and in particular for those who bridge fundamental research and
applied problem solving, an ecosystem is clearly a
‘spatially explicit unit of the Earth’ (Likens 1992).
As such it comprises abiotic substances,
autotrophic and heterotrophic organisms, and their
interactions. The nature and consequences of these
interactions, however, has fuelled a recurrent
debate: do these interactions lead to emergent
properties and integration of the ecosystem into a
self-regulated functional unit? A number of scientists working on subsets of ecosystems, such as
physiologists Engelberg and Boyarsky (1979) and
community ecologist Simberloff (1980) questioned
this idea, whereas ecosystem ecologists generally
supported the cybernetic nature of ecosystems
(McNaughton and Coughenour 1981; Patten and
Odum 1981). The strongest, and most controversial,
form of this view is probably Lovelock’s (1995)
Gaia theory of the total Earth system as a single
self-regulating unit. The debate on these issues,
however, has often been led astray to one-sided
positions. The theories of complex adaptive systems (Levin 1999) and multilevel natural selection
(Wilson 1980), for instance, provide frameworks to
understand the ecological and evolutionary emergence of properties at higher levels of organization
without invoking strong top–down, integrated
regulation.
Chapin et al. (1996, 2002) provide a useful synthetic view of what controls ecosystem structure
and functioning. According to them; five external
factors set the bounds for ecosystem properties:
parent rock material, topography, climate, time,
and potential biota. Within these bounds, actual
ecosystem properties are set by a suite of interactive
controls: (1) resources (soil, water, air); (2) physical
and chemical modulators (such as local temperature and pH, which affect organisms without being
consumed by them); (3) disturbance regime; (4) the
biotic community, and; (5) human activities which
affect all the other controls. The biotic community
L I N K I N G E C O S YS T E M A N D PA R A S I T E E C O L O G Y
influences ecosystem functioning through the
trophic levels present, the number of species within
each trophic level, their relative abundances, and
their identity. Dominant species (in term of biomass)
and species with particular functional attributes
(like mycorrhizal fungi) are the species with a priori
the largest role. Populations of these species are
regulated by a set of negative and positive interactions among species, and parasitism is one of them.
With only an indirect role on one of the five interactive controls of ecosystem processes, parasites
understandably are not of first concern to most
ecosystem ecologists.
1.2.2 Ecosystem science, its achievements
and frontiers
Ecosystem science is characterized by the processes
it addresses rather than by the type of system it deals
with, although it is more often conducted at high
levels of organization (several trophic levels) and
large spatial scales (from a plot to the whole Earth).
It is concerned mainly with the pools and the fluxes
of energy and materials among ecosystem components (in contrast to population and community ecology which are concerned with the demography,
diversity, and interactions of the organisms living in
ecosystems). Its aim is usually to understand how
these pools and fluxes are regulated by the interactive controls mentioned above, but also how they
set constraints on the structure of ecosystems (community types and diversity). Temporal and spatial
patterns of ecosystem processes and ecosystem
management are also of primary concern. The
increasing impact of humans on all these aspects
and its consequences are often at the forefront of
ecosystem ecology (Vitousek et al. 1997).
Accomplishments of ecosystem science have
been numerous (Pace and Groffman 1998), and
include understanding the flow of water and chemical elements and compounds in watersheds, rivers,
lakes, estuaries, and oceans; analysing feedbacks
between plants and animals and their biophysical
environment; understanding the causes of, and
remedies to, eutrophication; understanding the biophysical basis of production and its coupling to climate; assessing the importance of below-ground
15
processes in terrestrial ecosystems; and recognizing
the scale dependence of most ecosystem processes
(Carpenter and Turner 1998). These accomplishments have been mainly achieved through
(1) comparative studies of natural ecosystems (e.g.
Matson and Vitousek 1987; Turner et al. 2001);
(2) long-term field studies (Gosz 1996; Hobbie et al.
2003); (3) experimental manipulation of ecosystems
from model laboratory systems to large-scale field
experiments (Beyers and Odum 1993; Lawton 1995;
Schindler 1998); and (4) theory and mathematical
modelling (Tilman 1988; DeAngelis 1992; Ågren
and Bosatta 1996; Loreau 1995, 1998a).
The ecosystem approach is fundamental to managing the Earth’s resources. Ecosystem ecology
often bridges fundamental research and applied
problem solving. When environmental concerns
moved from the local scale in the 1960s to the
regional and now global scales, so did ecosystem
science. These three scales cannot replace each other,
however, and basic research is still needed at all
scales. For example, the knowledge of a basic
ecosystem process such as primary productivity,
whose study was fostered from the 1960s by the
International Biological Programme, is still developing fast, integrating new techniques, control factors,
and scales (Canadell et al. 2000; Roy et al. 2001). But
the main challenge ahead is getting more strongly
involved in solving the ever-increasing environmental problems and working towards a more sustainable future (Lubchenco 1998; Gosz 1999).
Integrating across scales is a prominent task (Levin
1992; Carpenter and Turner 2000b), as is integrating
the various controls of ecosystem processes. Taking
into account the role of biodiversity in ecosystem
functioning is a critical, fast-developing area, which
we develop in the next section. Integrating the
socio-economic aspects of human activities from
local to global scales is a novel dimension which
will be crucial for achieving a sustainable management of ecosystems (Carpenter and Turner 2000a;
Costanza 2000; Di Castri 2000). Efforts are also
needed to develop stronger communication and
cooperation among the research, policy and public
spheres (Baron and Galvin 1990; Rykiel 1997). The
Millennium Ecosystem Assessment is an example of
such efforts (Ayensu et al. 1999; Samper 2003).
16
PA R A S I T I S M A N D E C O S YS T E M S
Despite its achievements in basic and applied
science, ecosystem ecology has developed until
recently in growing isolation from other fastmoving ecological subdisciplines such as population
ecology, community ecology, and evolutionary
ecology. The level of integration that it promotes
has stimulated links with other scientific disciplines
such as chemistry and geology, but has also tended
to diminish links with other biological disciplines.
Reciprocally, population ecology, commun-ity ecology, and evolutionary ecology have until recently
largely ignored the higher level of integration
offered by ecosystem ecology. This separation
between subdisciplines that provide different perspectives on the same ecological reality is a fundamental limitation which needs to be overcome if we
are to understand the predominantly biological
basis of ecosystems, the reciprocal constraints that
individual species and ecosystems exert on each
other on ecological and evolutionary time-scales,
the role of biodiversity in ecosystem functioning,
and more particularly the role of parasites and of
their diversity in ecological systems.
1.3 Biodiversity and ecosystem
functioning, a new area that synthesizes
population, community, and ecosystem
ecology
The relationship between biodiversity and ecosystem functioning has emerged as a new research
area at the interface between community ecology
and ecosystem ecology which has expanded dramatically during the last few years (see syntheses in
Loreau et al. 2001, 2002; Kinzig et al. 2002). This new
area finds its origin in a questioning that started
only a decade ago on the potential con-sequences of
biodiversity loss which results from the increasing
human domination of natural ecosystems, a domination that is likely to further develop considerably
during the twenty-first century (Schulze and
Mooney 1993).
Three types of reasons have been put forward to
justify current concerns about threats to biodiversity. First, biodiversity is the source of natural
resources that lead to the direct production of
goods that are of economic value, such as food,
wood fibre, new pharmaceuticals, genes that
improve crops, or organisms that are used for biological control of pests. Second, biodiversity is
viewed as linked to human well-being for aesthetic,
ethical, and cultural reasons. Third, biodiversity may
contribute to the provision of ecosystem services
that are of value to society, but are generally not
given an economic value, such as primary and secondary production, plant pollination, climate regulation, carbon sequestration, the maintenance of
water quality, and the generation and maintenance
of soil fertility. It is this third possibility that gave
rise to the interest in biodiversity and ecosystem
functioning: could biodiversity loss alter the functioning of ecosystems, and thereby the ecological
services they provide to humans?
When this question was posed in the early 1990s,
scientific ecology had a number of theories and
empirical data that clearly showed the importance
of ‘vertical’ diversity, that is, functional diversity
across trophic levels along the food chain, in
ecosystems. An eloquent example of the dramatic
impacts that changes in vertical diversity can have
is provided by the kelp–sea urchin–sea otter food
chain in the Pacific. Removal of sea otters by
Russian fur traders allowed a population explosion
of sea urchins that overgrazed kelp (Estes and
Palmisano 1974). Reduction in kelp cover in turn
leads to extinction of other species living in kelp, as
well as increased wave action, coastal erosion, and
storm damage (Mork 1996). More intense herbivory
in the absence of sea otters has also been shown to
trigger evolution of chemical defences in kelp
(Steinberg et al. 1995). Thus, removal of a single top
predator generates a cascade of population dynamical, physical, and even evolutionary effects within
ecosystems.
In contrast, little was known on the ecological
significance of ‘horizontal’ diversity, that is, genetic,
taxonomic, and functional diversity within trophic
levels. Different theories of coexistence among
competing species have vastly different implications
for the relationship between species diversity and
ecosystem processes. To take two extreme examples,
neutral theory assumes that all species in a community are equivalent (Hubbell 2001). This implies
functional redundancy among species, and hence an
17
L I N K I N G E C O S YS T E M A N D PA R A S I T E E C O L O G Y
absence of any effect of changes in diversity on
aggregate community or ecosystem properties. At
the other extreme, niche theory postulates that all
species differ to some extent in the resources they
use. This implies functional complementarity among
species, and hence increased productivity and other
ecosystem processes with diversity (Tilman et al.
1997a; Loreau 1998b).
To investigate the effects of ‘horizontal’ diversity
on ecosystem processes, a new wave of experimental studies was developed using synthesized
model ecosystems. Many of these studies were
focused on effects of plant taxonomic and functionalgroup diversity on primary production and nutrient
retention in grassland ecosystems. Because plants,
as primary producers, represent the basal component
of most ecosystems, they represented the logical
place to begin detailed studies. Several, though not
all, experiments using randomly assembled
communities found that plant species and functionalgroup richness has a positive effect on primary
production and nutrient retention (e.g. Tilman et al.
1996, 1997b; Hector et al. 1999; Fig. 1.1). Although
the interpretation of these experiments was hotly
debated (e.g. Huston 1997; Huston et al. 2000;
Hector et al. 2000), this controversy has been largely
resolved by a combination of a consensus agreement
on a common conceptual framework (Loreau et al.
2001), the development of a new methodology to
partition selection and complementarity effects
(Loreau and Hector 2001), and new experimental
data (Tilman et al. 2001; van Ruijven and Berendse
2003). These new studies have all shown that plant
diversity influences primary production through a
complementarity effect generated by niche
differentiation (which enhances resource exploitation
by the community as a whole) and facilitation.
Thus, there is little doubt that species diversity does
affect at least some ecosystem processes, even at the
small spatial and temporal scales considered in
recent experiments, although it is still difficult to
assess how many species are important to generate
functional complementarity.
Even if high diversity were not critical for maintaining ecosystem processes under constant or
benign environmental conditions, it might nevertheless be important for maintaining them under
changing conditions. The ‘insurance’ and ‘portfolio’ hypotheses propose that biodiversity provides
a buffer against environmental fluctuations because
different species respond differently to these fluctuations, leading to functional compensations
(b)
1.4
1000
500
0
Total biomass (g/m2)
Above-ground biomass (g/m²)
(a) 1500
Germany
Ireland
UK
Switzerland
Portugal
Sweden
Greece
0
1.2
1.0
0.8
0.6
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0.2
0.0
1
2
4
8
16
32
Species richness
0
2
4
6
8
10 12
Species richness
14
16
Figure 1.1 Responses of plant biomass to experimental manipulations of plant species richness in grassland ecosystems: (a) above-ground plant
biomass in eight sites across Europe; (b) total plant biomass (mean ⫾ standard error) during several years in Minnesota.
Note: Points in (a) are data for individual plots.
Sources: (a) Modified from Hector et al. 1999; and (b) Modified from Tilman et al. 2001.
18
PA R A S I T I S M A N D E C O S YS T E M S
between species and hence more predictable aggregate community or ecosystem properties. A number
of studies have recently provided theoretical
foundations for these hypotheses (e.g. McNaughton
1977; Doak et al. 1998; Tilman et al. 1998; Yachi and
Loreau 1999; Lehman and Tilman 2000). Several
empirical studies have found decreased variability
of ecosystem processes as diversity increases,
despite sometimes increased variability of individual populations, in agreement with the insurance
hypothesis (e.g. Tilman 1996; McGrady–Steed et al.
1997). The interpretation of these patterns, however,
is complicated by the correlation of additional factors
with species richness in these experiments, which
does not fully preclude alternative interpretations
(e.g. Huston 1997).
An important limitation of virtually all recent
theoretical and experimental studies on the effects
on biodiversity on ecosystem functioning and
stability is that they have concerned single trophic
levels—primary producers for the most part.
Although they have contributed to merging community and ecosystem ecology, they have unintentionally disconnected ‘vertical’ and ‘horizontal’
diversity and processes. Yet it is well known that
trophic interactions can have important effects on
the biomass and productivity of the various trophic
levels (Abrams 1995; Oksanen and Oksanen 2000)
as well as on ecosystem stability (MacArthur 1955;
May 1974; Pimm 1984). An important current
challenge is to understand how trophic interactions
affect the relationship between biodiversity and
ecosystem functioning. A few recent experiments
have started to investigate biodiversity and ecosystem processes in multitrophic systems (Naeem et al.
2000; Downing and Leibold 2002; Duffy et al. 2003),
and new theory now provides testable predictions
on these issues (Ives et al. 2000; Loreau 2001; Holt
and Loreau 2002; Thébault and Loreau 2003). Since
parasites and diseases are cryptic higher trophic
levels, this extension to multitrophic systems provides a straightforward path towards including
parasites into our view of ecosystems.
1.4 Parasites in ecosystems
Parasites are typically small-sized organisms that
exploit their host both as a food resource and as
a habitat. They affect their host negatively either
because they alter specific physiological functions
or because they multiply and develop large
populations within their host; individually their
effect is often very small. Even collectively,
their biomass and the amount of material and
energy they process is often much smaller than the
biomass and the material and energy flows of their
host. This explains why parasites have traditionally
been ignored by ecosystem ecology: they are hidden
within their host, and their direct ecosystem impact
is seemingly negligible.
Yet their indirect impact on ecosystem processes
can be substantial through their effect on their host.
Here we explore some of the ways in which they
exert strong indirect influences on the biodiversity
and functioning of ecosystems.
First, parasitism and disease are probably one of
the most significant causes of population regulation
in many species under natural conditions (see
Chapter 3). By regulating populations of dominant
species they can have significant effects on ecosystem processes (see Chapter 8). Massive mortality or
fertility reduction in individual species, however,
may be of little long-term significance for ecosystem
properties under natural conditions, especially in
plants. Plants compete strongly for space, light, and
nutrients, so that population reduction or extinction
of one species, which may have a significant effect
on ecosystem productivity or other processes in the
short term, is usually compensated for by population growth of another species in the long term.
Compensation among otherwise functionally
‘redundant’ species is the very basis for the insurance effect of biodiversity on aggregated ecosystem
properties (Walker 1992; Walker et al. 1999).
A historical example is provided by the extinction of
the American chestnut, once a major canopy species
in Eastern US deciduous forests, following introduction of a fungal pathogen. Oaks and other species
replaced the chestnut, and forest productivity and
biomass returned to levels similar to previous levels
in about 40 years (Whittaker and Woodwell 1972).
Effects of parasites on individual animal populations
might be more significant for ecosystem processes
and services—at least as we perceive them from our
anthropocentric perspective—because animals often
have more specific roles in the complex interaction
L I N K I N G E C O S YS T E M A N D PA R A S I T E E C O L O G Y
networks of natural ecosystems. For instance, in
a successful attempt to control the proliferation of
the European rabbit, introduction of the myxoma
virus in Australia led to decimation of rabbit
populations (Fenner and Ratcliffe 1965). Rabbit
mortality helped restore the vegetation which supported sheep populations utilized for wool production in range and pasture lands. Little is known on
the net effect of myxomatosis on total primary and
secondary production, but wool production at least
was strongly influenced by the presence of the
myxoma virus.
Second, by exerting top-down control on populations from lower trophic levels, parasites may
substantially alter the diversity of their host species
and its effects on ecosystem processes. Higher
trophic levels can generate hump-shaped or other
complex nonlinear relationships between species
diversity and ecosystem processes (Thébault and
Loreau 2003). These nonlinear relationships are
critically dependent on where and how top-down
or bottom-up controls occur in the food web. For
instance, when all plant species are controlled from
the top down by specialized herbivores, there is a
monotonic increase in total plant biomass as diversity increases. By contrast, when some plant species
escape top-down control or when herbivores are
generalists, a unimodal relationship can emerge
between total plant biomass and diversity (Fig. 1.2).
Whether the agents of top-down control are herbivores or parasites is immaterial to these theoretical
results. Therefore these should apply to parasites as
well. Application of insecticide to a biodiversity
experiment revealed major effects of insect herbivores on the relationship between plant diversity
and primary productivity: there was a strong positive response of above-ground plant biomass production to plant diversity when insect herbivores
were reduced, which was not apparent when herbivores were unchecked (Mulder et al. 1999). The
reason for this difference lies again in the top-down
control exerted by insects on plants, which diverts
part of primary production to the herbivore trophic
level. There is no reason why this should not apply
to parasites too. Seed predators and pathogens
are hypothesized to be one of the main factors
maintaining tropical tree diversity (Janzen 1970;
Connell 1971; Wright 2002, see also Chapter 8). If
19
this is the case, they may have a major influence on
ecosystem processes in tropical forests despite
their very low biomass. Similarly, viruses are
arguably one of the major factors that maintain
(through selective exploitation), and even create
(through gene transfer), microbial diversity
(Weinbauer and Rassoulzadegan 2004). Their indirect
impact on microbially driven ecosystem processes, in
particular nutrient cycling, should accordingly be
considerable, although it is still poorly known.
Third, a well-established body of theory and
empirical evidence shows that there is a gradual
transition from parasitism to mutualism on both
ecological and evolutionary time scales (Maynard
Smith and Szathmary 1995; Johnson et al. 1997). In
particular, the nature and intensity of symbiotic
interactions can be highly variable, and change
from mutualistic to parasitic, and vice versa,
depending on local environmental conditions. For
instance, mycorrhizal fungi are usually mutualists
for their associated plant partners because they help
them to better capture soil nutrients. In fertile soils
with high nutrient concentrations, however, they
become parasitic because plants no longer need
them to gain access to soil nutrients while they still
incur the cost of providing them with carbon
resources (Johnson et al. 1997). As a consequence of
this high variability in the benefits and costs
derived by the two partners, mycorrhizal fungi
have highly species-specific effects on plants, and
may strongly affect the diversity, species composition, and relative abundances of plant communities
(van der Heijden et al. 1998). Mycorrhizal diversity
thereby contributes to maintaining plant diversity
and primary productivity under nutrient-limited
conditions (van der Heijden et al. 1998; Klironomos
et al. 2000). Under nutrient-rich conditions, however,
mycorrhizal fungi may behave as plant parasites.
Their impacts on plant diversity and productivity
are then expected to be more complex as discussed
above. Similar shifts in impacts on plant-based
ecosystem processes are likely to occur for other
plant parasites as environmental conditions change
and alter the physiological status of the two
partners.
Lastly, nutrient cycling is a key process that
determines the productivity of all trophic levels
in nutrient-limited ecosystems (DeAngelis 1992;
20
PA R A S I T I S M A N D E C O S YS T E M S
400
All edible vs. 1 inedible plant
P1
Hn–1 Hn
H1
Pn
Pn–1
P1
FWC 1
Plant biomass
H1
FWC 2
Hn–1
Pn–1
300
200
FWC 1
100
Pn
0
FWC 2
50
2
3
4
5
6
7
8
550
Herbivore biomass
Soil nutrient concentration
1
40
30
FWC 1
20
10
FWC 2
0
1
2
3
4
5 6 7
Diversity
8
9
10
9 10
FWC 1
450
350
FWC 2
250
1
2
3
4
5 6 7
Diversity
8
9
10
Figure 1.2 Expected soil nutrient concentration, total plant biomass and total herbivore biomass (mean ⫾ standard deviation across all species
combinations) as functions of species richness for two food web configurations: a food web in which each plant species is controlled by a
specialized herbivore (dotted lines), and a food web in which one plant species is inedible and lacks a specialized herbivore (solid lines). Herbivore
species richness varies parallel to plant species richness to keep the same food web configuration along the diversity gradient.
Source: Modified from Thébault and Loreau (2003).
Loreau 1995, 1998a; de Mazancourt et al. 1998).
Heterotrophic consumers such as herbivores, carnivores, and parasites can substantially influence
primary production through nutrient cycling. They
can even increase primary production if they channel
limiting nutrients towards more efficient recycling pathways, that is, to recycling pathways that
keep a greater proportion of nutrients within the
system (de Mazancourt et al. 1998). Although this
theory has been mainly applied to the debated
grazing optimization hypothesis, that is, the
hypothesis that herbivores maximize plant production at a moderate grazing intensity, this theory
should apply to parasites as well. By altering the
timing and spatial location of their host’s death,
parasites may contribute to release nutrients locked
in their host’s biomass at times and places that are
favourable for the conservation of these nutrients
within the ecosystem or, conversely, for their loss
from the ecosystem by such processes as leaching,
volatilization, and sedimentation. In the former case
they will tend to enhance local productivity; in the
latter case they will tend to depress local productivity. Stoichiometric constraints also come into play.
For instance, bacterial decomposers often immobilize a substantial amount of limiting nutrients such
as nitrogen and phosphorus because their carbon :
nutrient ratio is lower than the carbon : nutrient
ratio of plant dead organic matter which is their
main resource (Tezuka 1989; Ågren and Bosatta
1996). Parasitic viruses are likely to enhance nutrient
cycling, and hence primary production, by killing
bacteria and making nutrients available again to
plants.
1.5 Concluding remarks
Ecosystem ecology has provided an integrative perspective of the interactions between biological
organisms and their abiotic environment, especially
at relatively large spatial scales. However, it would
be strengthened by better ties to, and synthesis of,
L I N K I N G E C O S YS T E M A N D PA R A S I T E E C O L O G Y
the insights and approaches of population ecology,
community ecology, and evolutionary biology. After
all, organisms simultaneously experience all the
forces of nature, including those that are the foci of
evolutionary, population, community, and ecosystem ecology. Each of these perspectives has been,
and will continue to be, useful simplifications. Their
synthesis, we assert, is likely to provide novel and
important insights into all branches of ecology.
Recent theoretical and experimental work provides evidence that biodiversity dynamics can have
profound impacts on functioning of natural and
managed ecosystems and their ability to deliver
ecological services to human societies. Work on simplified ecosystems in which the diversity of a single
trophic level—mostly plants—is manipulated
shows that taxonomic and functional diversity can
enhance ecosystem processes such as primary
productivity and nutrient retention. Theory also
strongly suggests that biodiversity can act as biological insurance against potential disruptions
caused by environmental changes. One of the major
challenges, however, is to extend this new knowledge to multitrophic systems that more closely
mimic complex natural ecosystems.
The role of parasites in ecosystem functioning
has usually been underestimated and poorly investigated because of their low biomass, low visibility,
21
and small direct contribution to energy and material
flows in natural ecosystems. We have provided
several arguments why they may nevertheless have
significant indirect impacts on ecosystem properties, by controlling numerically dominant host
species, by exerting top-down control and maintaining the diversity of lower trophic levels, by
shifting from parasitic to mutualistic interactions
with their hosts, and by channelling limiting nutrients to more or less efficient recycling pathways.
Despite recent progress towards greater convergence and dialogue between population, community, and ecosystem ecology, much remains to be
done to achieve full integration of these subdisciplines. In particular, the potential importance of
parasites and disease emphasize the need to take
into account both direct and indirect effects in our
view of ecosystems. Although indirect effects have
received increasing attention in community ecology recently (Wootton 1994; Abrams 1995), their
importance for ecosystem functioning has seldom
been considered. Parasites, just as microbes, remind
us that small causes can have large effects. Unless
we better develop our understanding of the ecological significance of the whole of biodiversity,
including that of parasites, we have an insufficient
understanding of the functioning of natural and
managed ecosystems.
CHAPTER 2
Are there general laws in parasite
community ecology? The emergence
of spatial parasitology and
epidemiology
J.-F. Guégan,1 S. Morand,2 and R. Poulin3
Recent insights into both population and community ecology of host-parasite
relationships have shown the importance of spatial processes in influencing
the structure of local parasite and microbe communities. This now requires
from parasitologists, epidemiologists and evolutionary biologists working on
those interactions that they place their analyses into a broader spatial
perspective. Because local species richness and composition in parasites and
pathogens depend on large-scale species pools, a greater consideration of
epidemiological processes will favour the emergence of spatial parasitology
and epidemiology devoted to understanding population dynamics and
community structure.
2.1 Introduction
There is an increasing interest in parasite and
infectious disease population (Grenfell and Dobson
1995; Hudson et al. 2001) and community (Esch et al.
1990; Poulin 1998a; Rohde 2001) ecology, and interestingly this has developed at a time when mainstream ecologists have shown increasing interest in
metapopulation theory and habitat fragmentation
(Hanski and Gilpin 1997; Hanski 1999), population
dynamics in fragmented landscape (Hassell and
Wilson 1997; Ferguson et al. 1997; Grenfell and
Harwood 1997; Rohani et al. 1999) and macroecology
1
GEMI, UMR IRD-CNRS 2724, Centre IRD de Montpellier, 911
Avenue Agropolis BP 64501, 34394 Montpellier Cedex 5, France.
2
CBGP, UMR INRA-IRD-CIRAD-Agro.M., Campus International de Baillarguet, CS 30016, 34988 Montferrier sur lez cedex,
France.
3
Department of Zoology, University of Otago, PO Box 56,
Dunedin, New Zealand.
(Brown 1995; Rosenzweig 1995; Maurer 1999; Lawton
2000; Gaston and Blackburn 2000). The development
of what is now called spatial ecology is one of the
great triumphs of modern population and community ecology (Tilman and Kareiva 1997), which has
showed the critical importance of space and spatial
characteristics for understanding a wide range of
ecological phenomena (Holt 1993, 1999). There are
clear analogies between modern spatial ecology and
parasite–infectious disease population and community ecology, and this chapter will be devoted to a
review of the recent development in parasite–infectious disease population and community ecology
within this fruitful cross-fertilizing arena.
There are considerably more studies available on
parasitic systems today than 10 years ago (see Poulin
1997, 1998a; Poulin et al. 2000 for a review), and many
of these investigations have clearly showed the role
of dynamical processes in a spatial context (Ferguson
et al. 1997; Grenfell and Harwood 1997; Morand and
22
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
Guégan 2000a; Poulin and Guégan 2000; Morand et
al. 2002). Most if not all parasites live as populations
that are divided into metapopulations on several spatial scales, and each host operates as a patch. Many of
the topics in modern spatial ecology have also their
parallels in within-host infection processes with the
individual host body forming an heterogeneous
environment (see Holt 1999). From the perspective of
a parasitic larval form or microbe, an individual host
is an extraordinary landscape to invade with heterogeneity in resource availability and colonizationextinction risks. An infrapopulation is thus defined as
all the members of a given parasite species within a
single host individual, and an infracommunity
includes all of the infrapopulations within an individual host. The next hierarchical level includes all
the infrapopulations sampled from a given host
species within an ecosystem, and which forms the
metapopulation. Parallel to the metapopulation is the
component parasite community which represents all
of the infracommunities within a given host population. Then the highest level of parasite organization is
the suprapopulation which represents all individuals
of a given parasite species within an ecosystem. Next,
the parasite compound community consists of all the
parasite communities within an ecosystem (see Esch
et al. 1990). This creates at least a third-order scaling
of habitat fragmentation for the parasites which has a
significant impact on the development of theory
regarding the evolution of populations and communities of parasites and pathogens. Infrapopulations
and infracommunities may form many replicates
from one host to another, thus providing a remarkable opportunity for comparative analyses of the
variability of organizational patterns at several hierarchical levels, so much more difficult to explore for
free-living organisms. Furthermore, this hierarchical
organization means that larger-scale processes may
have a strong influence on local community structure
(see Poulin 1998a; Poulin et al. 2000) and dynamics of
parasites and microbes (see Grenfell and Harwood
1997; Rohani et al. 1999), indicating that these largerscale phenomena cannot be ignored anymore. For
instance, recent advances in epidemiology of childhood diseases have clearly shown the influence of
spatial fluxes on local disease dynamics, recognizing
structural similarities between the processes of
23
metapopulation biology and infection dynamics
(Grenfell and Harwood 1997; Rohani et al. 1999).
Price (1990) in his contribution to the seminal
book by Esch, Bush, and Aho (1990) argued that
parasite community ecologists should take a leading role in advancing areas of ecology with many
parasite studies being attractive complements for
investigating some of the major questions in population and community ecology. Nearly one decade
and a half after, the intent of the present chapter is to
synthesize the more recent developments in parasite and microbial community ecology, and to assess
current perspectives regarding our knowledge of
these communities.
To see where we are heading, consider a few simple questions one could ask about a parasite or microbial community. What determines the number of
parasite species one host individual can harbour?
Why are some parasite species extremely rare when
others are very common? What is the local population abundance of a widely distributed macroparasite when compared to that of a rare species? These
very basic questions of (parasite and infectious disease) community ecology have extraordinary little to
do with small-scale processes, but on the contrary
need that we explore larger-scale phenomena.
Having described the different macroscopic patterns,
we then explore the consequences of this research
framework in population and community ecology of
parasites and microbes. We opted in the present
chapter to use examples from both the microbial and
parasitological community literature to illustrate the
various concepts. We conclude by highlighting what
these findings mean for further study of population
dynamics and community ecology of parasitic and
infectious disease in wildlife and humans.
2.2 Parasite community organisation
and species coexistence
2.2.1 The emergence of spatial ecology in
infectious and parasitic diseases population
and community dynamics
As for mainstream population and community
ecology (see Putman 1994; Begon et al. 1996;
Weiher and Keddy 1999), parasite population and
24
PA R A S I T I S M A N D E C O S YS T E M S
community ecology has concentrated on local
processes with an emphasis on local interactions
between parasite species, and between these species
and their host environment (see Kennedy 1975;
Cheng 1986; Esch and Fernandez 1993; Combes 1995;
Bush et al. 2001). Another aspect is the strong research
effort made over the past decades on very untidy
small-scale studies, which do not take a strongly
quantitative approach to issues such as spatial patterns in species richness at very large scales or patterns in species distributions (but see Price 1980;
Rohde 1982; Poulin et al. 2000; this chapter). For
instance, what determines the structure of the local
community of human infectious diseases in a given
place of Western Africa has certainly as much to do
with large-scale, biogeographical processes as it has
to do with local conditions. This view is shared by an
increasing number of researchers interested in the
influence of climate variability on regional disease
dispersion and diffusion, for instance (Dobson and
Carper 1993; Rogers and Williams 1993; Hay et al.
1996; Patz et al. 1996; McMichael and Haines 1997;
Global species pool
Continental species pool
Regional species pool
Rapport et al. 1998; Epstein 1999; Rogers and
Randolph 2000; Aron and Patz 2001).
2.2.2 Some definitions and basic conceptual
framework
Many processes studied by parasite and microbial
community ecologists have clear linkages with
larger-scale, regional phenomena, but since studies
have focused too largely on small spatial scales they
are obviously unable to put the communities into
perspectives (see Lawton 2000; Poulin et al. 2000; this
chapter). The assembly of parasites or microbial communities as for free-living ones is a multistage, multilayered process, and this forms a conceptually
important framework on which to base further
research investigations. First, it starts at the top of
Fig. 2.1 with the largest-scale pool of species. The existence of a global-scale pool of parasite and microbe
species is entirely relevant for many organisms like in
the case of crop pests, viruses, bacteria, and fungi, or
human infectious and parasitic diseases (see Rapport
Historical
filters
Environmental
filters
Compound community
Component community
Dispersal
filters
Infracommunity
Top-down
Bottom-up
effects
effects
(screen filters) (invasive species,
pandemia,…)
Figure 2.1 Schematic illustration of the main determinants of parasite or pathogen species richness in hosts. On the left: processes influencing
species diversity are arranged into hierarchies in which different temporal and spatial factors may act. Any given level includes all lower levels, and it
is included within all higher levels. On the right: the hierarchical scheme indicates that parasite or pathogen community assemblages at lowerspatial scales, for example an individual host, are strongly dependent on upper scales (top-down effect on community richness), but the opposite
situation where lower-spatial scales may influence higher levels (bottom-up effect) is also possible.
Notes: Invasive species like crops or pandemia like HIV are illustrative of global impact of parasites and pathogens. Further research should reveal the
respective roles played by ‘top-down’ and ‘bottom-up’ effects on community assemblages of parasites and microbes.
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
et al. 2002). This notion is at present made highly relevant by the development of transcontinental transports and economical exchanges between two distant
biogeographical regions, making the Earth today a
global village for many pathogens and diseases (see
Poulin 2003a, and the later Section 2.3.2.4 ‘Latitudinal
gradient in species richness’). The regional pool of
parasite and microbe species, or metacommunity, is a
more conventional and accepted notion in community ecology, and it exists within a biogeographic
region like a continent or a subcontinent. Then,
understanding the origin of the parasite or microbe
pool requires a knowledge of the evolutionary history of host–parasite associations, of the geographic
isolation of the continent, of the linkages between
pathogens and the biological diversity present within
the area, and so on (see Brooks and McLennan 1991;
Combes 1995; Poulin 1998a). Local communities like
those of macroparasites in fish populations or
microbes in human populations assemble themselves
from this regional pool through a series of filters (see
Fig. 2.1). Differences in host population size and density or the spatial arrangement of host population
habitat patches (high to low connectivity), for
instance, may be responsible for the persistence or
the extinction of parasite or pathogen populations
moulding local communities (see Grenfell and
Dobson 1995; Grenfell and Harwood 1997; Keeling
and Grenfell 1997, 2002; Rohani et al. 1999). At the
individual host level, infracommunities of parasites
and pathogens again assemble themselves from the
local pool of available species (see Fig. 2.1). If species
can reach a host they may still find the environment
unsuitable, species interactions may also operate or
may be constitutive, and induced defences against
invasion can intervene. Many processes described
here have also clear parallels in within-host infection
since each host individual is composed of many different sites more or less connected with one another,
and available, or not, for parasite or pathogen establishment (see Holt 1999). This framework shows that
different environmental filters work on all these
communities representing important steps in community assembly and constitution (see Murray et al.
2002; Rapport et al. 2002).
Mainstream community ecologists have long
debated on the important steps in community
assembly working down from the larger scales
25
largely dominated by regional, not local processes
(see Ricklefs and Schluter 1993; Brown 1995;
Rosenzweig 1995; Maurer 1999; Lawton 2000; Gaston
and Blackburn 2000). This can be contrasted with a
more traditional approach in both parasitology and
epidemiology through the study of local phenomena
for understanding the structure and dynamics of
parasitic or microbe assemblages. However the ‘topdown’ and ‘bottom-up’ paths are clearly complementary, and the recognition of the importance of a
regional or even global perspective in parasite and
microbe population dynamics and community
assembly theory would clearly benefit from more
detailed attention than would be possible from either
approach alone. Recent studies on the impacts of
global environmental changes on disease population
and communities dynamics (see Harvell et al. 1999,
2002; McMichael 2001; Martens and McMichael 2002)
provide several good examples of how largest-scale
studies are of particular relevance to both parasitology in wildlife and human epidemiology. It is also
obvious that the ‘context’ of the beginning of an infectious disease outbreak transmitted from wildlife is
clearly local (see for instance the cases of HIV), some
having dramatically increased in incidence and
expanded in geographic range panglobally (see
Hahn et al. 2000; Daszak and Cunningham 2002).
As we know today from the study of complex hierarchical systems inspired by physics, both processes
from the top to the bottom and from the bottom to the
top of Fig. 2.1 (see also Allen and Hoekstra 1992;
Allen et al. 1993) are certainly acting as forces controlling parasitic and infectious disease community
assembly. Recognizing that often the determinants of
both host animal (or plant) and individual human
health may occur at levels higher within the ecosystem hierarchy is thus one of the major tasks of
modern parasitology and epidemiology.
2.3 Emergent properties of parasite
and infectious disease communities
2.3.1 On the search for regularities in parasite
and infectious disease community structure
and processes
One of the principal advantages of this two-way
viewpoint of community assembly organisation is
26
PA R A S I T I S M A N D E C O S YS T E M S
that it takes a sufficiently distant view of parasitological and epidemiological systems that the idiosyncratic details disappear, and only the important
generalities remain (see Brown 1995; Rosenzweig
1995; Gaston and Blackburn 2000 for application in
mainstream ecology; Poulin et al. 2000 and this volume for parasitological–epidemiological investigations). This may reveal general patterns, or
regularities, that would otherwise have been entirely
neglected (see Morand and Poulin 1998; Morand
2000; Morand and Guégan 2000a). Any scientific discipline must pass through a phase where the phenomena of interest are clearly and quantitatively
identified (this chapter), and then the mechanisms
underlying the observed patterns are explored and
challenged with rigourous theoretical and empirical
testing. Specifically, the recent developments in population dynamics of infectious diseases have clearly
shown how useful generalizations, but not at the
level of local human communities, might be indicative of significant regulation in spatial dynamics of
those diseases (Ferguson et al. 2003). Nevertheless,
the impossibility of using manipulative experiments
in natural systems (case of wildlife diseases) and
anthropogenic systems (case of epidemiology) means
that it is often difficult to retain a single hypothesis
among competing alternative solutions to understand the mechanisms that underlie the patterns (see
Morand and Guégan 2000a for an illustration).
Consequently, this inability to exploit manipulative
experimentation over large-scales have forced parasitologists, plant-associated insect ecologists, and
epidemiologists to use comparative approaches (see
Aho and Bush 1993; Cornell 1993; Lawton et al. 1993;
Poulin 1995a; Cornell and Karlson 1997; Morand and
Poulin 1998; Choudhury and Dick 2000; Morand
and Guégan 2000a; Guégan et al. 2001; Brändle
and Brandl 2003; Nunn et al. 2003; Guernier et al.
2004) as macroecologists did before (Brown 1995;
Rosenzweig 1995; Maurer 1999). The following
sections attempt to illustrate this using different
examples from the literature, and to discuss the consistency of the results with the various hypotheses
used to explain the observed patterns in the light of
recent advances in macroecology (see Gaston and
Blackburn 2000), and comparative analysis in parasitology-epidemiology (see Poulin et al. 2000).
2.3.2 Parasite and infectious disease species
richness
Undoubtedly, parasites and other kinds of microbes
and associated organisms like phytophagous
insects may represent more than half of the living
organisms (Price 1980; de Meeüs et al. 1998;
Morand 2000; Poulin and Morand 2000; Curtis et al.
2002; Brändle and Brandl 2001, 2003; Nee 2003),
even if very few attempts have been made to rigorously quantify and delineate the differences in richness between free-living organisms on the one
hand and their associated organisms on the other
hand (but see Strong and Levin 1975; Strong et al.
1985; Hillebrand et al. 2001; Guernier et al. 2004 and
hereafter). Most, if not all, organisms are hosts for
parasites, comprising helminths, arthropods, fungi,
or microbes, and if the pioneer work by Guernier
and colleagues is representative of other (host)
species, the overall biodiversity on Earth may be
currently underestimated by more than an order of
magnitude due to the unsuspected species diversity
of parasites and other kinds of microorganisms (see
Guernier et al. 2004 and hereafter). Investigations
attempting to identify determinants of species richness of parasites and other kinds of associated
organisms are now well represented in the recent
parasitological literature (Poulin 1995a; Morand
2000; Poulin and Morand 2000; Brändle and Brandl
2001; Guernier et al. 2004) much more than a decade
ago, and more research is needed on different symbiotic systems to examine the extent to which the
observed patterns are supported or undermined.
Here we draw attention to the four most popular
and striking ‘macroecological’ patterns in the
species richness of assemblages of parasitic and
other kinds of associated organisms, and we promulgate how the search for consistency in common
patterns, or not, from other symbiotic systems will
contribute to the emergence of a more rigorous
research agenda in parasitology and epidemiology.
2.3.2.1 Species–area relationship
The variation in species richness of parasites and
other associated organisms is generally not random,
but shows one regular pattern which is the
species–area relationship (Simberloff and Moore
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
breadth, extinction/colonization, and temporal
dynamics (see Gaston and Blackburn 2000), which
then disappear after such a statistical control (see
Guégan and Kennedy 1996).
The paper by Goüy de Bellocq et al. (2003) shows
that the parasite species richness in the woodmouse,
Apodemus sylvaticus, on western Mediterranean
islands depends on the surface areas of the different
surveyed localities (but see Dobson et al. 1992a,b for
contradictory results). Other factors, that is, parasite
species life-history traits and host species diversity,
were also important as determinants of helminth
richness and composition across isolated rodent
populations. Fig. 2.2 illustrates the relationship
between parasite species richness and surface area
for the eight Mediterranean islands and three
continental regions used in the study.
More interestingly, the authors demonstrate that
the positive relationship observed between parasite
species richness and surface area across woodmouse
populations is not the result of a random process, but,
on the contrary, it shows the existence of order, that is,
nestedness (see corresponding Section, 2.3.2.4) in the
presence/absence matrix of parasite species across
different localities. Helminth parasites are organized
according to a hierarchy of species, also called nested
species pattern (see Guégan and Hugueny 1994),
across surveyed areas: some parasite species are
widespread across localities, and some others are
Parasite species richness
(log-scale)
1997; Poulin 1998a,b; Morand 2000), a now-classical
factor explaining the number of species likely to be
found at any site in mainstream ecology (Brown 1995;
Rosenzweig 1995; Gaston and Blackburn 2000).
Usually, widespread hosts tend to have more parasite
or infectious disease species than hosts with a more
restricted geographical range because the increase of
host range may allow the host to encounter more
species (Gregory 1990). This pattern seems to hold
both within host species (see Freeland 1979;
Marcogliese and Cone 1991; Goüy de Bellocq et al.
2003; Calvete et al. 2004) and across host species (see
Poulin 1998a; Morand 2000; Brändle and Brandl 2003
for a review). Alternatively, host body size may be
taken to represent area size for parasites (see Guégan
et al. 1992; Guégan and Hugueny 1994). Indeed, in
interspecific comparisons among host species, many
positive relationships have been reported between
host body size and parasite species richness; however, the relationship is not universal, and there are
many exceptions (see reviews in Poulin 1997;
Morand 2000).
Still, the species–area relationship is generally a
strong pattern in parasite diversity studies. For
instance, the species–area relationship explains more
than 50% of the total variation in species richness of
phytophagous insects (Kennedy and Southwood
1984; Brändle and Brandl 2001), and around 14–30%
of the variance in species richness of parasitic fungi
(Strong and Levin 1975; Brändle and Brandl 2003).
More interesting than the existence of a species–area
relationship for symbiotic systems is what does this
pattern mean? Or, put in other words, which
processes may be responsible for the relationship?
One problem with this approach is that the
search for correlates of species richness across populations of host species characterized by different
geographical ranges (or size area for isolated
systems) is often not independent of sampling effort
(see Gregory 1990), and most studies have thus controlled for the effects of differential sampling of
host species (Gregory 1990; Poulin 1998a). Whether
it is correct still remains to be determined (Guégan
and Kennedy 1996). Sampling effort may be
strongly correlated with host geographical range
and other biological factors which may covary with
host range, for example, host size, host niche
27
1.6
1.4
1.2
1
0.8
0.6
0.4
0
1
2
3
4
5
6
Surface area (log-km2)
Figure 2.2 The relationship between log-species number and logsurface area for parasites of the woodmouse, Apodemus sylvaticus, on
different islands and regions from Europe.
Notes: The line of best fit is a linear function of the form
y ⫽ 0.11x ⫹ 0.72, r2 ⫽ 0.68, p ⫽ 0.0017). The three points in the upper right
side of the diagram are for Continental Europe, Spain, and Italy. Other
points are for western Mediterranean islands, that is, Mallorca, Menorca,
Formentera, Ibiza, Corsica, Port-Cros, Porquerolles, and Sicila.
Source: Redrawn from Goüy de Bellocq et al. (2003).
28
PA R A S I T I S M A N D E C O S YS T E M S
uncommon and found in only fewer areas (see Goüy
de Bellocq et al. 2003). The richness and distribution
of the different helminth species across areas
depends not only on area size as previously shown
but also on the type of parasite life cycle and host
mammal species diversity. The explanations given by
the authors are that larger areas may sustain larger
host populations, an important parameter in epidemiology which determines the host resource
needed for a parasitic or infectious disease agent to
persist (see Grenfell and Harwood 1997; Keeling
1997), and thus may favor the existence of a higher
parasite diversity (see Morand and Guégan 2000b).
Then the difference observed in both the parasite
species richness and composition across areas may be
due to the fact that a parasite with a direct life cycle
may have more chances to succeed in the colonization of a new host population compared with a parasite with an indirect life cycle which absolutely needs
to find a suitable intermediate or definitive hosts to
complete its cycle. Finally a locality with high host
species diversity may be more favourable for parasitic or disease persistence, for example parasites
with a complex life cycle finding more definitive host
species to achieve their development.
A reconsideration of the study by Goüy de
Bellocq et al. (2003) using Generalised Linear
Models (see Wilson and Grenfell 1997; Venables and
Ripley 1999) instead of simple regressions indicates
that the data are strongly flawed by sampling bias,
a fact that makes previous findings questionable.
The new results (see Table 2.1) show that helminth
component community richness variation across
areas is strongly dependent on both sampling effort
expressed as the host sample size per area
(F value ⫽ 345.97, p ⫽ 0.00034) and the interaction
between sampling effort and surface area
(F value ⫽ 30.35, p ⫽ 0.0118), the largest areas being
less sampled, on average, than smaller areas, with
all other parameters kept constant in the model.
Mammal host species diversity is then just marginally significant in the multivariate analysis (see
Table 2.1). Surface area does not appear to be significant anymore. A stepwise elimination procedure
using the Akaike criterion yielded similar results.
This new result indicates that sampling effort
may exert strong bias in estimation of parasite
Table 2.1 Summary of Generalized Linear Model with a gaussian
error structure for explaining the parasite species richness variation in
woodmouse across 11 different areas
Deviance Resid. df Resid. dev F value
Null
Sampling size
Host diversity
Surface area
Sampling ⫻ Host
Sampling ⫻ Area
Host ⫻ Area
Sampling ⫻ Host
⫻Area
678.73
538.77
22.12
3.33
6.33
47.26
40.53
9
8
7
6
5
4
139.96
117.84
114.51
108.18
60.92
20.39
15.72
3
4.67
345.97
14.21
2.14
4.06
30.35
26.02
p (F)
0.00034
0.03269
0.23978
0.13721
0.01178
0.01457
10.09 0.05021
Notes: Resid. df and Resid. dev are the residual degree of freedom and the
residual deviance at each step of the procedure, respectively; p(F) is the
probability statistics associated with the F test; Host diversity is the host
mammal species diversity per unit area; Sampling ⫻ Host is the two-way
interaction term between sample size and surface area, and so on (see text
for explanation). The rank of introduction of terms in the successive models
did not alter the main results as illustrated here.
species richness variation across different areas,
notably in the case of the largest areas where rare
parasite species may be missed during parasitological investigations. This point has been made before
(Gregory 1990; Poulin 1998b), and sampling effort
must be taken into account in any investigations of
species–area relationships using parasite data. We
also strongly recommend the use of multivariate
analyses to take into account perverse effects
exerted by sampling bias on statistics instead of a
priori regressing species richness data against sampling and the use of residuals since sampling effort
may also covary with other independent variables
under study.
2.3.2.2 Species richness–isolation relationship
More generally, species diversity is dependent on the
fragmentation and isolation of habitats (Whittaker
1998). Fragmentation and isolation have promoted
organism speciation and the build-up of endemic
faunas on Earth (Brown 1995). Isolation and fragmentation are, of course, one part of the many factors promoting species diversity and composition
(see Brown 1995; Rosenzweig 1995; Gaston and
Blackburn 2000). Most organisms, including parasitic and infectious diseases in hosts (this chapter),
exhibit patterns of similarity in composition and
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
richness depending on geographic distance and
isolation (see Poulin and Morand 1999; Morand and
Guégan 2000b).
Perhaps one of the most important lesson to be
learned from recent studies in host–parasite systems
is the demonstration by Poulin and Morand (1999)
that the geographical distance between component
communities of parasites in freshwater fish is often
the best, most general explanation of similarity in
parasite species composition and to a lesser extent,
of species richness across localities. Using multivariate analysis based on permutation methods (see
Legendre et al. 1994), these authors conclude that
patterns of parasite species composition across distinct isolated areas (i.e. distinct lakes in their study)
strongly depend on the distances that separate the
different localities, shorter geographical distances
between isolated areas being associated with a
greater similarity in parasite composition between
them, and nearby lakes harbouring numbers of parasite species more similar than those of distant localities. Put in other words, there is in these
parasitological data a tendency for species composition and richness to be autocorrelated over space.
As mentioned by Poulin and Morand (1999), it
might be more accurate to say that it is the isolation
of a given locality within the network of patch areas
that here matters instead of geographical distances
among sites that roughly approximate this isolation.
It is possible to have exceptions to this pattern, and
many other factors may promote similarity between
close localities in the composition and richness of
parasite communities (see Kennedy et al. 1991;
Hartvigsen and Kennedy 1993; Poulin 1998a).
Nevertheless, the authors strongly suggest to consider the effect of geographical distance as a good
index of isolation in further comparative analyses of
parasite communities, and it should therefore
become a basic requirement to control for the confounding and often important effect of geographical
distance on the determinants of species composition
and richness in parasite component communities.
Recently, Poulin (2003b) has shown that the influence of geographical distance on the similarity
between parasite communities may follow a regular
pattern. In the majority of parasite communities of
fish and mammal hosts, the similarity in the species
29
composition of communities decays exponentially
with increasing geographical distance between
localities (Poulin 2003b). Exponential rates of decay
in similarity have also been reported for plant communities (Nekola and White 1999), and further
emphasize the importance of geographical isolation.
One illustrative example of the effect of geographical distance and isolation on parasitic and infectious
disease communities is that of oceanic islands.
Typically islands have fewer species per unit area
than the mainland, and this distinction is more
marked the smaller the island and the farthest it is
from a continental source (Rosenzweig 1995;
Whittaker 1998). Very few studies have investigated
parasite species community richness and composition on islands (see Kennedy 1978; Mas-Coma and
Feliu 1984; Kennedy et al. 1986a; Dobson 1988a;
Dobson et al. 1992a; Miquel et al. 1996; Goüy de
Bellocq et al. 2002, 2003). The main conclusions
reached by Dobson et al. (1992a) concerning parasite
species richness and composition in Anolis lizards
from northern Lesser Antilles islands are that they
show a relatively depauperate parasite community
when compared with lizards sampled on the larger
Carribean islands, for example, Cuba, or on continental areas, and that these differences are associated
with the life history attributes of the different parasite
species in the assemblages. On the whole, Goüy de
Bellocq et al. (2003) reach the same conclusions (see
above), but they were unable to more formally characterize an effect of geographical distance and isolation in-between Mediterranean islands on parasite
species richness and composition in the woodmouse.
Examples of studies of pathogen communities and
species composition in animals and humans on
islands are even more scarce. Collares-Pereira et al.
(1997) provide the first epidemiological data on pathogenic leptospires serovars diversity in insectivore
and rodent species in the Azores archipelago, and
they conclude to a low serovars diversity of three
within this group of islands out of a total of nineteen
serogroups more largely represented over the world.
Surprisingly, there are only few studies that have
quantified pathogen species richness and composition on islands for human communities in a way similar to what is traditionally done in community
ecology. Based on unpublished data from one of us
PA R A S I T I S M A N D E C O S YS T E M S
(Guégan and Guernier, unpubl. data), we show here
that on a total set of 197 different countries all over
the world, the species richness of pathogens including viruses, bacteria, fungi, protozoa, and helminths
is lowest on the 73 islands compared with the mainland countries (see, Table 2.2). Even after controlling
for confounding effects that may be exerted by factors like the socio-economical power, the population
size in number of inhabitants or the latitudinal position of the country, the island factor still explains
24.1% of the total variation in pathogen species diversity across areas. This result on pathogen species
assemblages in humans is indicative that isolation
and/or distance from a continent may be highly
responsible for lower species richness in those localities. As suggested by the work of Goüy de Bellocq
et al. (2003), islands sample only from the dispersive
portion of the mainland pool. This effect must, of
course, be distinguished from area size since the
human pathogen study (see Table 2.2) has kept its
effect constant in a multivariate analysis. Present-day
distances between isolated islands and a regional biogeographic pool, even if they do not strictly reflect
distances at the time of disease colonization, may
however provide a rough index of isolation.
Table 2.2 Summary of Generalized Linear Model with a poissonian
error structure and a log-link for explaining the species richness
variation in human infectious diseases across a set of 197 different
continental (124) or isolated (73) countries
Deviance
Null
265.56
Island
64.07
GNP
2.63
Population size
40.32
Surface area
19.60
Latitude
8.80
Island ⫻ Surface area 2.98
Resid. df
196
195
194
193
192
191
Resid. dev
201.49
198.86
158.54
138.94
130.14
127.16
p ( 2)
0.00000
0.10466
0.00000
0.00001
0.00301
0.08404
Notes: Dispersion parameter in the model is 0.67. Island is coded 1 and
continental area is coded 0; GNP is the Gross National Product per country
(in US $) to control for its effect on final statistics; Population size is the
number of inhabitants; Latitude is the geographical position of each country
in degrees and minutes; see also Table 2.1; p (2) is the probability statistics
associated to 2 test. Models were built with independent variables and
their two-way and three-way interaction terms. The rank of introduction of
terms in the successive models did not alter the main results as
illustrated here.
From the present human diseases data set, information concerning the Caribbean islands and the
surrounding continental countries from Northern,
Central, and Latin America representing the
mainland, it is informative to see that remote
islands from the Gulf of Mexico are poorest in
pathogen species when compared to what is
observed on the continent and even on close islands
like Trinidad & Tobago, for instance (see Fig. 2.3).
When considering the confounding effects exerted
by covariate factors (notably the economic power of
a nation) on disease species richness across localities, the influence of distance still remains (statistical data not illustrated): distance from a continental
regional pool (49.1% of the total variation
explained; p ⫽ 0.00001), the total area size of islands
(28.9% of the total variation explained, p ⫽ 0.00001),
and to a lesser extent human community size (5.9%
of the total variation explained, p ⫽ 0.028) are the best
predictors of pathogen species richness in human
populations among the nineteen Caribbean islands
and the fifteen surrounding continental countries.
These findings based on a study of community
assemblage of human diseases are in accordance
with studies on population dynamics of infectious
diseases on islands (see Black 1966). According to
5.5
Pathogen species
richness (in log)
30
1
5.4
2
5.3
3
4
5
6
5.2
5.1
9
7
5
8
4.9
0
2
4
6
8
Distance from a continental source (in log)
Figure 2.3 The relationship between log-species number and
log-distance (in km2) from the continent for human infectious diseases
in different Caribbean islands (n ⫽ 19) and surrounding continental
countries (n ⫽ 15) from Americas.
Notes: Codes are 1 : USA; 2 : Brazil; 3 : Venezuela and Mexico;
4 : Colombia and Panama; 5 : Surinam, Guyana, Honduras, Guatemala,
and Costa Rica; 6 : French Guiana, San Salvador, Trinidad & Tobago,
Puerto Rico, Nicaragua, Haiti, Dominican Republic, Belize; 7 : Guadeloupe,
Cuba, Martinique, Jamaïque; 8 : Dutch Antilla, 9 : Aruba, Caïman Islands,
Montserrat, Grenada, St Kitts & Neville, Antigua & Barbuda, Barbados,
St Vincent and Dominica.
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
Price (1990), as local host abundance increases, so
the effective population size for maintaining parasite
populations increases, resulting in more parasite
species being maintained in larger communities.
Thus species dynamics of infectious diseases might
be in many ways analogous to population dynamics (e.g. critical community size threshold), (see
Grenfell and Harwood 1997; Keeling 1997; Broutin
et al. 2004). There are obviously similarities between
species and population maintenance and dynamics
(see Brown 1995), and all these points need to be
developed in further research on infectious diseases
in wildlife and humans as we learn more about the
patterns of variation in infectious disease species
richness with respect to island size, isolation, and
host community size. The above findings do not
stipulate that modern events, and more particularly
transcontinental exchanges, do not influence infectious disease dispersal and maintenance in heterogeneous environments, but they strongly suggest
that we need to explore the impact of spatial heterogeneity on the course of infectious disease species
dynamics, and the importance of these variables,
for example, area size, isolation, community size,
to better grasp the abundance, distribution, and
identity of pathogen species within local habitats.
A major outcome of fauna (or flora) isolation is
endemism; thus old and/or remote islands tend to
generally have a large degree of endemism (see
Whittaker 1998). The term endemism refers to the
restricted ranges of taxa in biogeography, and it is
used differently in epidemiology–parasitology. We
refer here to the former definition. Little is known
about parasite or infectious disease community
assemblages in endemic hosts, and Morand
and Guégan (2000b) have concluded with some
predictions based on both empirical studies and
mathematical modelling that hot spots of (host)
endemism are also the foci for a large diversity of
endemic parasites and pathogens, and that
restricted areas and/or low host community sizes
are associated with a decrease in parasite or
pathogen species numbers (see above). Regarding
the existence of endemic parasites or pathogens, we
can only speculate on their existence on Earth, and
they are probably legions. Many parasitological
investigations have focused their efforts on the
31
impacts of exotic pathogens and pests on native
host species, but an important advance in future
research should be the recognition of endemic
parasites and pathogens, and the role they may
play in maintaining and regulating biodiversity and
ecosystem dynamics. Recent research on emergent
pathogens might shed light on their importance in
nature (see Aguirre et al. 2002).
2.3.2.3 Local–regional richness relationship
Much parasitological literature on species diversity
patterns has been devoted to local mechanisms
whereas in recent years large-scale processes have
been regarded as important determinants of the
species richness of local communities in free-living
organisms (see Lawton 1999; Gaston and Blackburn
2000). Implicit in many ecological studies is the
important recognition that regional and historical
processes may profoundly affect local community
structure (Brown 1995; Rosenzweig 1995; Lawton
1999, 2000). Questions of spatial scale have been
addressed only very recently in parasite community ecology (Price 1980; Aho 1990; Aho and Bush
1993; Kennedy and Bush 1994; Kennedy and
Guégan 1994; Barker et al. 1996) probably because
traditional parasitology has been too medically
orientated over a long time with a major focus on
very fine-scale studies.
Simply because every parasitic, parasitoid, or
even microbe species cannot be present everywhere,
we do not expect every species occurring within the
regional pool to affect the composition of every local
community. A central method used for the recognition of the importance of regional and local
processes is the regression of regional species richness against local species richness plots (see Lawton
1999; Srivastava 1999; Hillebrand and Blenckner
2002), and several contributions have tried to disentangle the regional and local constraints in free-living communities (see Srivastava 1999; Shurin and
Allen 2001; Hillebrand and Blenckner 2002, for
recent reviews). The test requires estimates of
species richness for a given group of organisms at
both local and regional spatial scales and a statistical evaluation of their relationship. When local
richness is regressed against regional richness and
the relationship is linear, the communities are
PA R A S I T I S M A N D E C O S YS T E M S
Local species richness
Boundary line
Type I
Type II
Regional species richness
(b)
(c)
Local species richness
(a)
Local species richness
32
Regional species richness
Regional species richness
Figure 2.4 The relationship between regional and local species richness for parasite, pest and pathogen organisms. (a) Because of the hierarchical
processes illustrated on Fig. 2.1, every parasite, pest or pathogen species present within the regional pool is unlikely to occur everywhere, which thus
determines a boundary line never reached for which y equals x. Local species richness both at the infracommunity and component community scales
are usually less than regional richness, and two kinds of relationships may then exist. A type I curve indicates proportional sampling in which local
species richness increases linearly with regional richness. A type II curve saturates with local species richness above a threshold for higher regional
richness. In nature, parasite, pest or pathogen community assemblages lie anywhere between type I and type II systems (see Cornell and Karlson
1997). (b) Example where the richest regional (component) communities are associated with the richest infracommunities and vice versa, suggestive
of no saturation in parasite species. Helminth parasites of introduced freshwater fish in the British isles (Guégan and Kennedy 1993) or of natural
populations of partridges in Spain (Calvete et al. 2003) are clear examples of unsaturated systems. (c) Examples where local species richness may be
fixed by internal constraints indicative of saturation in local species communities. Intestinal helminth infracommunities (see Aho 1990; Kennedy and
Guégan 1994; Calvete et al. 2004) generally are examples where saturation in parasite species may occur (see also text for contradictory results).
unsaturated and are said to exhibit ‘proportional
sampling’ of the regional species pools. If the relationship is a somewhat curvilinear function, the
possibility of saturation may then arise (see Fig. 2.4).
Although this type of analysis appears to be
straightforward, several pitfalls have been discussed elsewhere (see Creswell et al. 1995;
Srivastava 1999; Shurin et al. 2000). A major question
is the definition of what exactly regional and local
richnesses mean for parasite communities, and the
way their measurements are best comprehended
(Kennedy and Guégan 1994; Barker et al. 1996).
Usually, regional (Kennedy and Guégan 1994) or
continental (Aho and Bush 1993) parasite species
richnesses, that is to say spatial scales reflecting a
naturally occurring hierarchy from which local parasite communities may be drawn, have been used to
represent regional pools. Morand et al. (1999) used
another estimate of regional species richness
defined as the component community richness, but
the authors were faced to the problem of defining
exactly the spatial hierarchy at which processes may
operate in open marine systems. The measure of
local parasite species richness adopted sometimes is
the mean or maximum number of parasite species
in the parasite component communities known to
the authors (see Aho and Bush 1993; Kennedy and
Guégan 1994), but a more correct definition of local
species richness seems to be the mean (Kennedy
and Guégan 1994; Morand et al. 1999) or even maximum (Poulin 1996a, 1997; Calvete et al., 2004) infracommunity parasite species richness.
Generally, all the studies agree on an important
influence of both regional and local factors, but
their relative importance may differ between categories of organisms. Concerning parasite, parasitoid, and microbe species communities, the
diversity of species in local (at the host population
level) assemblages is intuitively regulated both by
local (e.g. interspecific competition, habitat heterogeneity) and by regional factors (e.g. evolution,
migration, history). The studies published so far on
free-living organisms have stressed the prevalence
of type I communities (see Fig. 2.4) interpreted as
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
an indication of unsaturation of local assemblages
with generally weak or no effects of local interactions
on species richness. Analyses of local to regional
species richness performed on host-associated
organisms like parasites or parasitoids (Cornell
1985; Aho 1990; Bush 1990; Hawkins and Compton
1992; Aho and Bush 1993; Lawton et al. 1993;
Dawah et al. 1995; Kennedy and Guégan 1994, 1996;
Poulin 1996a, 1997; Morand et al. 1999; Frenzel and
Brandl 2000; Calvete et al. 2004) have, on the
contrary, shown the existence of both type I and II
communities (see Fig. 2.4). Particularly, the commonness of type II communities in host–parasite
systems, and more specifically for helminths, may
be illustrative of limiting factors shaping these local
communities. In addition to the occurrence of
saturated assemblages shown in parasite systems
compared to other organisms, the three clearest
results that emerge from the published
parasitological literature available today may be
summarized as follows.
First, most studies on herbivorous insects (see
Dawah et al. 1995; Frenzel and Brandl 2000) and
fish ectoparasites, that is, helminths and copepods
(see Morand et al. 1999), have identified that empty
niches are common and that local communities are
unsaturated. As such, many natural enemy communities are subject to strong regional influences
then providing opportunities for new invasive
species to become established. The opposite can be
observed for many studies on internal parasites
like intestinal helminths of fish (Kennedy and
Guégan 1994), of amphibians and reptiles (Aho
1990), and of birds (Bush 1990; Calvete et al. 2004)
where local forces may contribute to parasite community structure. Poulin (1996a, 1997) showed, on
the contrary, that for 31 intestinal helminth communities in bird hosts and 37 in mammal hosts the
relationship between the maximum infracommunity richness and component community species
richness was linear, indicating the absence of
species saturation and the availability of vacant
niches in organisms accepted to generally have
species-rich helminth communities (see Bush and
Holmes 1986a,b; Stock and Holmes 1988). The contrasting results may in part be due to the fact that
33
Poulin’s (1996a, 1997) analysis included different
host species, whereas many of the studies that
found a curvilinear relationship between infracommunity richness and component community richness included only different host populations of
the same host species (e.g. Kennedy and Guégan
1996; Calvete et al. 2004).
Then, second, the only intestinal helminth communities which exhibit unsaturated assemblages
are those occurring in introduced fish species in
the British Isles, that consist of non native fishes
not having had enough time to accumulate sufficient helminth species from the native pool
(Guégan and Kennedy 1993) to develop ecologically interactive communities (Kennedy and
Guégan 1994). A recent study by Torchin et al.
(2003) which compared the parasite species richness between introduced and native populations
for 26 host species of molluscs, crustaceans, fishes,
birds, mammals, amphibians, and reptiles also
confirmed the reduced parasitization of introduced organisms suggestive of an absence of saturation in those parasite communities (see Figs. 2(c)
and (d) in Torchin et al. 2003).
Third, major advances in our understanding of
saturation versus non saturation of local parasite
communities have been made in recent years.
Cornell and Karlson (1997) and Srivastava (1999)
drew attention to the necessity of the demonstration of other lines of evidences of niche and habitat
relationships combined with information on local
versus regional relationships. In particular, Rohde
(1998) using randomization procedures highlighted the many scenarios in which a curvilinear
local to regional relationship might be generated
without requiring the necessity of species saturation. Using a comprehensive survey of marine fish
ectoparasite communities, Morand et al. (1999)
examined the effects of interspecific aggregation
on the level of intraspecific aggregation in infracommunities, and they demonstrated that interspecific interactions were reduced relative to
intraspecific interactions thus facilitating species
coexistence in rich communities (see Tokeshi 1999
for further details on species coexistence). This pattern was highly coincidental with a positive linear
34
PA R A S I T I S M A N D E C O S YS T E M S
relationship between infracommunity species
richness and total parasite species richness
obtained after controlling for the confounding
effect exerted by phylogeny, indicative of no saturation in ectoparasite communities of marine fish
(see Rohde 1991, 1998). In a recent study, Calvete et
al. (2004) showed the existence of a curvilinear
relationship between local and regional species
richnesses of intestinal helminth infracommunities
for eight populations of the red-legged partridge in
Spain, even after checking for the confounding
effect of geographical distance among localities
on species richness calculations. Interestingly,
this finding was confirmed by a demonstration of
negative interspecific associations for the
helminth species community, especially between
cestodes and other helminths parasitizing the bird
intestines.
All these results illustrate a number of important
issues about the understanding of local–regional
richness relationships in parasite or microbe community assemblages. First, demonstrating the
effects of saturation, or not, in infracommunity
assemblages requires that we simultaneously use
additional investigations of interspecific interactions, or that published examples of the types of
interactions exist, to test for the possible existence
of interspecific competition. Neither of the two
patterns for community assemblage organization,
that is, the local to regional richness relationship
and the demonstration of interspecific competition, is conclusive on its own. Interestingly, conclusions about the degree of concordance in the
saturation of local communities, or not, between
two or more methods may yield generality, but
most of studies to date have only considered one
option to test for the shape of interspecific relationships (but see Calvete et al. 2004). Second, the
study of interspecific competition in local communities of parasites and pathogens has shaped the
development of our understanding of species
interactions, that is, importance of local processes.
Thus, consideration of local to regional richness
relationships in parasite or pathogen communities
should lead to more attention being paid to the
importance of large-scale patterns in parasitology
and epidemiology. Third, one area in which the
combination of these two methods should be fruitful is in the connection that might exist with the
density of parasites or microbes. Indeed, if competition is important within parasite or microbe communities, one would expect to see density
compensation in those communities with few
species. If complete compensation occurs, there
should be no relation between parasite density or
biomass and local species richness, while if there
was no density compensation a linear trend would
thus be expected (see Oberdorff et al. 1998; Griffiths
1999 for taxonomic groups others than parasites).
Furthermore, the linkages between interspecific
competition, (un)saturation and density compensation in parasite or microorganism community
assemblages will require more research from community ecologists, parasitologists and epidemiologists. Notably, these issues should be highly
relevant in the field of veterinary and medical sciences since any alteration of local habitats (from
the point of view of one parasite species, for example, one intestine) and other disturbances exerted
by humans (e.g. the use of drugs like helminthicides or antibiotics) should reduce parasite or
pathogen populations from time to time, making
ways for more resistant species or aliens to increase
or to invade. The idea of saturation predicts that an
invasive species (like a crop or an emerging virus)
should not invade an infracommunity in individual hosts, or should do so only with the consequence of excluding a resident member species,
that is, density compensation by new individual
invaders. The study of interconnectedness between
these patterns and our efforts at understanding the
processes behind will require judicious choices of
both host and parasite or pathogen taxa, and at different levels of spatio-temporal organization. As
discussed before, patterns of within-host microbial
species richness will also likely profit from a
greater consideration of dynamical processes in
patchy and discontinuously distributed environments, microbial persistence, and abundance in a
particular tissue-habitat being influenced in several ways by biogeographical-like processes within
host individuals.
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
2.3.2.4 Latitudinal gradient in species richness
Latitudinal gradients in species richness of
free-living organisms are one of the most consistent
large-scale trends that we can observe in nature,
and one of the best documented patterns in the
ecological literature (see Hawkins et al. 2003 for a
recent review), but there are still exceptions (Brown
1995; Rosenzweig 1995; Gaston and Blackburn
2000). This pattern does hold not only for the
hosts as a whole, but also for some parasitic and
infectious disease organisms (Rohde 1992; Poulin
and Rohde 1997; Rohde and Heap 1998; Calvete
et al. 2003; Guernier et al. 2004; but see Poulin 2001;
Poulin and Mouritsen 2003), which means that
it could be a simple consequence of the observed
latitudinal cline in host species diversity.
Parasitological or epidemiological investigations
on large spatial scales are rare, and there is
undoubtedly a need for more comparative studies.
Expectations of rich low-latitude parasite communities have been suggested by some authors
(Kennedy 1995; Salgado-Maldonado and Kennedy
1997) while it is intuitive from other studies (Poulin
and Guégan 2000; Guégan et al. 2001) that a latitudinal richness gradient exists for fish ectoparasite and human infectious disease communities,
respectively.
Across 80 localities from 16 Spanish provinces,
there is a marked cline in helminth species richness
and composition in the red-legged partridge
(Alectoris rufa L.) (Calvete et al. 2003). The highest
levels of helminth richness are encountered in
southern provinces of Spain (e.g. Badajoz, Huelva)
and the lowest in northern ones (e.g. Alava Burgos
Santander, Alava Navarra) (Calvete et al. 2003).
Statistical analyses controlled for the effect of host
age, sex, body condition, and time at which the
study was carried out, and thus it is unlikely that
these variables contributed to the spatial variation
in helminth distribution and species richness across
the study area. The cline in parasite species richness
and composition across Spain was mirrored by the
measures obtained for both infra- and component
communities levels, indicating that the poorest
component communities in the north correlated
well with the poorest infracommunities. In the
35
north, parasite communities were characterized by
having one, that is, Dicrocoelium sp., or a few dominant widespread species. In contrast, in southern
provinces, helminth communities were more
species-rich with several codominant helminth
species, Raillietina tetragona, Subulura suctoria,
Cheilospirura gruweli (see Calvete et al. 2003 for
further details). The answer to why there are more
helminth species in the red-legged partridge in
southern Spanish provinces than in the north is that
the pattern may be related to variation in definitive
host densities and to the distribution and diversity
of intermediate hosts. According to Calvete et al.
(2003), red-legged partridge populations are usually denser in the centre and south of Spain which
represent the core-area of their range. This finding
would tend to suggest that high densities of definitive hosts might be associated with a greater
abundance of helminths and greater helminth
species richness as a whole. In addition, and this
second hypothesis is not mutually exclusive of the
definitive-host density hypothesis, a greater abundance or diversity of arthropod intermediate hosts in
the centre and south of Spain might result in the
exposure of partridges to a wider variety of potential parasite species (see Poulin 1995a). Calvete et al.
(2003) argued, based on correlation statistics using
factorial scores from multivariate analysis, that the
north–south abundance and richness variation of
helminths in partridges might be to a large extent
determined by higher temperature in southern
regions of Spain, environmental conditions causing
an increase in the survival or activity of intermediate forms of parasites with life-history stages outside their definitive hosts. These results suggest
that variation in the distribution of helminths
in partridge hosts are probably associated with
variations in the distribution of their definitive
and intermediate hosts and the local ecological
conditions that may act on these host–parasite
relationships.
One recent study (see Guernier et al. 2004) goes
one step further in the explanation of the existence
of a latitudinal gradient of species richness for
pathogen species in human populations. Compiling
data on parasitic and infectious diseases for a total
36
PA R A S I T I S M A N D E C O S YS T E M S
set of 229 different species of pathogens in human
hosts, including bacteria, viruses, fungi, protozoa,
and helminths, Guernier and colleagues (2004)
showed that after correcting for cofactors, that is,
area, socio-demographic variables, physical and
environmental parameters, that could exert a
strong influence on the relationship between latitude and parasitic and infectious diseases species
richness, one still observes that the species richness
in human pathogens is strongly correlated with
latitude (Fig. 2.5) with, on average, tropical areas
harbouring a higher pathogen diversity than more
temperate areas. This new result shows that
(a)
pathogen species richness is not distributed homogeneously across the planet but there is a marked
cline with the highest levels of parasitic and infectious diseases species diversity near the Equator,
and the lowest in northern areas. The cline in
pathogen species richness occurs for the vast majority of groups of pathogens the authors analysed
(7 times out of 10, exceptions being bacteria, viruses
with direct transmission, and fungi). Interestingly,
this similarity between many free-living organisms
and pathogens is useful, because several common
extrinsic and/or intrinsic factors might cause these
common sets of pattern. Other variables are indeed
(b)
0–10%
60°
60
10–20%
20–30%
30–40%
40–50%
40°
40
50–60%
60–70%
70–80%
80–90%
20°
90–97%
Latitude
97–100%
0°
Northern hemisphere
(172 countries)
20°
Equator
40°
Southern hemisphere
(52 countries)
60°
0.10
0.00
0.10
0.20
PID species composition
PID species richness (residuals values)
Figure 2.5 (a) Relationship between parasitic and infectious disease species richness and latitude in human populations across the two hemispheres.
Linear relationships between species richness and latitude (dotted lines) are highly significant (F ⫽ 12.29, df ⫽ 29, p ⫽ 0.0015 and F ⫽ 18.01, df ⫽ 130,
p ⬍ 0.0001 for Southern and Northern hemispheres, respectively). Residuals of species richness on the x-axis were extracted from minimal GLIM
models controlling for the effects of confounding factors on disease species diversity estimates. Latitudes are expressed in degrees. (b) Presence/
absence matrix for the 229 distinct parasitic and infectious disease species across the two hemispheres. The spatial distribution of pathogen species
were organized according to the procedure adopted by the ‘Nestedness Temperature Calculator’ (see Atmar and Patterson 1995). One hundred and
seven ubiquitous pathogen species where eliminated from the entire data base since information they contained where entirely redundant with
the most ubiquitous species already present into the matrix. Figure 2.5 (b) was generated after 1000 randomized permutations. This distribution is
nonsymmetrical because of the 224 studied countries, 172 countries are found in the Northern hemisphere versus only 52 in the Southern one.
Figure 2.5 (b) indicates that species diversity decreases as we move northwards or southwards from the equator (F ⫽ 28.2307, df ⫽ 161, p ⬍ 0.001).
The occurrence boundary lines (black exponential curves) were fitted by non-linear regression (y ⫽ 1.51 ⫹ 20.01e–0.29x and y ⫽ 1.65 ⫹ 35.87e–0.36x
for Northern and Southern hemispheres, respectively). See Guernier et al. (2004) for further details.
Source: Courtesy by PloS (Biology).
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
important in explaining global-scale patterns of
human pathogens (e.g. modernization, urbanization, or impoverishment, especially in developing
countries), but the fact that the authors considered
such effects in their multivariate analyses tends
to indicate that biogeographical forces are also
important indeed in shaping the distribution and
abundance of pathogen species. These results thus
challenge the conventional wisdom that socioeconomic conditions are of preponderant importance
in controlling or eradicating diseases.
Over the last three decades, the number of
hypotheses advanced to explain the latitudinal
gradient has increased from six (Pianka 1966) to
nearly thirty, proffered by Rohde (1992). Some of
these include spatial heterogeneity and patchiness,
competition, predation, parasitism, mutualism,
area, environmental stability, productivity, seasonality, solar energy (see Rohde 1992 for a general
description). In reality, several factors may be
acting in concert or in series, and among the
numerous explanations given it is possible to
substantially narrow the list of the most plausible
explanations since many factors may be entirely
redundant or untestable (Hawkins et al. 2003). For
instance, Gaston and Blackburn (2000) listed only
three plausible explanations for latitudinal richness
gradients: area, energy, and time. They discarded
the possibility that random location of species
might be responsible for the latitudinal species
gradient based on the absence of formal evidence.
Area has often been cited as a simple hypothesis
(see section on species–area relationships) to
explain that the tropics, which really harbour the
highest richness for many groups of organisms,
also have the largest terrestrial surface area, that is,
the geographical area hypothesis (see Rosenzweig
1995). This explanation may not be plausible when
considering the latitudinal gradient of pathogen
species in human populations as observed by
Guernier and colleagues since both the surface area
and continental mass effects have been taken into
account in multivariate analysis.
Furthermore, and probably more important than
the existence of a latitudinal gradient in species
richness is the demonstration of an overall pattern
of spatial distribution of parasitic and infectious
37
diseases species in human populations on Earth
that conforms to a nested species subset hierarchy
(see Guégan and Hugueny 1994; Guégan et al. 2001;
Guernier et al. 2004). Nestedness structure indicates
that species (here pathogens) that compose a
depauperate community (here temperate conditions) statistically constitute a proper subset of
those occurring in richer communities (here
warmer conditions in tropical areas), but the
converse situation, that is, pathogen species solely
occurring in depauperate communities but not in
the richest ones, is either not found or not properly
substantiated. This pattern, although not considered in the ecological literature (but see Gaston and
Blackburn 2000 who suspected the existence of a
connection between the two patterns; see later),
was strongly associated with latitude, indicating
that the progression of pathogen species richness is
from species-poor countries in more temperate
areas to species-rich ones when reaching tropical
zones (see Fig. 2.5).
Using Monte-Carlo simulations (see Manly 1991;
Guégan and Hugueny 1994) to test the hypothesis
of parasitic and infectious diseases spatial organisation on the largest scale, Guernier et al. (2004)
assessed the degree of nestedness of the system
using two different but complementary programmes: (i) ‘Nestedness’ (Guégan and Hugueny
1994) and (ii) ‘Nestedness Temperature Calculator’
(Atmar and Patterson 1995). In the former programme, pathogen species were either selected
with uniform probability (R0) or with a probability
proportional to their incidence (R1) (Guégan and
Hugueny 1994) whereas in the latter one only a R00
procedure was retained (Atmar and Patterson
1995); (see also Wright et al, 1998; Cook and Quinn
1998; Gaston and Blackburn 2000 for further
details). Results from Monte Carlo simulations
showed that the global distribution of human
pathogens was strongly nested (Ns ⫽ 2481.4, R0 and
R1 procedures, p ⬍ 0.0001), with some slight differences that were found across the different groups of
aetiological agents (all groups, p ⬍ 0.0001, but
except for vector-borne viruses, with the R1
procedure (Ns ⫽ 1787, p ⫽ 0.0015). When considering the Northern and Southern hemispheres
separately, both were highly nested (R0 and R1
38
PA R A S I T I S M A N D E C O S YS T E M S
procedures, Ns ⫽ 6602, p ⬍ 0.0001 and Ns ⫽ 1230,
p ⬍ 0.0001, respectively). This was confirmed by
the R00 procedure used by the ‘Nestedness
Temperature Calculator’ program (Atmar and
Patterson 1995), which provides a useful graphic
representation of the results (Fig. 2.5), showing that
parasitic and infectious diseases species diversity
decreases as we move northwards or southwards
from the equator (F ⫽ 28.2307, df ⫽ 161, p ⬍ 0.001),
(see Guernier et al. 2004). Results from all three
nestedness models (see Wright et al. 1998)
explained reasonable amounts of the nested pattern
in human pathogen species across latitudes.
Wright et al. (1998) have suggested a cogent
explanation for nestedness as a series of probabilistic filters, screening species with particular characteristics: local habitat suitabilities, differential
colonization capacities of species, and sustainability of viable populations within their environment.
Additionally, as pointed out by Gaston and
Blackburn (2000), nestedness might be an inevitable
second-order consequence of the same factors that
cause variation in species richness and range size
along latitudinal gradients. It is exactly the view
with which Guernier et al. (2004) totally agree with
the example of pathogen species diversity in
human on a broad-scale.
Searching for the common causes explaining the
existence of both patterns, i.e. gradient in species
richness and nested structure, for parasitic and
infectious diseases diversity and composition in
human communities, Guernier et al. (2004) retained
the energy hypothesis as a likely candidate for
explanation. The energy hypothesis is a climatebased hypothesis that claims that energy availability generates and maintains species richness
gradients (see Hawkins et al. 2003 for a recent
review). Many studies have successfully correlated
gradients in species diversity with variation in the
climatic environment, a relationship thought to
shape large-scale biogeographic patterns (Hill et al.
1999). The authors decomposed the potential effect
of climate on pathogen diversity into Pearson’s
correlations to more deeply analyse the kinds
of relationships between each of the four climatic
variables and disease richness under study.
The results show significant positive correlations
between pathogen species richness and the
maximum range of precipitation after Bonferonni
multiple correction for all six of the parasite or
infectious disease taxa considered: bacteria
(r ⫽ 0.3545, df ⫽ 213, p ⬍ 0.0001), viruses directly
transmitted from person-to-person (r ⫽ 0.2350,
df ⫽ 215, p ⬍ 0.0001), viruses indirectly transmitted
via a vector (r ⫽ 0.3575, df ⫽ 215, p ⬍ 0.0001), fungi
(r ⫽ 0.3554, df ⫽ 216, p ⬍ 0.0001), protozoa
(r ⫽ 0.3744, df ⫽ 216, p ⬍ 0.0001), and helminths
(r ⫽ 0.4270, df ⫽ 215, p ⬍ 0.0001). On the other
hand, the relationship between pathogen species
richness and monthly temperature range was only
significant for three groups of pathogens: bacteria
(r ⫽ 0.3016, df ⫽ 213, p ⬍ 0.0001), viruses directly
transmitted (r ⫽ 0.2142, df ⫽ 214, p ⫽ 0.0015), and
helminths (r ⫽ 0.2590, df ⫽ 213, p ⫽ 0.0001). No
relationship between parasite species richness and
mean annual temperature appeared to be significant after Bonferroni corrections. Finally, only the
relationship between bacterial species richness
and mean annual precipitation was significant
(r ⫽ ⫺0.1987, df ⫽ 213, p ⫽ 0.0034). No or very
slight differences between total and categories of
pathogen species richnesses and some climatic
factors were observed between Northern and
Southern hemispheres.
Many factors are involved in the determination
of the climate in an area, particularly latitude,
altitude, and the position of the area relative to
oceans and land masses. In turn, the climate largely
determines the species of plants and animals
that live in those areas. According to the results
of Guernier et al. (2004), the maximum range of
precipitation is highly correlated with latitudinal
gradient of pathogen species, the parasitic species
diversity significantly increasing with this climatebased factor. Interestingly, the variation of precipitation around the mean was overall a better
predictor of pathogen species distribution than its
average value, thus indicating that pathogen
species, their vector and host populations might
best function over only a wide range of precipitation, which is actually found in many tropical
regions of the world, those regions having more or
less distinct wet and dry seasons during the year.
Many parasites obviously require water as the
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
basic medium of their existence, and many others
strongly need wet conditions to complete their life
cycle, for example vector-borne diseases. Often,
many microorganisms are also constrained by the
humidity of the atmosphere. Undoubtedly, the
physical factor of precipitation variation may affect
parasitic and infectious microorganisms, vectors
and/or hosts over a range from low precipitation
variation at one extreme, for example, deserts, to
high precipitation variation such like in the tropics.
This relationship might be related to biological
cycles and a variety of features in parasitic and
infectious stages that have evolved so that they are
specifically well adapted to the variability of precipitation. So, prolonged drought should not be
fatal for some well-adapted microbes if wet conditions are encountered once to complete their life
cycle. Curiously, average precipitation was not
retained as a good candidate for explaining the latitudinal gradient of pathogen species diversity
except for bacteria (see Guernier et al. 2004). If we
consider the Earth as a simple body with an environmental gradient, such as the annual precipitation range, which runs from wet and hot equatorial
regions northward and southward to Arctic and
Antarctic areas with harsh conditions, then distance
and isolation from pathogen species-rich regions in
the tropics may screen pathogen species by their
extinction and colonization tendencies. Moreover,
habitat suitability, for example presence of new
hosts and reservoirs, and passive sampling may
screen them by their habitat preference and availability, and abundance, respectively. Guernier et al.
(2004) reached the same conclusions as Calvete et al.
(2003) indicating that parasite species richness, their
spatial distribution and organization on very different scales, climate-based forces, and the interplay
between habitat conditions and host–parasite interactions might be intimately connected to generate
the observed patterns of parasite species diversity.
The overall conclusion that can be drawn from
this section on the latitudinal gradient in species
richness for parasite and pathogen organisms is that
a better understanding of parasitic and infectious
diseases species diversity and community dynamics
over wide ranges of spatial scales is now clearly
needed. The similarity in the patterns of some
39
parasitic or pathogen taxonomic groups and
free-living organisms suggests that common mechanisms are at work. Regardless of whether the
richness of parasitic and infectious diseases simply
tracks host diversity or, rather, is determined to a
greater extent by exogenous factors, for example,
climate-forced variables, is now a challenge that
needs to be pursued in parasitology and epidemiology. In addition, the significant findings illustrated
in this and other sections confirm that investigations
on parasite and microorganism community assemblages should also be performed at greater scales
than the scale at which local variation in species
richness and composition is too often examined.
Integration of systematics, biogeography, population and species dynamics, community ecology,
and evolutionary biology is now essential for
a complete understanding of the many scaling
processes affecting parasitic and infectious diseases.
2.4 Linking parasite and microorganism
communities and ecosystems. Directions
for further work
The results summarized above underscore the
important role of large-scale determinants on local
parasite and pathogen community organization and
assembly processes. They suggest that the success of
invasive parasite species may vary depending on
how physical conditions, for example, size of the
area, geographical distance from a continental
source, affect the rates of colonization. Additionally,
the regional effects on local parasite or microorganism species richness also tend to suggest that
research should be directed at regional processes
and their effect on local diversity, regional processes
being just as important as local ones in setting levels
of richness in parasite or microbe communities.
Then, the existence of a latitudinal gradient of parasite and microbe species richness both at subregional
(gut helminths in Spanish red partridges) and global
(infectious diseases in human populations) scales
confirms that investigations on parasites and
microorganisms should expand the scale at which
local variation is traditionally examined. More
interestingly, the demonstration of the existence of
a nested species subset pattern for human infectious
40
PA R A S I T I S M A N D E C O S YS T E M S
diseases (also true for gut helminths in Spanish red
partridges) suggests that the interplay between welldifferentiated species of pathogen species within
assemblages and distinctive requirements for
resources, including micro- and macro-habitats, contribute to the overall nestedness pattern and species
diversity we observed.
It is important to recognize that similar patterns,
that is, species area, species isolation, local to global
relationships, and latitudinal gradient in species
diversity, have been observed for many free-living
taxonomic groups (see Gaston and Blackburn 2000;
Hawkins et al. 2003), suggesting that common
mechanisms might be at work in generating the
observed patterns of species diversity for parasitic
and infectious agents (see previous sections). But
what kinds of common properties and characteristics between, say, a virus species and a bird
species, may produce similar patterns?
So far, the concern of parasitology and epidemiology has been widely aimed at defining the characteristics in which pathogens may differ from
other groups, focusing on details instead of searching for similarities. One pattern that appears to be
pervasive across many communities, parasites,
microbes, and free organisms alike, and at different
spatial hierarchical scales, is the nested species subset pattern. Nested patterns were observed in some
parasitological–epidemiological studies (Guégan
and Hugueny 1994; Hugueny and Guégan 1997;
Guégan and Kennedy 1996; Guernier et al. 2004;
Poulin and Valtonen 2001, 2002; Vidal-Martinez
and Poulin 2003), but in many other cases communities were observed to form random, unstructured
assemblages (Rohde et al. 1994, 1995, 1998; Poulin
1996a,b; Worthen and Rohde 1996). The previous
sections make clear something that should be obvious, that is, that the four patterns documented
above are not independent of each other. Morand
et al. (2002) have provided a cogent explanation
for the generation of nested patterns in parasite
communities, thus reinforcing the importance of
both spatial and demographic stochasticity in parasite species distribution and composition. Fig. 2.6
illustrates the way Morand and collaborators
synthesize the hypothetical distributions of parasite species among local communities and the many
factors that may be implied in shaping these
communities. Considering that nested versus
non-nested species patterns are strongly linked
to unimodal versus bimodal species frequency
distributions, respectively (Morand et al. 2002), the
authors concluded that observed patterns should
be the result of differential colonization/extinction
processes acting at the level of each parasite
(or pathogen) species. Differential colonization/
extinction processes, also called epidemiological
processes in the field of epidemiology (see
Anderson and May 1991), are attributes of parasite
or microbe species, and are related to birth
and death processes in population dynamics (see
Morand et al. 2002). Assemblages of microbes
and parasites displaying nestedness on different
hierarchical scales, ranging from within individuals
of the same host population to the global scale, as
shown in the present chapter, provide a strong
indication that the same forces are at work across
different spatial and temporal scales.
So what emerges from this concept is that both
the recruitment of parasite (or pathogen) species
from local (host) patches and the differential capacities of parasite (or pathogen) larval or adult forms
to colonize those patches may have strong impacts
on the composition and richness of those communities from the local to the global scale, and vice
versa. This is an approach which is roughly similar
to that adopted by metapopulation biologists
(see Hanski 1999; Hanski and Gaggiotti 2004) and
ecologists working on the diffusion of infectious
diseases (see Grenfell and Dobson 1995; Diekmann
and Heesterbeek 2000), and in which invasibility
is a key factor for explaining local presence and
distribution of a given species.
Invasibility is dependent on the availability of
local resources and potential competition with local
species, for example, presence of empty niches. In
mainstream ecology (see Elton 1958), it has been
hypothesized among other predictions that greater
diversity should increase resistance to invasions
because the levels of limiting resources are generally lower in more diverse habitats (Tilman et al.
1996; Knops et al. 1999), thus giving rise to the
so-called diversity–invasibility hypothesis. A
decrease in host species diversity allows remaining
E M E R G E N C E O F S PAT I A L PA R A S I TO L O G Y A N D E P I D E M I O L O G Y
41
Large area size
Wide habitat types
Low isolation
Small area size
Specific habitat types
High isolation
Low probability
of invasion
High probability
of extinction
Parasite species
(by rank)
High probability
of invasion
Low probability
of extinction
Localities
(by rank)
species to increase in abundance as a result
of decreased competition for limiting ressources,
a phenomenon called density compensation by
ecologists (see Begon et al. 1996). As a result, the
increase in remaining host abundances should facilitate the invasibility of parasite or microbe species
(Anderson and May 1978; Burdon and Chilvers
1982; Antonovics et al. 1995). Indeed, host living in
high densities may harbour a high diversity of
parasite species (Morand et al. 2000; Poulin and
Morand 2000; Stanko et al. 2002), which in turn
often achieve high abundances (Arneberg et al.
1998a). Not all available results agree with this,
however (Stanko et al. 2002). Hence, both host
diversity and disease invasibility are related to host
species abundances within communities (Burdon
and Chilvers 1982; Mitchell et al. 2002). As already
stated, this hypothesis has received some support in
general ecology (Tilman 1997), but further work
needs to be done in both parasitology and epidemiology to determine whether higher parasite (or
microbe) species diversity at different hierarchical
scales, that is, within-host, within-population,
and within-metapopulation community dynamics
protects parasite or pathogen communities from
invaders (but see Torchin et al. 2003).
Another prediction available from the general literature is that greater species diversity of microbes
or parasites should decrease the severity of each of
Figure 2.6 Nested (versus non-nested) species
subset patterns are strongly associated with an
interplay of specific characteristics of parasite
(or microbe) species themselves) and local
habitat conditions to sustain or not a given
parasite (or microbe) species population and
its life-cycle associates, for example, vectors,
reservoirs. Parasite (or microbe) community
ecology would benefit greatly by considering the
importance of epidemiological patterns in
generating the processes observed.
the component diseases, a theorem which is called
the species composition–disease hypothesis (see
Elton 1958). This hypothesis predicts that any
changes in parasite or microbe community composition within a host community should impact on
the severity and virulence of one, or a group of,
diseases, which then proliferate to the detriment
of other parasite or microbe species. Both these
hypotheses, that is, the diversity–disease hypothesis
and the species composition–disease hypothesis,
have received some empirical support from the
plant disease literature (Knops et al. 1999; Mitchell
and Power 2003), but they have never been tested
to our knowledge in the case of both animal or
human pathogens. Research on community ecology
of parasite or microbe species, at the different
hierarchical scales discussed in the present paper,
should clearly benefit from developing both experimental designs and comparative studies to explore
in greater detail the potential linkages between
species diversity and composition, invasibility, and
other life-history traits such as virulence.
In addition, theoretical studies on parasite (or
microbe) invasibility rest upon epidemiological
principles, in which the local abundance of hosts is
the key determinant of whether a parasite can establish into a naïve host population (Anderson and May
1978; Burdon and Chilvers 1982; May and Anderson
1978). Within the study of human infectious
42
PA R A S I T I S M A N D E C O S YS T E M S
diseases, recent investigations have clearly illustrated the importance of local community size
for the maintenance and diffusion of, in particular,
childhood diseases (see Grenfell and Harwood 1997;
Rohani et al. 1999; Dieckmann and Heesterbeek 2000;
Grenfell et al. 2001). Unfortunately, very few studies
have gone a step further in demonstrating that
higher local abundance in hosts should yield higher
parasite or microbe species diversity (but see Poulin
and Morand 2000).
For macroparasites, and especially for contacttransmitted microparasites, both high parasite
abundance and high parasite species richness
should be attained more easily at high host abundance or density. This is expected from epidemiological theory (see Grenfell and Dobson 1995)
and supported by empirical studies on the determinants of parasite species richness (see Poulin and
Morand 2000, and the present chapter). Indeed,
host abundance/density is positively correlated
with parasite (or microbe) species richness in
several groups of vertebrates (Poulin and Morand
2000). This trend has yet to be demonstrated for
human populations (and plant pathogens as well)
in which large communities as resources should
harbour and sustain a greater diversity of
pathogens over space and time. Some, though very
few, studies have even shown that parasite species
richness covaries positively with host species richness across localities, an interesting finding that is
yet to be more seriously quantified across different
host taxonomic groups (Krasnov et al. 2004).
Any loss of host biological diversity should intuitively have a direct influence on the diversity and
abundances of parasites or pathogens, and in turn
on their virulence and pathogenicity within host
populations. In addition, changes in host community composition should also influence the component community of parasites or microbes living
there. Host species diversity should not randomly
affect parasite species richness and composition as
some of them will be more affected than others
depending on the exact causes of diversity loss.
This loss may depend on habitat fragmentation,
which should impact on rare host species living
at low abundance, or may be due to landscape
changes, which may influence the more adapted
host species, and thus will favour either the spread
of rare species or invasion by exotic species
(Daszak et al. 2001). Unfortunately, we cannot easily
refer to parasitological or epidemiological studies
on animals or humans that have specifically tested
these different hypotheses. Further empirical studies are thus needed, which should contribute to a
better understanding of how native host species
and their associated parasite or pathogen species
may prevent or limit the attacks of invaders (see
Torchin et al. 2003).
In summary, there are, of course, other interesting parasitological or epidemiological patterns that
are not discussed in the present chapter. However,
our aim here was to argue that both parasitology
and epidemiology would first largely gain from
developing both a much broader perspective and a
more quantitative approach, as advocated recently
by both macroecologists and community ecologists.
Parasitology and epidemiology are two scientific
fields that have evolved with an individual-centred
research perspective, and which have then concentrated their research efforts on only local phenomena over the past decades. One important message
from the present work is clearly that we need to
adopt a much broader research perspective in
parasite (or microbe) community ecology. Second,
we are also intimately convinced that a better consideration of the linkages between host species
diversity and composition, and parasite or microbe
species diversity and composition within communities on the one hand, and the risk of altering any
(host) species and composition on host invasiveness,
host defences and increase of virulence by parasites
or pathogens on the other hand. We are definitely
advocating here a community ecology perspective
for host–parasite systems.
CHAPTER 3
Parasitism and the regulation of
host populations
Anders Pape Møller
Parasites can regulate hosts when parasites affect density-dependent
mortality or fecundity, particularly among early life stages. Evidence
consistent with parasite regulation of host populations include experiments
that manipulated parasites; analyses of area–abundance relationships
showing that host populations strongly affected by parasites are relatively
small; and analyses of introductions of hosts to novel environments where
they are released from parasite regulation.
3.1 Introduction
Factors that determine the size of populations of
animals and plants have been studied for over two
centuries. Understanding such factors is important
because of applied aspects of ecology such as harvesting and conservation, but also for purely scientific reasons. Population regulation depends on
density-dependence since only reduced fecundity
or survival under high densities can regulate
populations. Only biotic agents such as conspecifics,
predators, or parasites can play this role. Densitydependent regulation is more likely during earlier
stages of the life cycle because density-dependence
at later life stages occurs ‘too late’ to allow regulation. Our knowledge of population regulation is
still relatively poor despite more than a century of
research (see reviews in Begon et al. 1996; Newton
1998). This opens up the possibility that even major
factors contributing to population regulation may
have been neglected. Parasites may be an example
of such a neglected factor.
I will start this chapter by reviewing studies that
show that parasites locally at least can regulate host
populations. This aspect is important because such
Laboratoire de Parasitologie Evolutive, CNRS UMR 7103,
Université Pierre et Marie Curie, Bât. A, 7ème étage, 7 quai
St. Bernard, Case 237, F-75252 Paris Cedex 05, France.
cases are the basis for any potential of population
regulation at larger scales. Second, I will review the
literature on population introductions, parasitism,
and success of introduction. Introduced species in
novel environments provide examples of some of
the most dramatic examples of population growth,
the reverse of strict population regulation. A careful
study of such examples might therefore provide
important insight into mechanisms that could be of
importance for population regulation. Third, I will
investigate the possibility that indices of parasite
impact on hosts, such as host investment in
immune function, may predict population size of
hosts. I do that by investigating the literature on
abundance–area relationships and how that relates
to parasitism. Finally, I briefly describe parasitemediated competition and predation and how
these mechanisms may play an important role in
population regulation of hosts.
3.2 Parasites and density-dependent
effects on host fecundity and survival
Like most natural enemies, parasites are quite capable of regulating their host population when they
reduce the fecundity or the survival of their host
population in a density dependent fashion. The fundamental understanding of how macro-parasites
43
44
PA R A S I T I S M A N D E C O S YS T E M S
can regulate their host population arises from a
series of papers by Anderson and May (Anderson
and May 1978; May and Anderson 1978) that have
since been reviewed by Tompkins et al. (2001). In
these models, Anderson and May not only identified the conditions when parasites would be capable of regulating their host population but also the
processes that could destabilize or stabilize the
host–parasite relationship. In essence regulation
will occur when the growth rate of the parasite
exceeds that of the host population assuming that
the parasite has a harmful affect on the survival or
fecundity of the host population so the growth rate
of the host population is reduced through the parasite induced effects. In essence the parasites ‘outstrip’ the host population such that when the host
population size gets high the parasites reduce it
and when the host population is low, so levels of
parasite infection tend to be low allowing the levels
of infection to rise. Demonstrating that regulation
by parasites occurs in free-ranging wildlife is not so
easy, particularly when the host population is at
equilibrium and requires careful, large-scale
experimental treatment in which levels of parasite
infection are either reduced or host numbers
increased. In this section I review the features of the
Anderson and May model and some of its assumptions and then examine some experimental data
that test the hypothesis that parasites can play an
important role in regulating host populations.
The basic Anderson and May model for macroparasites is based on two linked differential equations that describe changes in the size of the host
and the parasite population, respectively. The
model encompasses two important elements. First
and foremost it captures the aggregated distribution of the parasites within the host population by
assuming the parasites distribution conforms to the
negative binomial distribution and uses the inverse
estimate of aggregation described by the aggregation parameter, k. When k is low, aggregation is
high but when k is above 5, the distribution
approaches a random distribution as described by a
Poisson distribution. By far and away the majority
of macro-parasites exhibit an aggregated distribution; Shaw and Dobson (1995) examined 269 data
sets of parasite distribution within wild animal
species and found a tight relationship between
log-variance and log-mean that followed Taylor’s
power law with the variance rising faster than the
mean, indicating an aggregated distribution (e.g.
Fig. 3.1). The second feature is that the model
incorporates both the effects that the parasites have
on the survival of the host and on their ability to
produce young. Macro-parasites tend to generate
morbidity rather than mortality in the host, reducing
the condition and the ability of the host to search
for resources, defend a good territory or provide
food for their offspring so heavily infected individuals tend to have lower reproductive success
and increased vulnerability to secondary causes
of mortality such as predation or secondary
infections.
The Anderson and May model demonstrates that
it is the parasites of moderate virulence that will
regulate a host population and not those of high virulence. Those parasites that are effectively benign have
no impact on the growth rate of the host population
so naturally they are unlikely to control the host
growth rate while those of high virulence tend to
cause mortality in the host before the parasites have
had time to infect many other hosts, and thus the host
tends to escape the regulating role of the parasite. The
regulation is more likely when the parasites have a
random distribution as opposed to an aggregated
distribution. When the parasites are highly aggregated, most of the parasites are concentrated in a small
proportion of the host population and since they
influence just a small proportion of the host population, the host can escape the regulatory role. There
will in fact be a threshold of aggregation, above
which the host escapes regulation by the parasite but
below which the parasite can still regulate.
Aggregation will tend to stabilize the host–parasite
dynamics, but as the distribution becomes more
random, the population will become increasingly
unstable. Two other features will tend to stabilize
the parasite–host relationship: density-dependent
constraints on parasite growth rate such as
acquired immunity or competition for space or
resources within the host and nonlinear increases in
parasite-induced host mortality.
The features of the parasite–host system that will
tend to destabilize the dynamics include a random
R E G U L AT I O N O F H O S T P O P U L AT I O N S
(a)
(c)
45
90
Frequency
Frequency
200
150
100
60
30
50
0
0
0
1
2
3
4
0
5
Number of parasites/host
(b)
(d)
Frequency
Frequency
800
600
400
1
2
3
4
5
6
7
Number of parasites/host
600
450
300
150
200
0
0
0
50 100 150 200 275-541
Number of parasites/host
0
2
4
6
8 10-100
Number of parasites/host
Figure 3.1 Examples of aggregated distributions of parasites within their host population. The bars represent observed frequencies and the points
the fit of the negative binomial distribution for (a) perch Perca fluviatilis infected with the parasitic tapeworm Triaenophorus nodulosus,
(b) reindeer Rangifer tarandus infected with the warble fly Hypoderma tarandi, (c) starling Sturnus vulgaris infected with the nematode Porrocaecum
vulgaris, and (d) the pond frog with the nematode Spiroxys japonica.
Note: More details can be found in Shaw et al. (1998).
Source: After Shaw et al. (1998).
distribution of parasites within the host population,
time delays in the development of the parasite,
direct parasite multiplication within the host, and
relatively high impact of parasites on fecundity
compared with the impact of the parasites on survival. Time delays in parasite development are an
integral part of most parasite systems, since the
parasites usually leave the host in an egg form and
then there is either a period of further development
through several stages, or at least a time period
where the infective stage is lying dormant outside the
host or even a period of diapause within the host
(known as arrested development). Parasite induced
reduction in fecundity is likely to be prevalent in
parasite–host systems in wild animal populations
and has been recorded in a number of parasite–host
systems. An experimental approach to this with red
grouse Lagopus lagopus scoticus found that grouse
with experimentally reduced levels of infection had
greater clutches, higher hatching success, and chick
survival than controls, but the important effect is to
note that this was not because chicks were being
infected but because these effects were operating
through the condition of the female (Hudson 1986a;
Hudson et al. 1992b). A common misunderstanding
of the Anderson and May model is that the
oscillations in abundance are caused by a delayed
density dependent feedback, this feedback is to
some implicit within the system, but there again the
tendency to cycle is an emergent property and
usually a consequence of the parasite induced effect
on host fecundity.
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PA R A S I T I S M A N D E C O S YS T E M S
3.2.1 Regulation and laboratory studies
While a number of studies have provided evidence
that parasites can reduce host fecundity and/or
survival (Tompkins et al. 2001: table 3.1), few studies have provided sufficient evidence to suppose
that these effects are acting in a density-dependent
manner and are capable of leading to regulation.
One of the problems is to show that the effects of
the parasites on host fitness are acting in an additive or compensatory manner. To demonstrate
regulation we need to perturbate the system experimentally by changing the host–parasite relationship and predicting the outcome (Scott and
Dobson 1989). This is not that simple, since we need
both the right scale, replication, and importantly
ensure that the mechanism is truly altered at the
right scale and in the correct manner (Hudson and
Bjørnstad 2003).
Marilyn Scott undertook two free-running laboratory studies and provided evidence to suppose
that parasites were capable of regulating host
populations. In the first (Scott and Anderson 1984)
she investigated the effects of the monogenean
Gyrodactylus bullaturdus on guppies Poecilia reticulata in fish tanks. They showed that parasites had a
dramatic effect on reducing host abundance and
reduced abundance below the level it would have
been without infection although after about 95 days
the parasite went extinct. In another free-running
experiment Scott (1987) introduced the nematode
Heligmosomoides polygyrus into large mouse enclosures and showed that with a wet peaty substrate
(that encourages transmission) the parasite regulated the host population for a period of 16 weeks
after which anthelmintic treatment resulted in an
increase in the population.
3.2.2 Regulation and a case study: red grouse
and Trichostrongylus tenuis
Dobson and Hudson (1992) explored the dynamics
of the red grouse–T. tenuis system by extending the
basic Anderson and May model and incorporating
a third equation to describe changes in the size of
the free-living stages. They also included terms to
evaluate the effects of time delays introduced
through arrested development. Simulations from
the model show that the degree of aggregation and
the time delays in parasite development identified
through arrested development are not the main
cause of the population oscillations in red grouse.
Cyclic oscillations in the model occurred when the
ratio of parasite induced reduction in host fecundity to parasite induced reduction in host survival
was greater than the degree of parasite aggregation
within the host population. In other words, the
impact on fecundity is the feature that destabilizes
the host population and is the principal cause of
oscillation.
The findings from detailed field studies and
experiments (Hudson 1992; Hudson et al. 1992b)
coupled with the model do not show that the parasites were the actual cause of the observed cyclic
fluctuations. To determine if the parasites do indeed
impact the dynamics of their host required a largescale population experiment that manipulated
parasite burdens and predicted the subsequent
dynamics (Hudson et al. 1998). The model provides
the means by which these predictions can be made.
By incorporating terms that describe how worm
mortality is affected by anthelmintic treatment they
predicted the proportion of grouse that must be
treated to have a significant impact on the population
and the timing of this application. Treatment of just a
small proportion of the population just at the peak
grouse density would have an impact on the
dynamics of the host population but worm eradication would require almost total treatment of the
whole population.
Six study areas were used for the experiment.
The first predicted crash was 1989 and in the winter
before the crash, large numbers of grouse were
caught at night on four of the six populations and
treated orally with an anthelmintic to reduce
intensities of worm infection. The remaining two
were left untreated as control areas. On three of the
treated populations about 20% of the population
were caught, treated, and tagged although on the
remaining one about 15% were treated. A second
population crash was predicted in 1993 and in this
year two of the areas treated in 1989 were treated
again while two of those treated in 1989 were left
as controls to provide comparisons within and
R E G U L AT I O N O F H O S T P O P U L AT I O N S
between estates. The treatment of grouse reduced
the variance of the bag records and in effect reduced
the extent of the population crash following treatment in all the years and sites where treatment was
applied (Fig. 3.2). Note that all treated sites showed
some level of decline as predicted from the model
and one site exhibited a decline that was similar to
the extent of a decline when no treatment was
applied, this was the site where just 15% of the population was treated. Nevertheless, the conclusion is
clear, the removal of parasites reduced the amplitude of the oscillations in agreement with the model
predictions implying that in these sites at these
(a) 10,000
1000
100
10
47
times the parasites were necessary for the cycles
observed. This statement does not refute the
possibility that other factors may influence the
dynamics of the grouse at other sites or at other
times (e.g. Mougeot et al. 2003), simply because
when we consider all the long-term monitoring and
experimental data together it seems clear that
parasites play an important role in the regulation of
red grouse. Lambin et al. (1999) suggested that the
use of bag records rather than traditional population density estimates may have affected the conclusions. However, Hudson et al. (1999) suggested
that this was unlikely for the population densities
considered.
In summary, it is clear that parasites are quite
capable of regulating populations. Demonstrating
this in free-ranging wild animal populations is not
so simple and it is interesting to note that the clearest case comes from an unstable host population.
The models indicate that parasite–host relations are
intrinsically unstable so maybe this is an area where
studies of host–parasite dynamics should focus.
1
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
(b) 10,000
1000
100
10
1
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
(c) 10,000
1000
100
10
1
1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997
Figure 3.2 Population changes in red grouse, as presented through
bag records, in (a) the two control plots, (b) the two plots with a
single anthelminthic treatment, and (c) the two plots with two
anthelminthic treatments.
Note: Further details can be found in Hudson et al. (1998).
3.3 Population introductions, parasitism,
and success of introduction
Population introductions now constitute model systems that are used to study colonisations, the fate of
small populations and conservation. Introductions
of hosts into novel environments are interesting
because they provide large-scale natural experiments that are replicated at a sufficient level to
assess the ecological and evolutionary determinants
of success. Successful colonizations also comprise
some of the most dramatic population increases
known, with the populations of several birds and
mammals reaching hundreds of millions of individuals in their novel environments. Three studies of
parasites are relevant for the problem of population
regulation of hosts by parasites. First, Mitchell and
Power (2003) and Torchin et al. (2003) investigated
success of colonizations of a range of different
organisms in relation to reduction in parasites in the
newly colonized environment (see also Chapter 7).
The parasites that were left behind were an important predictor of successful colonization (Mitchell
and Power 2003; Torchin et al. 2003). Second, an
48
PA R A S I T I S M A N D E C O S YS T E M S
analysis of introduction success of birds released in
novel environments revealed a difference in T-cell
mediated immune response between successful and
unsuccessful colonizers (Møller and Cassey 2004). I
will briefly review these studies and address their
importance for determining the importance of
parasites for population regulation of hosts.
First, Mitchell and Power (2003) and Torchin et al.
(2003) investigated success of colonisations of a
range of different organisms in relation to reduction
in the parasite fauna in the newly colonized environment. The parasites that were left behind were an
important predictor of successful colonization in
plants (Mitchell and Power 2003) and animals
(Torchin et al. 2003). Introduced populations of animal hosts on average had more than 40% fewer
species of parasites than the native populations,
and the average prevalence was also more than
40% reduced (Torchin et al. 2003). The parasites that
were left behind were those that were less prevalent, perhaps because such species are less likely to
be present in a small sample of hosts. In addition,
less prevalent parasites are more likely to be more
virulent since virulent parasites by definition have
a higher probability of killing their hosts, thereby
reducing their prevalence in the host population.
However, prevalence of parasites that did invade
the novel environment with their host had as large
prevalence as in the native environment, and native
parasites that subsequently invaded introduced
host populations had as large prevalences as those
that were introduced with the invading host
(Torchin et al. 2003).
Second, an analysis of introduction success of
birds released in novel environments, mainly New
Zealand, revealed a difference in T-cell mediated
immune response between successful and unsuccessful colonizers (Møller and Cassey 2004).
Deliberate human introductions of birds to novel
environments were a passion for many immigrants
of European origin in the eighteenth and nineteenth
centuries. The number of introductions, the number of individuals introduced, and the outcome of
many of these introductions has been meticulously
documented, allowing statistical analysis of factors
that potentially contribute to colonization.
Introductions of birds to New Zealand and other
islands have been particularly well documented,
and a number of key features of successful introductions such as number of introductions, number
of individuals, habitat generalism, and sexual
dichromatism have been identified as significant
predictors of success (Cassey 2002). Møller and
Cassey (2004) suggested that the stressful conditions
associated with introductions would render individuals that suffered from chronic parasitic infections less likely to survive than less infected
individuals. Therefore, individuals of species with
strong immune responses would have a reduced
likelihood of succeeding because bird species with
stronger nestling mortality directly caused by
parasites have stronger T-cell mediated immune
response (Martin et al. 2001). In addition, bird species
with stronger T-cell mediated immune response
have higher prevalence and/or more specialized
parasites than species with weak responses (fleas:
Møller et al. in press; chewing lice: Møller and
Rozsa in press; blood parasites including
Plasmodium: Møller et al. unpublished data). Møller
et al. (2004a) have shown for European passerines
that species with strong T-cell responses have
longer natal dispersal distances than species with
weak responses, even when controlling statistically
for potentially confounding variables. Therefore,
individuals with strong immune responses are
better able to disperse long distances successfully,
giving rise to the prediction that successful colonisers
should have stronger immune responses.
A comparative analysis of species of birds introduced to New Zealand, and for which information
was available on T-cell mediated immune
response, revealed that successful colonisers had
stronger T-cell responses after controlling for other
factors associated with introduction success
(Fig. 3.3). This finding clearly refutes the first prediction. However, the effect of T-cell response on
success depended on the size of the inoculum, with
the effect only being significant for large releases.
Introductions usually failed immediately after
release before the birds had a chance to reproduce,
making it unlikely that inbreeding played a role
in success. Since introduced populations typically
are derived from small subsets of native populations, they generally have fewer species and
R E G U L AT I O N O F H O S T P O P U L AT I O N S
Coefficient for T-cell response
15
10
5
0
< 10
11–100
Propagule size
> 100
Figure 3.3 Introduction success of birds to New Zealand and other
islands in relation to T-cell mediated immunity among nestlings. The
values are partial regression coefficients (± SE) after controlling for
habitat generalism, other potentially confounding variables and
phylogenetic relationships among taxa.
Source: Adapted from Møller and Cassey (2004).
lower prevalences of parasites than the ancestral
population, as described by Torchin et al. (2003) and
Mitchell and Power (2003). A strong immune
response would not be important in such a situation. In contrast, large introductions with more than
100 individuals are much more likely to harbour a
diverse and abundant parasite fauna, where a
strong immune response might play a key role
between life and death.
Which are the interpretations of these findings of
introductions, parasitism, and immunity? I suggest
that at least four not necessarily mutually exclusive
explanations are possible. (1) The results could be
an effect of parasite absence from the inoculum of
introduced hosts; (2) the findings could be an effect
of host physiology during stressful introductions,
which only secondarily is associated with parasitism; (3) the results could arise as an effect of the
local host and parasite community in the novel
environment; and (4) many parasites have complex
life cycles that depend on more than one species of
host. I will discuss each of these explanations in
detail.
First, missing parasites from introduced
populations may arise as a consequence of such
49
populations often representing a small subset of the
native population. Both Torchin et al. (2003) and
Mitchell and Power (2003) found that diversity and
prevalence of parasites among introduced species
were dramatically reduced compared to the native
populations. While this may make a difference in
terms of probability of successful colonisation, this
conclusion rests upon the untested assumption that
the introduced population is a random sample
derived from the native population. Small populations are by definition likely to suffer from strong
sampling bias giving rise to demographic stochasticity that could affect host–parasites interactions as
well. This is most likely the case for bird species introduced to New Zealand (Legendre et al. 1999). Drake
(2003) has shown in a simple model that the relationship between the number of individuals introduced
and the probability of establishment depends upon
the relationship between virulence and the fraction of
the population infected at introduction. The finding
that T-cell mediated immune response did not predict introduction success for small inocula, but did so
for large inocula (Cassey and Møller 2004; Fig. 3.3) is
in agreement with this suggestion.
Second, the ability of hosts to cope with parasites
depends strongly upon their current physiological
state. Stressful conditions may especially provide an
impediment to efficient host defences. The birds
that were introduced to New Zealand and other
islands went through extraordinary ordeals before
reaching their final destination for release. First,
they were captured in the United Kingdom and
placed in cages that subsequently were transported
to the harbour for shipment. The sea voyage took
several months, often under very different weather
conditions than commonly experienced by the
species in question. These conditions must have
resulted in strong physiological stress responses
including a strong corticosterone response and
induction of heat-shock proteins. Corticosterone is
notorious for depressing immunity including T-cell
mediated immunity (von Holst 1999), giving the
parasites an upper hand during this long-lasting
part of the introduction process. Such responses will
only be important in vertebrates with a corticosterone-based stress physiology, although other
mechanisms such as induction of stress proteins
50
PA R A S I T I S M A N D E C O S YS T E M S
occur across almost all organisms. It seems very
likely that natural selection will have played an
important role in shaping the phenotype of the individuals that eventually arrived in New Zealand and
other islands, since particularly individuals that
were able to cope with the stressful conditions by
not developing strong stress responses should be
able to succeed. An important parallel situation
similar to that experienced during introductions can
be seen in the process of domestication (Kohane and
Parsons 1988). Individuals with weak stress
responses are strongly favoured by initial selection,
and such individuals are characterized by low levels
of testosterone, low levels of aggression, and a lifehistory characteristic of r-selected strategies. Since
domestication can result in dramatic micro-evolutionary changes in just a few generations (see examples in Kohane and Parsons 1988), it seems likely
that introductions might likewise have resulted in
intense natural selection and changes in genetic
composition in just a single or a few generations.
Third, the local host and parasite community in
the novel environment may differ dramatically
from those of the native environment. Parasites are
often disproportionately common on islands
(review in Hochberg and Møller 2001). Models of
the coevolution of parasite virulence and host
resistance on islands have shown that costly host
resistance genes tend to be lost from populations
inhabiting oceanic islands (Hochberg and Møller
2001). As a consequence, island populations are
very susceptible to introduced parasites from
continents that tend to be more virulent than their
island counterparts (Hochberg and Møller 2001).
These theoretical arguments would suggest that
species of birds introduced to oceanic islands in
general would run low risks of parasite-induced
mortality due to local island populations of parasites.
If anything, the absence of virulent parasites on
islands should provide introduced species with a
considerable fitness advantage. The local parasite
community in the area of introduction will often
differ considerably from that of the native populations. Since horizontal transfer of parasites is
more common among sister taxa than among more
distantly related taxa, introduced hosts would
encounter relatively few novel parasites due to the
absence of congeners or even other species belonging
to the same family, as was the case for introductions
of house sparrows Passer domesticus and starlings
Sturnus vulgaris to the Americas.
Fourth, many parasite species have complex life
cycles that depend on more than a single species of
host. Each of these intermediate hosts and the final
host must be present to allow the parasite to complete its entire life cycle. If this mechanism was
important, we should expect parasites with complex life cycles to be less common among introduced as compared to native populations. Torchin
et al. (2003) did not test this prediction.
While these preliminary studies of introduced
species, successful colonization, and missing parasites may appear to be clear-cut, there is clearly
scope for much more work to be done before the
exact mechanisms that led to this situation can be
resolved.
3.4 Abundance–area relationships and
parasitism
Abundance–area relationships constitute one of the
most robust findings in ecology, with locally
abundant species being widely distributed, while
those with low local densities tend to have
restricted distributions (Gaston 1994; Brown 1995).
While this ‘law’ seems to be general, accounting for
20–30% of the variance across related species
(Gaston 1996), the factors contributing to this relationship remain largely unknown. For example,
Gaston and Blackburn (2003) failed to find general
support for the hypothesis that greater dispersal
propensity among birds could account for some of
the variance in abundance–occupancy relationships.
If parasites are able to reduce the abundance of
hosts compared to the level of abundance expected
in the absence of virulent parasites, we should
expect that indices of parasite impact on hosts would
be able to partly explain some of the variance in the
abundance–occupancy relationship. In particular,
given that population regulation is more likely to be
due to density-dependent effects at early rather than
late life stages, we can make the prediction that
estimates of the impact of parasites on hosts during
early life stages should be better predictors of
R E G U L AT I O N O F H O S T P O P U L AT I O N S
2
Residual population size
abundance after controlling for occupancy than
estimates of parasite impact during later life stages.
Recently, Møller et al. (2004c) tested this prediction
using a measure of T-cell mediated immune
response to a challenge with a novel mitogen as an
estimate of parasite impact on hosts. This assumption is supported by the fact that bird species with
stronger nestling mortality directly caused by parasites have stronger T-cell mediated immune
response (Martin et al. 2001). In addition, bird species
with stronger T-cell mediated immune response
have higher prevalence and/or more specialized
parasites than species with weak responses (fleas:
Møller et al. in press; chewing lice: Møller and Rozsa
in press; blood parasites including Plasmodium:
Møller et al. unpublished data). Thus, there is empirical evidence supporting the assumption that species
with stronger T-cell mediated immune response
indeed suffer from greater mortality due to parasitism, and that such species are exploited by more
specialized and virulent parasites.
In a comparative analysis of 73 European bird
species for which information on continental population size, occupancy, and T-cell mediated immune
response was available, Møller et al. (2004c) found
the commonly reported positive association
between abundance and occupancy, accounting for
more than 30% of the variance. In a stepwise regression analysis T-cell mediated immune response of
nestlings was a significant predictor of abundance
with a negative impact as expected (Fig. 3.4). The
relationship accounted for 12% of the variance, suggesting that parasites can have dramatic impact on
host population size on a continental scale. In contrast, there was no significant relationship due to
T-cell mediated immunity in adult birds. Likewise,
a number of potentially confounding variables that
has been found to be related to T-cell mediated
immunity (e.g. hole nesting (Møller and Erritzøe
1996) and coloniality (Møller et al. 2001)) did not
account for the relationship between abundance
and immunity in nestlings.
These findings are suggestive and certainly raise
a number of questions about future studies of
abundance–occupancy relationships in general and
about the impact of parasites on population size of
hosts in particular.
51
1
0
–1
–2
0.0
0.5
1.0
1.5
2.0
2.5
3.0
T-cell response (mm)
Figure 3.4 Relative population size of European passerine birds in
relation to T-cell mediated immune response (mm) of nestlings.
Population size was estimated as the residuals from a regression of
log (population size) on log (distribution area).
Source: Adapted from Møller et al. (2004c).
3.5 Parasite-mediated competition and
predation
There is clear evidence of intraspecific competition
causing population regulation (e.g. Begon et al. 1996;
Newton 1998). Likewise, there is clear evidence consistent with the suggestion that predators regulate
prey populations (e.g. Newton 1998; Murdoch et al.
2003). Most population ecologists are happy to
accept the notion that predators can regulate prey
populations (e.g. Hudson and Bjørnstad 2003;
Murdoch et al. 2003). This is fair judgment based on
available evidence. However, we do not know what
was the case of successful predation in the first
place. Therefore, a more appropriate conclusion
would be that predation, or any factor associated
with successful predation, has been shown to result
in population regulation. This distinction is crucial
since most studies are only based on correlations,
thereby preventing firm conclusions about exact
cause and effect. What is must less appreciated is
that these effects of competition and predation may
be parasite-mediated, thereby changing the important role of population regulation from conspecifics
and predators to parasites. There is firm empirical
and experimental evidence showing that both
52
PA R A S I T I S M A N D E C O S YS T E M S
intraspecific competition and predation can be parasite mediated. Begon et al. (1996) review several
studies showing that parasites can play an important
role in intraspecific competition.
A few studies have investigated how parasites
may mediate which host individuals are killed by
predators and which survive. In a now classical
study Temple (1986) used a tame red-tailed hawk
Buteo jamaicensis to collect a sample of chipmunk
Tamias striatus, cottontail rabbit Sylvilagus floridanus,
and grey squirrel Sciurus carolinensis prey and compared the health status of such individuals with a
random sample that he simultaneously collected
with a gun. There was a dramatic difference in
intensity and prevalence of parasitism of these two
categories of potential mammalian prey, with mammals killed by the predator suffering significantly
more from parasitism by trematodes, nematodes,
and ectoparasites (Temple 1986). In a second study
Møller and Erritzøe (2000) investigated 535 individuals of 18 species of common passerine birds that
had either been killed by domestic cats Felis catus or
died accidentally by crashing with a window. All
individuals were sexed and aged and a large number of characters were recorded for each specimen,
including the size of the spleen. Bird species with
larger spleens suffer more from parasite-induced
mortality (Møller and Erritzøe 2002, 2003), and prey
to cats were therefore expected to have smaller
spleens than non-prey reflecting their poor ability to
defend themselves against parasites. Prey had consistently smaller spleens than non-prey in a paired
comparison across the 18 species, implying that they
had weak immune systems. The data set did not
indicate that sex or age, month of death, body mass,
body condition, liver mass, wing length, or tarsus
length differed significantly between prey and nonprey. These studies suggest that parasites can play
an important role in determining which individuals
are eaten and which survive.
The mechanisms behind differential predation on
heavily parasitized hosts could simply be that
such individuals are weakened and therefore easier
to catch. Alternatively, predators may interact
directly with the immune system of the host, thereby
increasing the probability of prey being heavily
parasitized (Møller et al. 2004b). Predation risk
may affect the allocation priorities of limiting
resources by potential prey, reducing investment in
immune function when hosts are exposed to predators because of the costs of immune function. Møller
et al. (2004b) tested this hypothesis by randomly
exposing adult house sparrows to either a cat or a
rabbit Oryctolagus cuniculus for six hours while
assessing their ability to raise a T-cell mediated
immune response. Sparrows exposed to a cat had a
significant reduction of on average 18% and 36%,
respectively, in T-cell response in two different
experiments, as compared to sparrows that were
exposed to a rabbit. In a field experiment in which
sparrows were exposed to a barn owl Tyto alba or a
rock dove Columba livia placed next to a nest box
during laying Møller et al. (2004b) found a mean
reduction in T-cell mediated immune response of
20%. In a third experiment conducted during
spring, when blood parasite infections relapse,
house sparrows were either exposed to a barn owl
or a rock dove, while development of malarial
infections was recorded during the subsequent
6 weeks. Individual sparrows exposed to a predator
had a significantly higher prevalence and intensity
of Haemoproteus malarial infection than control
individuals. Therefore, exposure to predators
reduced that ability of hosts to cope with parasitism
mediated through effects on immune function. This
was the case in aviaries and under field conditions.
In conclusion, predators may have direct effects on
the ability of hosts to defend themselves against
parasites. This is likely to increase the mortality rate
since house sparrows infected with Haemoproteus
are more likely to die than uninfected individuals
(González et al. 1999). Reductions in immune
defence will also result in increased levels of
parasitism that subsequently will affect risk
of predation. The importance of this mechanism
will increase with the density of predators, but
potentially also with the density of prey, if
availability of shelter from predators is limiting.
As these few examples suggest, parasites may
play a much more indirect role in predator–prey
interactions than previously thought. Such mechanisms must be taken into account when evaluating studies of population regulation of hosts by
predators.
R E G U L AT I O N O F H O S T P O P U L AT I O N S
3.6 Concluding remarks
This chapter has provided one important insight
that was clear at the outset: we have a very incomplete knowledge of population regulation of hosts
by parasites. This may stem from the fact that a
large part of parasitology and immunology is
restricted to the laboratory. Another reason is that
most population ecologists are not interested in
parasites, perhaps stemming from the influence of
David Lack who wrote that ‘While further evidence
is needed, it seems unlikely that disease is an
important factor regulating the numbers of most
wild birds’ (Lack 1954: p. 169). This clearly has to
change and there are signs that parasitism finally
has started to claim its rightful position in population ecology. Here, I suggest four areas for which
more research is needed.
First, more long-term field studies of hosts and
parasites. Studies of population regulation have traditionally been based on long-term studies such as
those on mammals in Canada, rodents in many
parts of the northern hemisphere and hole nesting
birds in Europe. Almost all of these ongoing studies
have completely neglected the role of parasites. This
clearly has to change if we want to understand if
53
parasites play a role in many population ecology
processes.
Second, more large-scale field experiments. I am
aware of very few large-scale field experiments that
have manipulated the level of parasitism and
subsequently investigated the consequences for
host populations. Clearly, many more such studies
are needed.
Third, we need more comparative studies of
population regulation. We may be able to gain
insights into the role of parasites in population
regulation of hosts by studying the explanatory
power of estimates of parasite impact on hosts as
predictors of host population sizes.
Finally, we need more studies of mechanisms. As
emphasized above, we need to include parasitism in
studies of predator regulation of prey populations
to be able to partition the variance into predator and
parasite components. We also need to know much
more about the effects of parasites as mediators of
competition and predation under field conditions.
Finally, we need to know more about the microevolutionary changes that have happened during
introductions. I believe that such efforts will provide
a much better basis for judging the role of parasites
in population regulations of their hosts.
CHAPTER 4
Food web patterns and the parasite’s
perspective
Michael V. K. Sukhdeo and Alexander D. Hernandez
The way that parasites fit into food webs remains unclear. We argue that
coherent energetic patterns (biomass pyramids) occur in food webs that
include parasites. These patterns typically evolve in stable associations when
considered from the perspective of the parasite, and empirical evidence is
provided of biomass patterns in a natural fresh water food web.
4.1 Introduction
It is clear that parasites are capable of exerting major
effects on ecological interactions, and this is well
documented in the growing mountain of theoretical
and empirical evidence, much of it summarized
within the pages of this very book. Yet, it is remarkable that several fundamental questions about the
ecology of parasites still remain unanswered. For
example, how do parasites fit into food web
patterns?
This is a complex question at many levels, and it
has been the subject of much debate since the 1920s.
There have been several studies that have
attempted to incorporate parasites into food web
patterns (e.g. Elton 1927; Campbell et al. 1980;
Goldwasser and Roughgarden 1993; Huxham et al.
1995, 1996; Leaper and Huxham 2002). However,
few have provided verbal or theoretical models for
thinking about how parasites might fit in food
webs in the same way we visualize how predators
or prey fit into food web patterns. Some of our best
understanding of parasites in food web dynamics
come from studies on the food web in the Ythan
estuary, one of the largest and most completely
documented food webs available, comprising 134
taxa of which 42 are metazoan parasites (Hall and
Raffaelli 1991; Huxham et al. 1995; Leaper and
Department of Ecology, Evolution and Natural Resources, Rutgers
University, Cook College, New Brunswick, NJ 08901.
Raffaelli 1999). Depending on whether parasites are
included or excluded in the food web analysis, or
whether they are included as biological species versus tropho species, there are significant changes in
several food webs statistics including food chain
length, omnivory, and connectance (Huxham et al.
1995; Leaper and Huxham 2002). However, no
easy-to-recognize general pattern has emerged
from these analyses. Indeed, the absence of a clear
model of how parasites might fit into food webs is
a hindrance for many ecologists working with
parasites. Thus, although the dramatic effects of
parasites on host behaviour and host population
dynamics have been reported from numerous taxa
almost invariably, the consequences of these effects
on community processes are usually left to inference and speculation (Dobson and Hudson 1986;
Minchella and Scott 1991; Marcogliese and Cone
1997; Poulin 1999; Moore 2002; Mouritsen and
Poulin 2002, but see Chapter 8). The reasonable
assumption by most investigators is that population
effects will ultimately translate into system level
effects.
In this chapter, we will briefly summarize some
of the history of food webs and the debate about
parasites. If one takes the view that the study of
food webs is the study of energy flow through a
community and the search for general patterns
(Lindeman 1942; Odum 1953; Hairston and
Hairston 1993; Winemiller and Polis 1996; Morin
54
F O O D W E B PAT T E R N S
1999), then it follows that before parasites can be
considered legitimate actors in the food web
drama, they must first be integrated into a general
pattern of energy flow in the community. We will
argue that coherent patterns may occur in evolutionary stable associations when viewed from the
parasite’s perspective, and we present some empirical evidence for a biomass pattern in a natural food
chain.
4.2 A brief history of food webs and
parasites
The food web literature is enormous and continues
to grow exponentially, and it would be a formidable
task to summarize all of the complex theoretical
and experimental directions in modern food web
studies. However, for the readers not familiar with
this literature, an abbreviated history of the field
might elucidate some of the principles and major
perspectives that have guided progress in the field.
In 1927, Charles Elton was only 26 years old when
he wrote Animal Ecology, which went on to become
one of the most influential books in the field. Here he
introduced the concept of food cycles (now food
chains and food webs), and he argued that they provided the conceptual framework to understand
species interactions in the context of complex ecosystems. Although other workers had used food cycle
diagrams as an aid in the understanding of ecological
systems, Elton’s genius was in recognizing that food
cycles play a central organizing role in ecology. One
of his major insights on organisms was that ‘food is
the factor that plays the biggest parts in their lives,
and it forms the connecting link between members
of the community’ (Elton 1927). Thus, food was the
common currency of communities, and significantly,
distinct patterns emerged from the feeding relationships in natural communities. He is most famous for
‘Eltonian pyramids’, which argue that food cycles
tended to be organized as a pyramid of numbers,
where organisms at the bottom of the food chain
tend to be very abundant, while predators on top
are relatively few in numbers. Elton is now widely
considered the father of community ecology, and
his book helped formulate many of the basic
questions that are still considered important by
55
ecologists today; the roles of competition, niche
space, temporal and spatial heterogeneity, ecological
succession, indirect effects, and body size on structuring communities, and the crucial importance of
feedback between organisms and their environments (Elton 1927). His synthetic view of community
interactions has continued to be a dominant paradigm in food web studies, and many of the basic
lessons that Elton helped develop, like the importance of natural history and the use of multiple lines
of inquiry, still resonate with ecologists.
Elton’s most enduring gift to food web studies
was the abstraction of complex community interactions in nature into simple patterns that were accessible to all. Eltonian pyramids provided a template
for thinking about community structure both theoretically and empirically, and led to an explosion of
food web studies. However, Elton was not always
completely right. The pyramid of numbers,
based on the relative size of food items, missed an
important component of modern thinking, that is,
the trophic inefficiency of energy transfer.
Subsequently, Lindeman (1942) combined Elton’s
concepts with an energetic perspective from Lotka
(1925), shifting the focus to pyramids of biomass
rather than pyramids of numbers because biomass/productivity patterns better captured the
dynamics of energy flow through the community.
Lindeman’s values of trophic efficiencies of ⬃5–15%
are still widely accepted as an informal rule among
ecologists (see Fig. 4.1). Odum (1953) further refined
Lindeman’s ideas (in a few marine communities
biomass pyramids may overemphasize the
importance of large organisms), and suggested that
energy flow, that is, Productivity ⫹ Respiration, was
the appropriate index for comparing any and all
components of an ecosystem and across ecosystems. Thus, energy became the accepted currency
of all community interactions, and this elementary
perspective on the nature of food webs has
remained unchanged for more than 50 years. The
analysis of energy and material flow is still considered to be fundamental to understanding the patterns and dynamics in ecosystems and the way
ecosystems are organized (DeAngelis 1992;
DeRuiter et al. 1995). For most food chains, trophic
biomass (standing crop) patterns are good
56
PA R A S I T I S M A N D E C O S YS T E M S
(a)
Lake Mendota
3° consumers
2° consumers
1° consumers
producers
0
50
100
(b)
150
200
250
300
350
400
450
500
Cedar Bog Lake
2° consumers
Figure 4.1 Biomass/productivity
pyramids for the (a) Lake Mendota and
(b) Cedar Bog Lake food webs.
1° consumers
Notes: Producers here are defined as
macrophytic pondweed and microphytic
phytoplankton, while primary consumers are
the herbivores, or ‘browsers’, in aquatic
ecosystems. Secondary and tertiary
consumers are benthic and swimming
predators, respectively.
Source: From data in Lindeman (1942).
producers
0
20
40
60
g-cal/cm2/year
80
surrogates of this energetic perspective (Lindeman
1942; Odum 1953).
Since these early studies, the food web field has
grown enormously in size and complexity, and
modern models often incorporate population
dynamics as an important process in the structuring
of communities and food webs (May 1972, 1973;
Pimm and Lawton 1977, 1978; Pimm 1982; Paine
1988). Over the past few decades, several of the
most gifted minds in ecology have devoted extraordinary intellectual effort towards capturing a
model of natural webs. Investigators now have
immediate access to more than 200 food webs in a
shared database (ECOWeB, Cohen 1977), and it is
probably fair to say that every interaction occurring
between community members has been meticulously scrutinized and evaluated for pattern and
meaning. Indeed, several patterns have emerged
that seem to be repeatable across different food
webs. The list includes, but is not limited to a constant ratio of predators to prey, food chains are
short, three species loops are rare, omnivory is rare,
and connectance and interaction strength vary from
100
120
food web to food web (Cohen 1977, 1978; Morin
1999). However, the ecological significance of these
patterns remain controversial since many ecologists
have serious reservations about the accuracy and
completeness of food web descriptions in the database (Paine 1988; Polis 1991; Martinez 1991, 1992;
Hall and Raffaelli 1993), and contrary to the strong
assertions by many theorists, patterns from food
webs of real communities generally do not support
predictions arising from dynamic and graphic
models of food web structure (Polis 1991; Leibold
and Wooton 2001).
We now have a much better sense of the elegant
mathematical complexity of natural food webs, but
the synthesis that Elton hoped for has not yet
materialized (Leibold and Wooton 2001). The field
is now largely dominated by theorists, and dictated
by statistical and methodological issues. The book
‘Food Webs’ edited by Winemiller and Polis (1996) is
the published proceedings of a symposium to bring
together viewpoints from theoretical ecology and
empirical research in systems ranging from soil
fauna to oceans. One need only peruse the titles of
F O O D W E B PAT T E R N S
the 37 chapters (none dealing with parasites) to
recognize the tremendous diversity of approaches,
models, and analytical tools. The field is now so
large it defies simple categorization, but it is abundantly clear that food web theory has far surpassed
our experimental capabilities. This situation was
already familiar to an older Elton, who in his fifties
remarked that ‘although the subject is partly illuminated, it is also greatly obscured for the ordinary
ecologist by the brilliant cloud of mathematical
theory that has evolved’ (Elton and Miller 1954).
For the most part, parasitologists have not been
very impressed with this remarkable effort, nor
have they been overwhelmed by the conclusions. A
clear point that emerged from this debate was that
parasites had been ignored. Less than 15 webs in
the literature contain parasites, and usually the
data includes only small subsets of the parasite
community (see table 1 in Marcogliese and Cone
1997). Parasitologists are appalled (or at least act
appalled) that parasitism, a feeding strategy that is
used by 50–70% of species on earth (Price 1980; Toft
1991), has been ignored in food webs. Ecologists
respond that they do indeed recognize that parasites are ubiquitous in natural systems, that parasites can have significant effects on community
structure (Dobson and Hudson 1986; Scott and
Dobson 1989; Minchella and Scott 1991; Huxham
et al. 1995), and even that parasites can act as ‘keystone species’ in some habitats (Curtis and Hurd
1983). In such cases, they acknowledge that omission of parasites from a community web is no more
defensible than the omission of the principal vertebrate predator (Huxham et al. 1995). In addition, the
inclusion of parasites obviates any size-based cascades (a popular analytical tool), and this by itself
has led to several calls for analyses of webs that
include parasites (Price et al. 1986; Lawton 1989;
Polis 1991; Cohen et al. 1993; Goldwasser and
Roughgarden 1993; Leaper and Huxham 2002).
Nevertheless, it has been extremely difficult to
retrofit parasites into eight decades of theoretical
constructions and assumptions on the nature of
food webs.
Parasitologists themselves have been very late
entering into the food web debate. One reason is
that the field of modern parasitology operates
57
under an exacting biomedical rubric that favours
extreme empiricism, and parasitologists were not
trained to critique theoretical assumptions. Since
parasitology began incorporating explicit ecological paradigms around mid-century (e.g. Park 1948;
Haldane 1949; Holmes 1961; Schad 1963;
Barbehenn 1969), parasite ecology has grown into
an exciting discipline focusing on the rules of
assembly of parasite communities within their
hosts (see also Chapter 2), the roles of parasites in
host population regulation (see Chapter 3), and the
evolutionary and ecological implications of parasite mediation in trophic interactions (Esch 1977;
Anderson and May 1979; May and Anderson
1979; Nickol 1979; Freeland 1983; Esch et al. 1990;
Minchella and Scott 1991; Marcogliese and Cone
1997; Hudson et al. 1998; Lafferty 1999; Lafferty and
Kuris 2002; Marcogliese 2002; Moore 2002; Torchin
et al. 2003; Chapter 8). Most of the evidence for key
roles of parasites in community structure is based
on the differential susceptibility of host species to
infection and its consequences, and although in
principle these effects could greatly influence the
structure of species assemblages, the roles of parasites in community dynamics are still being
debated (Barbenhenn 1969; Holmes 1982; Freeland
1983; Price et al. 1986; Freeland and Boulton 1992;
Holmes 1996; Poulin 1999; Thomas et al. 2000a,b; see
Chapter 8). It is difficult to assess just how important parasitism is for food webs because few studies
have been designed to specifically address the role
of parasites at the community level (Mouritsen and
Poulin 2002).
4.3 Visualizing parasites in food webs
Elton (1927) was the first to argue that food cycle
pyramids could ‘be fully understood only by bringing in parasites.’ He had a good understanding of
parasites, and even authored a classic ‘parasitology’
paper on endoparasites in a mouse population
(Elton et al. 1931). His famous book is peppered
with references to host–parasite interactions and he
devoted an entire chapter, simply entitled
‘Parasites’, solely to discussing the role of parasites
in food webs. He envisaged that parasites and
hyper-parasites fit into food cycles in an inverted
58
PA R A S I T I S M A N D E C O S YS T E M S
pyramid of numbers from the top predator. Elton’s
number-based analyses are now long fallen out of
favour and we no longer think of communities in
this context, but there have been few other ideas to
supplant this inclusive perspective.
Modern ideas for including parasites into food
webs fall into one of two general categories of argument, piggybacking or statistical. The most popular
is the piggyback argument, which uses wellunderstood trophic patterns to show how parasites
fit into the web. Typically, a complex (multi-host)
parasite life cycle is depicted with arrows tracing the
parasite’s developmental path through successive
hosts, and where invariably the intermediate hosts
are eaten by the definitive hosts, for example,
Fig. 4.2. Simple one host life cycles, or life cycles with
hosts that do not interact trophically are not used as
examples. Life cycle descriptions are the result of
intensive field observations and experiments by
traditional parasitologists and they provide a natural
history perspective that is persuasive to biologists.
However, although they are powerful visual
metaphors for the parasite’s intimate connections
with trophic interactions in the food web (Price 1980;
Price et al. 1986; Marcogliese and Cone 1997;
Marcogliese 2002), life cycle diagrams by themselves
do not aid in our understanding of pattern and
process.
There are several upgraded versions of the piggyback argument, including some that verbally or diagrammatically map the parasite’s movements up
the trophic cascade. Data collected over a period of
four years from streams in the New Jersey Pinelands
were used to produce the examples of food webs in
Fig. 4.3 (a), and the same food webs with parasites
Fig. 4.3 (b). All of the interactions (arrows) in these
webs came from studies reported in the literature,
and represent probable interactions rather than
Trophic
transmission
Adult
Egg
Clinostomum marginatum
(Digenea)
Metacercaria
Miracidium
(free-swimming)
Sporocyst
Cercaria
(free-swimming)
Redia
Figure 4.2 The life cycle of the digenean
Clinostomum marginatum. Adult worms parasitize
the intestine of egrets and other fish eating birds,
where they produce eggs that are dropped into
water with the bird’s faeces. A miracidium hatches
out of the egg and swims until it finds a snail and
infects it. The miracidium sheds its cilia and
develops into a sporocyst, which then produces
multiple redia. The redia produce multiple cercaria,
which leave the snail and swim until they find a
fish to infect, and then develop into metacercaria.
Predation of fish by birds facilitates the
completion of the parasites life cycle.
F O O D W E B PAT T E R N S
(a)
American
eel
Pumpkinseed
sunfish
Chain
pickerel
Banded
sunfish
Swamp
darter
Pirate
perch
Creek
chubsukcker
Golden
shiner
Megaloptera
Coleoptera
Trichoptera
Isopods
Plecoptera
Diptera
Ostracod
Copepods
Ephemeroptera
Gastropoda
Nematode
Annelida
Collembola
Turbellaria
Sphaeridae
Cladocera
CPOM
Algae
FPOM
(b)
American
eel
Pumpkinseed
sunfish
Chain
pickerel
Banded
sunfish
Swamp
darter
Pirate
perch
Creek
chubsukcker
Golden
shiner
Megaloptera
Coleoptera
Trichoptera
Isopods
Plecoptera
Diptera
Ostracod
Copepods
Ephemeroptera
Nematode
Annelida
Collembola
CPOM
Brown
bullhead
catfish
Eastern
mudminnow
Odonata
Amphipods
Brown
bullhead
catfish
Eastern
mudminnow
Odonata
Amphipods
59
Gastropoda
Turbellaria
Sphaeridae
Cladocera
FPOM
Algae
Figure 4.3 A topological food web from a New Jersey Pinelands stream during the fall season. (a) All possible trophic interactions between fish
and macroinvertebrates, and between macroinvertebrates and their resource are shown. (b) Four helminth parasites whose adult stages parasitize
fish are tracked through the food web.
Note: Dotted lines represent the path for Fessisentis sp., dash lines Acanthocephalus sp., dash-dot lines Phyllodistomum sp., and solid black lines Crepidostomum sp.
60
PA R A S I T I S M A N D E C O S YS T E M S
actual interactions. These topological diagrams help
to visualize the complexity of natural systems, and
the complexity is vastly increased when parasites
are added. In the example in Fig. 4.3(b), only 4 of the
11 parasites in the system are mapped onto the web.
There are even more sophisticated versions of
analyses that piggyback onto food web relationships to examine parasite effects on life history
traits, parasite mediation of interactions between
competing species or to make predictions on the distribution and abundance of hosts and parasites
(Curtis and Hurd 1983; Freeland 1983; Price et al.
1986; Marcogliese and Cone 1997; Hudson and
Greenman 1998; Thomas et al. 2000a; Skorping
and Hogstedt 2001; Marcogliese 2002; Mouritsen
and Poulin 2002), but the community-level processes
of many of these interactions remain elusive.
The statistical argument for including parasites
in food webs is based on the popular approach of
analysing real food webs to determine patterns in
their properties. Food web theorists have developed sophisticated metrics to analyse food web
structure, and in these analyses, parasites are generally treated as top predators, or trophospecies
(omnivores feeding at multiple trophic level),
although their hosts (and the parasites themselves)
must fall prey to the predators. Typically, when
parasites are included in the analyses, several food
web statistics are altered, including increases in
food chain length, increases in omnivorous links
and increases in connectance (Huxham et al. 1995;
Memmot et al. 2000; Leaper and Huxham 2002).
Increases in food chain length and omnivory are
relatively easy to explain, but the meaning of
changes in connectance is less obvious. Food web
theory centres around the idea of connectance,
which in a mathematically profound way is a measure of system stability. It is the fraction of all potential trophic connections that are actually observed
in the food web under study, and is calculated as
the number of trophic links observed divided by
the maximum number of possible binary connections in the species assemblage (Cohen 1978, 1989;
Pimm 1982).
It is difficult to visualize the patterns that are illuminated by these web statistics (Raffaelli 2002). In
addition, web statistics, including connectance,
may be too arbitrary to be useful in predicting
patterns. These metrics are dependent on a variety
of subjective decisions related to lumping different
kinds of animals into single functional groups, and
thus are subject to the idiosyncrasies of each investigator. Paine (1988) provides an example where five
different analyses of the exact same food web
yielded five different connectance values that varied
by as much as 100%. Other investigators have raised
similar concerns about the artefactual view of
trophic interactions within communities that
come from these analyses (Polis 1991, 1994;
Tavares-Cromar and Williams 1996), and although
the debate is beyond the scope of this chapter, it is
clear that the search for a generalizable pattern that
includes parasites has not yet been successful.
4.4 Patterns through simplification?
Most food webs in the literature are now thought of
as incomplete caricatures of natural communities,
and there have been several calls to improve them
(Paine 1988; Pimm and Kitching 1988; Closs 1991;
Polis 1991). In general, the recommendations call
for two broad categories of improvements; more
explicitness, and more exhaustiveness (Cohen et al.
1993). For example, it is suggested that the kinds of
organisms in a food web should be reported by
using units of observation that are as refined as
possible (taxonomic resolution) to avoid the current
problems with lumping animals (Polis 1991; Cohen
et al. 1993; Goldwasser and Roughgarden 1993;
Townsend et al. 1998). Previous studies are criticized
for a failure to resolve webs at the highest possible
level of taxonomic resolution, but increasing the resolution involves a considerable increase in the effort
required (Lancaster and Robertson 1995). Recent
studies have demonstrated that improving taxonomic resolution can have significant effects on several food web statistics, including connectance, but
there is still some question as to whether rigour, or
understanding, is improved (Thompson and
Townsend 2000). Nevertheless, it appears that the
proposed solution to the already complex situation
of food webs is the addition of more complexity. The
daunting diversity of parasitic strategies that exist
is already a barrier to incorporating concepts about
F O O D W E B PAT T E R N S
parasitism (Lafferty and Kuris 2002), and we would
argue that, at least for parasites, the answer might
better come from simplification.
Simplification of any aspect of complex food
webs runs the risk of ignoring interactions that may
be important in shaping web structure. Food web
communities are envisaged as assemblages of
species populations, many of which interact with
each other to varying degrees. Thus, understanding
the system requires understanding the dynamics of
each species population, each pairwise interaction
between species, and the direct and indirect influences of the whole web of community interactions
on these relationships. If estimates of the number of
parasites species are true (⬎50% of all species on
Earth; Price 1980), then adding parasites to this mix
could make these projects even more mindboggling. On the other hand, if one tries to imagine
the simplest food web possible, it would be a food
chain. We would argue that it is at this basic operational unit that we should begin to examine the role
of parasites.
In a sense, this approach is validated by the
numerous empirical studies using simple food
chains to extrapolate the basic rules of food webs,
including those using artificially assembled protozoan food chains, or quasi-natural communities in
pitcher plants (e.g. Gause 1934; Lawler 1993;
Lawler and Morin 1993; Morin and Lawler 1996;
Ellison et al. 2002). However, this approach also
brings us back to the very beginnings of the discussion that was initiated by Elton and Lindeman, and
this time, we can also look at it from the parasite’s
perspective.
4.5 Host specificity and food webs
One of the most important issues in this debate may
be the question of specialists and generalists among
parasites, because it causes the most confusion. All
organisms specialize, and we share the view that the
dichotomy created by the terms specialist and generalist is often artificial, and comes from consideration of only one or two resources axes along which
an organism can specialize (Thompson 1982).
Parasites are highly host-specific. The classic
community-wide study of parasite specificity is
61
that of the feeding habits of parasitic beetle larvae
on the seeds of dicotyledonous plants in the tropics
(Janzen 1980), but there are numerous other examples (Price 1980). In Janzen’s study, the vast majority (83 of 110) parasite species living in the forest fed
exclusively on a single host species, 14 species fed on
2 host species, 9 on 3, 2 on 4, 1 on 6, and 1 on 8. A
great deal of evidence in the literature suggests that
phylogenetic backgrounds, body sizes, morphologies, and feeding behaviours of both players serve
to promote parasite–host specificity (Freeland 1983).
The problem is usually not why so many parasites
are highly host specific (we recognize the intimacy of
the host–parasite relationship), but why some
species appear to not specialize as consistently on a
single host species (Thompson 1982).
Part of the problem relates to the nature of
semantic definitions. Parasites are designated as
specialists or generalists with respect to the number
of hosts they use. However, these terms are still
used in a variety of different ways. For example,
some studies may base their definition of specificity
on the number of higher taxa on which a parasite
feeds, rather than on the number of host species it
feeds on because this allows inferences about the
extent to which a parasite is tracking it host taxon
phylogenetically. A parasite feeding on two closely
related hosts might be more tightly bound to its
host genome than a parasite feeding on two hosts
from different families or orders. However, as
Thompson (1982) argues, by this logic, a parasite
feeding on 12 hosts (many) in the same host genus
can be considered more host specific than a parasite
feeding on two hosts (fewer) in different orders.
The second and more important concern is a
methodological problem related to how data on
parasite host distributions are recorded, and how
these data might be used in the construction of food
webs. Consider the situation in the North Atlantic
food web, one of the most complex webs in the
world, and one that features the cod, an important
human food source (Yodzis 1996). Marine systems
are thought to have the greatest numbers of generalist parasites because it is an adaptation for completing their life cycles in a dilute open system
(Polyanski 1961; Bush 1990; Holmes 1990), and it is
no surprise to find that cod are host to 105 parasites,
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PA R A S I T I S M A N D E C O S YS T E M S
most of which are generalists (Marcogliese 2002).
This sort of data causes food webologists to tear
their hair out because of all the lines they must now
add to their interaction diagrams. However, in fact,
very few of these parasites may be relevant to the
energetic interactions occurring within specific
food chains in the web. The majority of members on
this list are paratenic generalists, and only seven of
these species are actually specific to the cod
(Marcogliese 2002). Paratenic stages enter fish
species nonspecifically, and the parasites undergo
no development in the paratenic hosts, tend to use
few host resources, and produce little pathology. It
is an opportunistic relationship, and the parasites
simply use these hosts for transport up the food
chain and for prolonged transmission in the large
ocean. Essentially, this situation is no different from
the strategy of parasites like the common liver fluke
Fasciola hepatica, whose infective stage encysts on
vegetation and awaits ingestion by the definitive
host. This strategy does not make the plant an
important part of the energy flow between the
hosts and the parasite. Thus, for the most part,
paratenic parasites tend to be unimportant in the
food webs of their hosts, and the important hosts
are the obligate hosts with whom they share
evolutionary history.
Reducing the number down to seven obligate
parasites in cod significantly eases the analytical
effort, but the web can still be complicated. Again
however, not all of these parasites might deserve
their own lines on the food web. There is an astonishing amount of regional and local specialization
by parasites. It has long been recognized in studies
of diverse groups of parasites that in species with
impressively long lists of recorded hosts, different
populations of parasites often specialize on different
host species (Gilbert and Singer 1975; Cates 1980;
Fox and Morrow 1981; Thompson 1982). For
example, resource partitioning in the ocean may
contribute to the formation of distinct regional parasite assemblages, and within a single fish species,
the parasites can vary significantly between inshore
and offshore stocks (Polyanski 1961; Thoney 1993;
Hemmingsen and McKenzie 2001; Marcogliese
2002). It is for this reason that parasites are often
employed as indicators of fish stocks or populations
(Williams et al. 1992; Arthur 1997). Therefore, before
making any inferences on the roles of parasites, it is
important to identify the parasite species cycling in
the specific food web of interest, rather than relying
on the historical data of host records.
4.6 The parasite’s perspective on host
specificity
At the simplest level, individual organisms form
the basic units of species interactions, and the
organismal perspective of parasites has not been
generally considered in the host-centric debate on
food webs. We cannot truly ‘see’ the world the way
any other animal sees it, but its perception can often
be inferred from its responses to specific conditions
in the environment (Von Uexkull 1934; Lorenz and
Tinbergen 1957). In this regard, we are interested in
the parasite’s viewpoint on the question of host
specificity.
The parasite’s perspective on host specificity is
perhaps best inferred from the numerous studies in
immunology, taxonomy, biochemistry, behaviour,
and physiology coming from the laboratories of traditional parasitologists. These data paint a picture
of exquisite and intimate specificity in parasite
interactions with their hosts. The finely tuned
processes that parasites use to evade their hosts’
immune responses, and blend unobtrusively into
their hosts’ physiological and metabolic activities,
are the stuff of every textbook on the subject.
Parasites are not just specific to their hosts, but they
are often extremely specific to certain tissues and
organs within their hosts. The classic example of
parasite microhabitat specificity is a study that
describes eight pinworm species that co-occur in
the tiny rectum of the land turtle Testudo graeca, yet
there is no overlapping in the parasites’ microhabitats (Schad 1963). Parasites often make tortuous
migrations through their hosts, using complex locomotor patterns and responses to get to these precise
microhabitats. However, despite the apparent complexity of these responses, neurobiological, neuroanatomical, and behavioural studies on diverse
parasite taxa have demonstrated that these behaviours are fixed, or genetically programmed activities
that are hardwired in the organisms (Sukhdeo and
F O O D W E B PAT T E R N S
Sukhdeo 1994, 2002). There is no plasticity in these
responses! Indeed, there is no need for behavioural
plasticity because parasites are extraordinarily well
adapted to their specific hosts (infections of the
wrong host often results in the condition of ‘larva
migrans’ where the parasites wander aimlessly until
they die). Thus, parasitologists are quite comfortable with the notion that the relationship between a
parasite and its host can be so ‘precise’ that parasite
behaviours will become fixed over evolutionarily
long periods of interaction with their hosts.
For our purposes, the more interesting viewpoint
is the perception of parasites moving about in the
free-living world of the food web, as they leave one
host and search for their next obligate host. The
evidence suggests that the free-living stages of
parasites searching for their hosts have narrow perceptual worlds, and that host-finding behaviours
are genetically hardwired and fixed. The first illustrations of a parasite’s perceptual world came from
studies on ticks (Von Uexkull 1934), but modern
examples come from the trematodes, a group that
has been the focus of more behavioural and ecological study than any other group of endoparasites. As
part of the trematode life cycle (Fig. 4.2), the cercarial stage emerges from the snail host and searches
for the next host, usually in an aquatic environment. It is difficult to do justice to the huge diversity of extraordinary and unique search patterns that
are found among the 40,000 species in this group
(Schell 1970; Kearn 1998; Combes et al. 2002), but
host-finding activities almost always include
intricate patterns of behaviours which bring the
cercariae to the host, where they attach and penetrate while discarding their tails (Sukhdeo and
Mettrick 1987). Cercarial bodies are all morphologically similar, but cercarial tails reflect the
diversity of shapes and sizes and other adaptations
to get to their hosts (Schell 1970, Kearn 1998). In
species where these host-finding behaviours have
been studied in detail, a common finding is
that the behaviours occur in repeatable fixed
patterns (Graefe et al. 1967; Nollen 1968; Rees
1971; Chapman and Wilson 1973; Haas 1974, 1976,
1992; Whitfield et al. 1977; Combes 1980; Bundy 1981;
Combes et al. 1994, 2002). Interestingly, these
complex host-finding programmes are generated
63
entirely by the tail, and the tail will execute the
programmes even if the cercarial body is removed
(Chapman and Wilson 1973; Prior and Uglem 1979;
Uglem and Prior 1983). Neurophysiological recordings confirm that this activity is initiated in the tail
and that sensory feedback from the cercarial brain
in the body is not required (Prior and Uglem 1979).
Tails have no organized ganglia or brains, and are
innervated only by primitive fixed neural networks
that must generate these complex patterns
(Brownlee et al. 1995; Solis-Soto and De Jon-Brink
1994, 1995; McMichael-Phillips et al. 1996;
Zuwaroski et al. 2001; Sukhdeo and Sukhdeo 2004),
and this is hard evidence that these host-finding
behaviours are hardwired! From the parasite’s
point of view, the host is a ‘predictable’ resource in
the space and time of the food web (Combes et al.
2002), and therefore, there is no need for plasticity
in the responses.
The significance of these observations on the
hardwired nature of host-finding behaviour is that
they argue that parasites are not just specialized
within each of their hosts, but they are equally specialized to deal with the environmental space that
connects their hosts. So, for example, in parasites
with multi-host life cycles, it suggests that there
must be long-term ecological stability in the interactions between the hosts, and between the hosts
and their environment, before the parasite can
establish a life cycle and specialize to the degree we
now see. From the parasites’ perspective, these
interacting hosts would represent stable evolutionary units (Thompson 1982) in which they can profitably invest in obligate relationships that lead to
specialization and fixation.
This view of the intimate relationship between
parasites and their obligate hosts and their host’s
environment share the same underlying principles
with arguments used by investigators who have
proposed using parasites to track consistent trophic
feeding relationships in food webs (Campbell et al.
1980; Campbell 1983; George-Nascimento 1987;
Bush and Holmes 1986a,b; Gardiner and Campbell
1992; Bush et al. 1993; Marcogliese and Cone 1997;
Marcogliese 2002). This view is also implicit in
explanations of enemy release for the numerous
examples where invaders do better than native
64
PA R A S I T I S M A N D E C O S YS T E M S
competitors because the invaders are able to leave
their parasites behind (Holt and Lawton 1994;
Torchin et al. 2003, see also Chapter 3 and 7). It is
also the view that derives from studies of coevolution in mutualistic and parasitic associations. Since
the earliest ideas of gene-for-gene interactions
between plant parasites and their host (Flor 1942,
1955), the elegant study on coevolution in butterflies and their host plants (Erlich and Raven 1964)
and the development of the first mathematical
model of coevolution (Mode 1958), the field of
coevolutionary studies has grown considerably.
Mutualists and parasites have been the focus of
much of the debate, and the basic mechanisms of
the coevolutionary process have been well
described in numerous books and reviews (e.g.
Price 1980; Thompson 1982; Price et al. 1986; Lively
et al. 1990; Toft and Karter 1990; Freeland and
Boulton 1992; Thompson 1994; Clayton et al. 2003).
Very briefly, coevolution is reciprocal evolutionary
change in interacting species, and an important part
of the definition is that it involves the partial coordination of non-mixing gene pools. The evolution of
an interaction between two host species can become
a focal point around which parasites evolve and
become part of the interaction (Price 1980;
Thompson 1982, 1994). It is generally accepted that
a basic evolutionary building block in many communities is a unit group of species within which
selection acts on all participants (Gilbert 1975, 1977,
1979; Thompson 1982), and several investigators
have reasoned that obligate parasites may effectively identify these unit groups (Price 1980;
Thompson 1982; Marcogliese and Cone 1997;
Combes 2001; Marcogliese 2002).
Consequently, when selecting a food chain for
study on how parasites might fit into trophic patterns of energy flow through the system, it is
important to include only those obligate parasites
that are hardwired to the hosts and to the dynamic
interactions occurring in the system, and which
comprise stable unit groups of species. In these
food chains, one might expect the energetic organization of trophic structure to stabilize into natural
patterns that include these parasites.
We will describe an example from a model system in the New Jersey Pinelands, and as a first
assessment of trophic relationships, we will use
biomass patterns as the surrogate for energetic
patterns.
4.7 New Jersey pine barrens
We have been studying helminth endoparasites
(Acanthocephala, Cestoda, Nematoda, and
Trematoda) that infect fish from streams in the
Mullica River watershed, which is located within
the New Jersey Pinelands (USA). The Pinelands is a
region of over 1 million acres of pine–oak forests
and sandy soil of the coastal plains. It is nestled in
the centre of one of North America’s most populous
regions, the New York City and Philadelphia metropolitan area, but a significant fraction is under
government regulation and is characterized by
minimally disturbed habitats with relatively few
farms and developed areas. High acidity and low
concentrations of dissolved solids characterize
undisturbed streams in this region (Morgan and
Good 1988; Zampella 1994), and these streams
typically support native fish communities (Zampella
and Bunnell 1998; Zampella et al. 2001). The advantage to working with food webs in the Pinelands is
that the naturally acidic system and low productivity contributes to lower overall biodiversity
(Zampella and Laidig 1997; Zampella and Bunnell
1998), and this constrains the lengths and complexity
of local food webs.
In fall 2002, we collected biomass data from four
trophic levels in a second-order stream, Muskingum
Brook, and this included leaf detritus falling into
the stream, macroinvertebrates, fish, and parasites.
Preliminary studies had previously identified two
acanthocephalan species, Fessisentis sp. and
Acanthocephalus sp. as the most abundant adult parasites infecting fish in this stream (66% of all adult
parasites). The life cycles of both of these species
occur between the same two obligate hosts: isopods,
which are one of the most numerous detritivorous
macroinvertebrates in the system (32% of detritivores), and pirate perch, which are one of the most
abundant fish species in the system, with up to 50%
of all fish caught at every sampling effort. Isopods
and pirate perch are both native to this region
(Peckarsky et al. 1990; Zampella and Bunnell 1998),
F O O D W E B PAT T E R N S
and pirate perch feed primarily on isopods
(Hernandez, unpublished data). The acanthocephalan parasites do not infect other macroinvertebrates
in the stream, and both of these parasite species
show high specificity for pirate perch over other
fish species in the system (Fig. 4.4).
The amount of leaf detritus (dry weight, in
grams) that fell into the stream was measured by
(a)
Brown bullhead catfish 1%
2% Banded sunfish
E. mudminnow 12%
Pirate perch
85%
(b)
Acanthocephalus sp.
Pumpkinseed sunfish 10%
2% Brown
bullhead catfish
E. mudminnow
13%
Banded
sunfish 8%
Fessisentis sp.
Pirate perch 67%
Figure 4.4 Distribution of adult worms of (a) Acanthocephalus sp.
and (b) Fessisentis sp. within fish species in New Jersey Pinelands
streams.
Note: The primary definitive host of these species is the Pirate Perch, a
native species.
65
placing five plastic milk crates (surface area ⫽ 0.146
m2/sample) at random locations within a 25-m transect of the stream (surface area ⬃154 m2), one month
prior to the collection of macro-invertebrates. The
macroinvertebrates were collected by taking 10
samples, using a Hess-Sampler (surface area ⫽ 0.126
m2/sample) (modified from Hauer and Lamberti
1996; Jaarsma et al. 1998), and samples were fixed in
70% alcohol and brought back to the lab for sorting
and counting under a dissecting microscope. Isopods
were one of the commonest macroinvertebrates,
and they were sexed, weighed (mg) and examined
for the juvenile stages of acanthocephalan parasites.
These juvenile parasites were then identified to
genus and weighed (mg). Fish were collected from
all habitat types for one hour within the same transect of the stream using a 4 mm seine (after methods
in Zampella and Bunnell 1998), and then brought
back to the lab where they were killed and frozen
until examined for internal parasites using standard
parasitological methods. Adult acanthocephalans
were identified to genus and weighed.
The two acanthocephalan species used in this
analysis constituted the vast majority of the obligate parasites of the fish in this food chain. Adults of
only two other parasite species were recovered
from these fish hosts, Crepidostomum sp., a trematode parasite of the intestine (55% prevalence), and
Phyllodistomum sp. a trematode parasite of the urinary tract (45% prevalence). The intermediate hosts
of these trematode parasites are amphipods, caddisflies, and dragonflies. Thus, these parasites do
not cycle through the isopod food chain, and their
biomass data were not included in the analysis of
this food chain. Biomass values for parasites were
the total of all stages of the parasites, and the biomass values of fish included all species that can act
as host. The biomass pyramids from these data are
shown in Fig. 4.5(a). These results show that in this
simple food chain, obligate parasites fall into a natural pattern at the top of the biomass pyramid. The
estimate of energy that makes its way into total
parasite biomass is ⬃4.5% of the predators’ trophic
level, and this is consistent with thermodynamic
principles of trophic inefficiencies first elaborated
by Lindeman (1942). The pyramids of numbers for
this data set is shown in Fig. 4.5(b), and it validates
66
(a)
PA R A S I T I S M A N D E C O S YS T E M S
Parasites
Fish
Isopods
Detritus
0
00
00
30
10
00
50
00
70
00
90
0 2
30 30
61 61
Biomass (g)
(b)
Parasites
Fish
Isopods
0
100
200
300
Number of individuals
Elton’s ideas of an inverted pyramid of numbers
above the level of predator. Clearly more work needs
to be done; this study was a first try, and there are
probably several ways to improve it. Nevertheless, it
is still interesting that this simple biomass pattern has
emerged, especially given the notorious quirkiness of
field studies on natural systems.
4.8 Concluding remarks
In the search for fundamental patterns that include
parasites in food webs, we have argued the need
for simplification, and suggested that simple natural food chains and their obligate parasites may
form stable evolutionary units as conceived by
Thompson (1982), and that these should be the
units of study when looking at parasites in food
webs. Our results on biomass pyramids from a simple aquatic food chain in the Pinelands suggests
that parasites might fit into a meaningful pattern of
energy flow through successive trophic levels in the
food chain. Parasites are not normally considered
to be important in the web’s energy flow, and there
has been some conjecture on how parasites can
exert major regulatory effects on host population
and yet do this without consuming much energy
400
500
Figure 4.5 (a) Biomass pyramid and
(b) numbers pyramid for acanthocephalan
parasites in the food web of Muskingum
Brook.
(Polis and Strong 1996). An alternative explanation
may relate to trophic constraints in their energy
consumption. It is reasonable that parasites should
be part of the energy pattern. Parasites are stable
features in all ecological and evolutionary landscapes, and they are subject to the same thermodynamic principles that govern their coevolving
hosts. The biomass pyramid provides a conceptual
framework of trophic structure that includes parasites, and although we must be cautious in extrapolating from our data, the pyramid suggests that
parasites may deserve to have a distinct trophic
level. This interpretation may be debatable, but it is
an idea that is easily testable in the field.
In closing, it is appropriate to consider whether
this inclusive view of parasites in the energetic pattern of food chains might be generalizable to higher
levels of ecosystem organization, and become
relevant to current debates on the interrelationships
among stability, productivity, and biodiversity in
ecosystems (Rodriguez and Hawkins 2000). We feel
that the answer to this question is yes, and that the
energetic pattern of parasites in food chains will be
reflected at the ecosystem level. As a shortcut to synthesizing a view on the complex nature of modern
food web studies, we will defer to the opinions of
F O O D W E B PAT T E R N S
Dave Raffaelli of Ythan estuary fame, an accredited
world leader in theoretical and experimental studies on food webs, and possessing the accumulated
wisdom of decades of excellent work in the field. In
a recent Science article, Raffaelli (2002) bemoaned
the complexity of mathematical and modelling
efforts that has blurred and obscured fundamental
patterns in food webs, and he argued for the return
towards more ‘Eltonian’ principles in the search for
basic patterns in food webs. As a way of conceptualizing simple patterns he created ‘Raffaelli’s pyramid’; species in a food web are grouped into
functionally similar trophic levels, and the biomass
of each level is used to construct a pyramid whose
slope may reflect system stability. We have replicated the original diagram of ‘Raffaelli’s pyramid’
almost exactly in Fig. 4.6, with the exception that
we have added the parasite’s trophic level. The
implications of this pyramid are enormous! At the
very least, adding parasites will add to the rigor of
estimating the pyramid’s slope. If this pattern holds
true at higher levels of ecosystem organization, it
may explain why we are not being overrun by parasites even though parasitism is such a popular
feeding strategy. Again, it may not be difficult to
test these ideas in the field, especially since the taxonomic identity of the parasites need not be precise
67
B
Parasites
Top carnivores
Carnivores
Herbivores
A
Plants
Figure 4.6 A hypothetical pyramid of biomass first described by
Rafaelli (2002), but modified to include parasites.
Note: Biomass decreases, as trophic level increases, and the slope of the line
AB may be a reflection of system stability.
at this level, and we would need only good estimates of their biomass.
There are many exciting directions in which we
can take this discussion, but at this time it would
consist mostly of speculation in the absence of data.
Thus, we will conclude this chapter by saying that
much work needs to be done, and that traditional
parasitologists and ecologists might benefit from
increased interactions in food web studies.
CHAPTER 5
Ecosystems and parasitism: the
spatial dimension
Robert Holt1 and Thierry Boulinier2
Within ecosystems, parasites and hosts often occur in multiple, spatially
distributed sites, dispersed over large distances. The interplay of local
interactions and dispersal at various spatial scales leads to a rich array of
spatial dynamical processes, with important implications for the ecology and
evolution of host–parasite interactions and the ecosystem impacts of
parasitism.
5.1 Introduction
Most species of pathogens and their hosts occur in
multiple, spatially distributed sites, dispersed over
much larger distances than the spatial arena that
circumscribes the lives of individuals and interactions between pathogens and hosts. Yet, some
pathogens have tiny spores and can move great distances via aerial dispersal, which potentially leads
to coupling of host–parasite systems at continental
and even global spatial scales (Brown and
Hovmoller 2002). The combination of local interactions and dispersal at various scales leads to a range
of important implications of spatial dynamics for
the ecology and evolution of host–pathogen
interactions, with consequences for the ecosystem
impacts of parasitism (Hochberg and Holt 2002).
There is a vast literature on the dynamics of infectious disease in well-mixed populations (Anderson
and May 1991). For many years, many authors have
recognized the importance of space for the ecological and evolutionary dynamics of host–pathogen
systems (e.g. Cliff et al. 1981; Bolker and Grenfell
1995) (see also Chapter 2). Mollison and Levin
(1995) provide a useful review of earlier work. We
1
Department of Zoology, 223 Bartram Hall, P.O. Box 118525,
University of Florida, Gainesville, Florida 32611-8525.
2
Laboratoire d’Ecologie, CNRS-UMR 7625, Université Pierre &
Marie Curie, 7 Quai St Bernard F-75005 Paris, France.
will not attempt to synthesize this far-flung literature
(which would take a volume all by itself), but
instead draw out some highlights that seem most
pertinent to ecosystem issues.
5.2 Ecosystem implications of parasitism:
some potential major effects
From an ecosystem perspective, parasites have several distinct consequences; spatial dynamics can
matter for each of these.
5.2.1 Population limitation and regulation
Understanding how populations are limited in
abundance, and bounded in their fluctuations, is
essential to understanding how ecosystems as a
whole are governed. Although not sufficient for
understanding ecosystem processes, the standard
concerns of population and community ecology—
the focus on processes of positive and negative feedbacks arising from density dependence, resource
dependencies, and interspecific interactions—are
necessary for understanding patterns of energy and
nutrient flows in ecosystems, and the responses of
ecosystems to disturbance and secular environmental change. Demographic effects of parasites leading
to population limitation and regulation, when
quantitatively strong, can affect many aspects of
68
T H E S PAT I A L D I M E N S I O N
ecosystem dynamics. For instance, one hypothesis
for the rich diversity of trees in tropical rain forest is
that species experience strong, intraspecific density
dependence due to host-specific pathogens acting
on seedling plants (the Janzen–Connell hypothesis,
see also Chapter 8). Given that diversity is maintained (for whatever reason), there are likely to be
numerous other differences present among species.
Such differences could be important at buffering the
system from environmental change (the ‘insurance
hypothesis’, Loreau et al. 2003)
Spatial dynamics can influence the ability of
parasites to limit and regulate their hosts, over both
ecological and evolutionary time-scales; theoretical
reasons why this is to be expected are given below.
It is thus likely that the ecosystem roles of parasites
have important spatial dimensions.
5.2.2 Energy and nutrient flows
A core concern of ecosystem ecology is to understand the fluxes of energy and material through a
given population that is potentially available to the
rest of the ecosystem. Flux rates are closely related
to the death rate of the population, which governs
the provisioning of biomass either for consumption
by higher trophic levels, or for decomposition.
Pathogens that directly increase the death rate of
their hosts will thereby facilitate entry of nutrients
into the decomposer food web. Pathogens that
make their hosts more vulnerable to predation will
alter the strength of trophic interactions, and thus
the channelling of energy and nutrients through
food webs. Parasites which lead to morbidity in
their hosts may make those hosts less capable as
consumers, making these species less significant
factors in the dynamics of their resources (both
biotic and abiotic). Spatial heterogeneity and
dynamics which influence the average parasite
‘load’ of a host population can thus have profound
ecosystem consequences.
As an example of how to place host–pathogen
interactions into a canonical ecosystem context,
consider a simple host–pathogen interaction with
classic SI dynamics (e.g. Anderson and May 1981),
in which the host is regulated entirely by the
pathogen.
69
dS
ᎏᎏ ⫽ (b ⫺ d)S ⫺ SI ⫹ ␦I,
dt
dI
ᎏᎏ ⫽ SI ⫺ (d⬘ ⫹ ␦)I.
dt
Here, S is the density of healthy hosts, and I the
density of infected hosts. Alternatively, if hosts have
a given biomass, these equations could describe
changes in biomass. Healthy hosts give birth at a per
capita rate b, and die at a rate d. Infected hosts die at
a rate d⬘, do not give birth, and recover at a rate ␦.
There is no permanent immunity, or lingering
demographic consequence of having once been
infected, following recovery. The disease transmission process is the usual mass action term, with
transmission scaled by . As long as the recovery
rate is non-zero, the population will reach an equilibrial abundance. The equilibrial densities of
healthy and infected hosts are respectively
S* ⫽ (d⬘ ⫹ ␦)/, and I* ⫽ (b ⫺ d)( d⬘ ⫹ ␦)/d⬘.
A principal concern of ecosystem ecology is characterizing and interpreting the causes of flux rates
among compartments. The total rate of production
of biomass by the host population at equilibrium
must equal the rate at which biomass enters other
compartments in the ecosystem (e.g. the food web).
Adding dS/dt and dI/dt, at equilibrium we have
total deaths equal to total production, or
dS* ⫹ d′I* ⫽ bS* ⫽ b(d′ ⫹ ␦)/.
Note that this measure of production does not
depend upon the basic death rate of the host, when
healthy, but instead depends upon the death rate of
infected hosts. Given that the pathogen regulates
host numbers, one ecosystem ‘function’ performed
by that host (namely, its production) appears to be
governed by the death rate of infected hosts.
However, note that an alternative parameterization
of the model is to write the death rate of infected
hosts as the basic death rate of healthy hosts, plus a
difference term, that is, d⬘ ⫽ d ⫹ q, where q measures
the mortality effect of the pathogen. So the basic
death rate of the host is not necessarily irrelevant, but
environmental factors which may affect the death
rates of healthy hosts but not the death rate of
infected hosts will not alter the productivity of the
population, and thus not change the flux of materials
70
PA R A S I T I S M A N D E C O S YS T E M S
and energy it provides via deaths to other ecosystem compartments. This is not an implausible scenario. For instance, if deaths arise due to aggressive
contest competition, and infected individuals avoid
such aggressive encounters, spatial variation in the
intensity of competition will not influence the death
rate of infected individuals and so would not be
expressed in ecosystem fluxes through the population. This model of course does not directly consider space, but it does suggest some hypotheses
regarding spatial effects that could be assessed in
more complex models. For instance, if spatial
dynamics tends to produce systems with overall
lower transmission rates because of the spatial
localization of interactions (see below), this should
increase host population size, and thus enhance the
particular ecosystem process of production.
If spatial dynamics lead to shifts in virulence (as
measured by d′), then this will likewise alter the contribution of this host species to ecosystem productivity. Some models discussed below suggest that
spatial dynamics can characteristically produce systems with lower levels of virulence (viz., lower d⬘).
If so, then the total production of the host population in the ecosystem context will be reduced. This
may seem counterintuitive. The reason for this is
that with lower virulence, the host population will
equilibrate with fewer healthy hosts, and more
infected hosts. In other words, with lower virulence
the host carries a heavier load of parasites. We have
assumed that infected individuals do not reproduce,
and that the parasite is the sole factor regulating
host numbers; hence, this decrease in virulence can
shift individuals from productive to nonproductive
states, and so depress host population productivity.
Also, somewhat counterintuitively, an increase in
the recovery rate for individuals at the level of the
population translates into an increase in total death
rate (for all individuals). Any ecosystem factors that
might influence recovery rates (e.g. the presence of
bioaccumulated toxins) could thus indirectly alter
population productivity and flux rates to other
ecosystem compartments.
Finally (and to return to the spatial theme of this
chapter), assume that the above model applies in
each of a number of distinct habitats, which each
reach their own respective demographic equilibria.
The habitats differ in one or more parameters in a
fixed manner (e.g. due to topographic, edaphic, or
climatic factors, or because they are at different
stages of plant succession). An expression for the
average productivity per habitat is given by taking
the expectation of the above expression, or
E[b(d⬘ ⫹ ␦)/]. If the parameters vary across space
independently, then by using Jensen’s inequality it
is immediately apparent that the only parameter
for which spatial variation affects the mean is the
transmission rate. A host with a spatially varying
transmission rate has a higher production, averaged over a landscape, than does a similar host
with the same average transmission rate, but one
which is spatially invariant.
For most of the remainder of this chapter, we will
not directly consider ecosystem processes, but rather
focus on the population and evolutionary dynamics
of the host–pathogen system, and how these are
influenced by space. Throughout, however, there is
assumed to be an implicit link to ecosystem function,
via impacts of pathogens on host abundance and
stability. Moreover, even if this link is not of direct
interest, ecosystem context (e.g. habitat productivity,
patterns of spatial connectivity) can be of great
importance in determining the population and
evolutionary dynamics of host–parasite systems.
5.3 Spatial variability in empirical
patterns of parasite distribution within
ecosystems
Before reviewing models of spatial dynamics in
host–parasite systems and their implications for the
understanding of epidemiology and evolution, we
present some empirical patterns that stress the role
of space at various levels within ecosystems and
highlight a series of factors that have been considered or need to be considered in theoretical
studies.
5.3.1 Geographical distribution of parasites
species: availability of hosts and opportunity
for transmission
Parasites need their host(s) to complete their life
cycle, either as an important source of nutrients (for
T H E S PAT I A L D I M E N S I O N
example, for many ectoparasites like fleas,
mosquitoes, or ticks parasitizing vertebrates) or as
a habitat to live and reproduce (for example, for
some helminthes and microparasites such as bacteria and viruses). The distribution of hosts in the
environment will thus condition the distribution of
their parasites. This constraint is especially strong
as most parasites are specialized to a limited number
of hosts, and also because some parasite life cycles
are complex and involve series of hosts, with some
playing the role of vectors or of intermediate hosts
(Combes 2001). Before considering the factors
affecting the spatial variability in the distribution of
parasites within a given host population, a first step
is thus to see how heterogeneity in the spatial
distribution of parasite species within ecosystems
relates to the spatial distribution of their hosts.
As most species are parasitized by several parasites, most of which are specialized to a given host
species, the diversity of parasite fauna is spatially
constrained, within and among ecosystems, by the
diversity and ecology of their component species.
The spatial distribution of parasites is also affected
by the opportunities for completing their cycle
which can be prevented by abiotic conditions outside their hosts. An example of this involves arctic
ecosystems (see also Chapter 6) where an important
component of the parasite fauna of seabirds are the
flukes (Digenea), and where a detailed study of
such parasites compared their distribution between
two intermediate host species and among spatial
locations (Galatkionov and Bustnes 1999). Different
species of digeneans have life cycles which may
consist of one intermediate host and no free-living
larval stages, two intermediate hosts and one freeliving stage, or two intermediate hosts and two
free-living larval stages. The study examined the
distribution of such parasites in the intertidal zones
of the southern coast of the Barents Sea (northwestern Russia and northern Norway) by investigating
two species of periwinkles (Littorina saxatilis and
L. obtusata) which are intermediate hosts of many
species of digeneans. A total of 26,020 snails from
134 sampling stations were collected. The study
area was divided into five regions, and the number
of species, frequency of occurrence, and prevalence
of different digenean species and groups of species
71
(depending on life cycle complexity) were compared
among these regions, statistically controlling for
environmental exposure. The authors found 14
species of digeneans, of which 13 have marine birds
as final hosts. The number of species per sampling
station increased westwards, and was higher on the
Norwegian coast than on the Russian coast. The frequency of occurrence of digeneans with more than
one intermediate host increased westwards, making
up a larger proportion of the digeneans among
infected snails. The prevalence of different species
showed the same pattern, and significantly more
snails of both species were infected with digeneans
with complicated life cycles in the western regions.
The authors concluded that the causes of changing
species composition between regions are probably
(1) the harsh climate in the eastern part of the study
area reducing the probability of successful transmission of digeneans with complicated life cycles;
and (2) the distribution of different final hosts
(Galatkionov and Bustnes 1999).
The combined effect of spatial variability in host
availability and abiotic conditions on levels of parasite infestation has also been addressed for other
ecosystems. Ecosystems at tropical latitudes are
well known for harbouring much higher number of
animal and plant species than at higher latitudes
(e.g. Rosenzweig 1995), and these areas are thus
expected to harbour more parasite species. The picture is not that simple though. For instance, despite
some evidence of higher parasite richness in marine
fish ectoparasites (Rohde and Heap 1998), field
studies conducted on communities of endoparasites of freshwater fish as a function of latitude have
reported lower richness in host species living in
tropical areas than at higher latitudes (Choudhury
and Dick 2000). This result holds even after controlling for potential confounding effects such as
sampling effort, host body size, and phylogenic
relationships among host species (Poulin 2001).
Geographical differences in the diet of related
host species are likely to affect the richness of the
endoparasite fauna, whereas latitudinal effects in
ectoparasite richness may be more related to the
abiotic characteristics of the environment in which
the host species live (Rohde and Heap 1998). Other
factors such as spatial variability in the seasonality
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PA R A S I T I S M A N D E C O S YS T E M S
of host reproduction and the biogeographic history
and diversity of actual or potential host species also
have to be considered.
The geographic range of a host and its specialist
parasites may thus differ, with the geographic
range of the host being usually larger than that of
the parasite (though interesting exceptions to this
generalization may occur if parasites have widely
ranging transmission stages in their life histories).
Some parasite species with complex life histories
and intermediate host species may actually show a
much broader apparent geographic distribution
than any one of their host species. In such cases the
parasite geographic distribution may nevertheless
be strongly constrained by one of the host species,
as for instance when the transmission among final
hosts needs to be done through a species playing
the role of a vector. Vertebrate species affected by
blood parasites such as Plasmodium spp. may carry
the parasite all over the world in their bodies (e.g.
during seasonal migration or business travel) but
the transmission of the parasite to another final
host is nevertheless constrained by the need for a
local host species that will play the role of a competent vector (Kiple 1993). The type of life cycle
will thus affect greatly the geographic distribution
of a parasite and its ecological meaning: some
microparasites which are directly transmitted
among hosts will be found everywhere hosts are
found in sufficient density, but some parasites with
extensive free living stages or complex life cycles
involving different host species may on the contrary have geographic distributions that do not
match tightly those of their hosts.
A low richness of parasite and host communities
in some areas, for example, at very high latitudes
(see Chapter 6), does not mean that parasites are of
negligible importance in these systems. For
instance, an extremely high prevalence of infestation of the sibling vole Microtus rossiaemeridionalis
by the taeniid tapeworm Echinococcus multilocularis
has recently been reported in a geographically isolated and very small population of that small mammal in the Svalbard archipaelago (Henttonen et al.
2001). The life cycle of the parasite involves the arctic fox Alopex lagopus as final host; long distance
movements by foxes between Siberia and Svalbard,
together with the human-mediated introduction of
the vole to Svalbard, are likely responsible for the
presence of the parasite in such a remote population of the intermediate host (Henttonen et al. 2001).
E. multilocularis is the agent of a life-threatening
zoonosis. Thus, this example highlights the different roles that humans can play in a spatial context,
sometimes being inadvertently efficient at changing the spatial availability of hosts and facilitating
the completion of life cycles (see also Chapter 10). A
better understanding of the role of space in the
dynamics of host–parasite interactions can be gained
by considering the processes responsible for the
distribution of parasites among hosts at different
scales.
5.3.2 Aggregation of parasites among hosts
and spatial distribution of hosts and parasites
A striking and taxonomically widespread pattern is
that the distribution of parasites among hosts
within populations is typically aggregated, that is,
most host individuals have no parasites but a few
hosts are infested by many parasites (Shaw and
Dobson 1995). Another often reported pattern
[when the spatial locations where the host individuals were sampled are known] is that the proportion (prevalence) of parasitized hosts varies among
areas (Wilson et al. 2002). These observations are
key to understanding the importance of spatial
variability in host–parasite interactions within
ecosystems. Analyses of spatial aggregation have
mostly been done for macroparasites (Hudson and
Dobson 1995). Little explicit attention has been
given to this in microparasites, the abundances of
which are usually not quantified within individual
hosts, and for which the reporting of prevalence is
often linked with information on their rate of
spread in the host population (see below). The existence of latent periods in infection, and asymptomatic infected host individuals, is however
consistent with heterogeneity among host individuals in the abundance of pathogens within them.
A concern with overdispersion and aggregation as
defining attributes of the distribution of parasites
among hosts is important, as this form of spatial
heterogeneity has been identified as a key factor for
T H E S PAT I A L D I M E N S I O N
the stability of the dynamics of host and parasite
populations (Anderson and May 1978; Jaenike 1996).
Many factors can contribute to generating an
aggregated distribution of parasites among hosts,
including hosts with different histories of exposure of
hosts to parasites, and differential susceptibility of
host individuals to parasites. These factors may be
structured in space at different scales, and this structuring may contribute to the aggregated distributions
of parasites among hosts. Indeed, pooling of individuals from locations with different levels of infestation
into single combined analyses can generate an overall aggregated distribution. Classically, explicit information on the relative spatial location of the host
individuals has seldom been considered in the analysis of aggregative distribution patterns. It is nevertheless interesting to measure aggregation at
different spatial scales to attempt to identify the
spatial scale at which the aggregative process is
occurring (Boulinier et al. 1996). The tick Ixodes uriae
has for instance been found aggregated among
nestlings of its seabird host, the black-legged
kittiwake (Rissa tridactyla), when all samples were
pooled, but when the level of aggregation was quantified both within-nest among nestlings and among
nests within an area, the ticks were found aggregated
among nests but not among nestlings within nests
(Boulinier et al. 1996). This pattern is not surprising,
given the specific features of the system considered;
the ectoparasite, which has limited mobility, infests
the nesting substrate of the breeding colonies of its
host, and nestlings within each nest share traits in
common likely to affect their levels of tick infestation.
In this species, aggregation is evident among
nests. This pattern may be due to a combined effect
of the correlated age of the nestlings within each
nest, some genetic basis for susceptibility to the
ticks (Boulinier et al. 1997) and spatial heterogeneity
in local exposure to the ticks which overwinter in
the nesting substratum. Within a breeding cliff,
spatial autocorrelation in the level of infestation of
nestlings has for instance been reported (McCoy
et al. 1999). Another potentially important factor is
an induced maternal response by females against
local parasites (Gasparini et al. 2001). A comparable
approach to partitioning aggregation at different
scales has been conducted with other systems (e.g.
73
Haukisalmi and Henttonen 1999; Elston et al. 2001;
Poulin and Rate 2001; Latham and Poulin 2003) and
often a minimal spatial scale is identified at which
little aggregation is found (Jaenike 1994). In such
cases, the identification of the spatial scale at which
aggregation occurs helps to identify which
processes are potentially important in the transmission of the parasites and the maintenance of infestation. It can also facilitate the identification of
environmental variables possibly responsible for
the variable levels of local infestation, as is done in
the field of landscape epidemiology. In landscape
epidemiology, geographic information systems
(GIS) combining field data with remotely collected
data on climate and landscape attributes (Hess et al.
2002), and geostatistic modelling (e.g. Kitron et al.
1996; Diggle et al. 2002; Srividya et al. 2002), are
being increasingly applied. When the spatial distributions studied are those to vectors for parasites,
host aggregation is especially important to consider; the reason for this is that aggregative
responses of vectors to hosts can define foci of
transmission (e.g. Perkins et al. 2003).
It should further be noted that spatial structure in
infestation levels is not static, because it arises from
the interplay of the local population dynamics of
hosts and parasites, and dispersal by each species,
potentially at different scales. This can be especially
evident when studies are conducted at different
time intervals, permitting the temporal dynamics of
the spatial distribution of infestation to be apprehended. The role of space in this context is highlighted in the study of the spatial dynamics of
epidemics in ecological landscapes (see below).
5.3.3 Determinants of dispersal and
host–parasite interactions
Dispersal is now recognized to be a major factor
affecting the spatial dynamics of populations. This
is especially likely for parasites, as hosts and
groups of hosts can be considered as islands among
which parasites must disperse, to persist (Boulinier
et al. 2001). Dispersal can enable individual parasites (either within or outside of host bodies) to
reach groups of hosts that are susceptible and/or
uninfected. It will also lead to gene flow.
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Dispersal can be linked with transmission, but
dispersal and transmission can also occur
independently. Dispersal is usually modelled as a
rate that can vary with habitat, but factors directly
related to the host–parasite interaction can be
involved as well. For instance, dispersal of hosts
could be affected by the local level of parasite infestation. In colonial birds, increased natal dispersal of
cliff swallows (Hirundo pyrrhonota) (Brown and
Brown 1992) and breeding dispersal in black-legged
kittiwakes have been associated with higher level of
ectoparasite infestation of nesting areas (Boulinier
et al. 2001). Nevertheless, few studies have addressed
the question of how dispersal rates and transmission
rates and patterns are interrelated.
If parasite infestation can lead to host dispersal,
movement of hosts can also be responsible for the
dispersal of parasites. And indeed, the few studies
that looked at the population genetic structure of
parasites as a function of their host ecology have
shown patterns suggesting that host movement is
responsible for parasite dispersal (in large herbivores, Blouin et al. 1995; seabirds, McCoy et al. 2003;
and salmonids, Criscione and Blouin 2004).
Movement of hosts leading to parasite dispersal
may not imply host dispersal. Making such a distinction is important as it will affect differently the
spread of parasites, and thus epidemiology, but
also the relative gene flow of host and parasites,
and thus the dynamics of host–parasite coevolution
(see Holt and Hochberg 2002 and below).
Keeping in mind the potential need to incorporate these complex spatial processes when considering some specific host–parasite systems, simple
modelling approaches can nevertheless capture the
main properties of the dynamics of host–parasite
interactions in a spatial context.
5.4 Host–parasite interactions in
coupled, heterogeneous patches
One straightforward way to incorporate space into
host–pathogen systems is to imagine that the environment is comprised a number of distinct habitats.
In each of these, there is a well-mixed population of
hosts and pathogens, described by standard epidemiological models. The habitats are then coupled
by dispersal of hosts, pathogens, or both. Examples
of authors who have explored such models include
Post et al. (1983), Rodriguez and Torres-Sorando
(2001), Hethcote and Ark (1987), Diekmann et al.
(1990), Sattenspiel and Dietz (1995) and Sattenspiel
and Simon (1988). In general, the conditions for
establishment of the parasite, and its equilibrial
incidence, can be strongly influenced by heterogeneity among habitats. Sattenspiel and Dietz
(1995) provide an expression for establishment of
an infectious disease in a spatially heterogeneous
population, where total numbers are fixed by
factors other than the disease (as appropriate for
many infections of humans, for example). Rodriguez
and Torres-Sorando (2001) develop comparable
models for malarial infections of humans, and
Diekmann et al. (1990) discuss the general issue of
calculating the basic reproductive ratio R0 in
heterogeneous populations.
In principle, there are no conceptual complexities
in this, but in practice it can be difficult to wade
through the algebraic tangles which arise when
analysing models with multiple patches and nonuniform mixing. As a relatively simple example, we
consider the problem of initial establishment of an
infectious disease in a landscape consisting of just
two distinct habitats (one with area A1, the other
with area A2) coupled by host movement. In the
absence of the disease, we assume that the host in
each habitat equilibrates at a carrying capacity, that
the disease has direct transmission, and that both
healthy and infected hosts can move between habitats at constant per capita rates (though possibly at
different rates in the two habitats). A model for this
scenario which describes the initial stage of infection
is given by duplicating the above SI model, with two
pools of infected individuals (recall, for the moment
we are assuming that the host population is initially
all healthy hosts, with fixed densities). The model
describing the initial stages of infection is
dI
ᎏᎏ1 ⫽ 1S1I1 ⫺ (d1′ ⫹ ␦1)I1 ⫺ m12I1 ⫹ m21I2(A2/A1),
dt
dI
ᎏᎏ2 ⫽ 2S2I2 ⫺ (d2′ ⫹ ␦2)I2 ⫺ m21I2 ⫹ m12I1(A1/A2).
dt
All the parameters in the above earlier SI model
have now been made habitat-specific. In addition,
T H E S PAT I A L D I M E N S I O N
we have assumed that infected individuals can
move between habitats, at rates that are also
potentially habitat-specific. (Healthy hosts may
also be moving, but if so, they are assumed to do so
in a manner that does not alter the pattern of abundances between habitats). Because the variables are
cast in terms of density, the fluxes between habitats
have to be adjusted to account for the fact that the
number of individuals per unit time moving from
habitat i to habitat j equals the product of the density in habitat i, the area of habitat i, and the migration rate; whereas, the impact this influx of
individuals has on density in habitat j has to be
scaled against the area of habitat j.
The above model is a pair of coupled linear differential equations, so it can be fully analysed. In particular, the dominant eigenvalue of the characteristic
matrix defines the growth rate of the infection over
both habitats, after an initial transient phase. For
simplicity, we combine infection, death, and recovery into a habitat-specific intrinsic growth rate for
the infection, when rare:
ri ⫽ iSi ⫺ (di′ ⫹ ␦i).
A habitat may foster a high initial growth rate for the
parasite simply because there is a high density of
hosts there, or instead because of individual impacts
of the infection upon hosts (e.g. locally low death
rates of infected individuals). We assume that habitat
1 has the higher growth rate. With this notation, the
growth rate of the infection can be shown to be
1
[⫺m12⫺m21⫹r1⫹r2
2
⫹兹(m12⫹m21⫺r1⫺r2)2⫺4(⫺m21r1⫺m12r2⫹r1r2)].
(see Holt 1985 for an analogous treatment of population increase in a two-habitat environment, albeit
with symmetrical movement).
This expression can be manipulated to make
some general statements about how habitat heterogeneity influences the establishment of a disease.
1 Note that the relative habitat areas drop out. The
slightly counterintuitive result is that a combination of intrinsic habitat qualities influences invasion
rates, but relative habitat areas do not. The reason
for this is basically that with reciprocal movement,
the descendents of any given individual cycle
through both habitats. Overall, the asymptotic
75
growth rate reflects a nonlinear averaging of the
growth rates of the two habitats.
2 If we let both movement rates be equal, and then
take the limit as they get very large in the above
expression, the growth rate simply becomes the
arithmetic average over the two habitats, (r1 ⫹ r2)/2.
In this limit, the landscape is actually just one habitat with internal heterogeneity. Given rapid movement of infected individuals, landscapes with the
same average growth rate (averaged among habitats) but different degrees of internal heterogeneity,
nonetheless should have the same growth rate for
the infection.
3 If both intrinsic growth rates are positive, so is the
overall growth rate; conversely, if both growth rates
are negative, the overall growth is also negative.
Parasite invasion requires that there be at least one
habitat in the landscape which is intrinsically
favourable, and could potentially sustain an invasion
on its own (were infected individuals not to move).
4 If we let m21 approach zero, while keeping
the other movement rate fixed, all movements
will be from habitat 1 into habitat 2. In this case,
the growth rate overall converges on the growth rate
of the better habitat (which we have assumed to be
habitat 1) minus losses to emigration. Thus, an infectious disease may grow in habitats where it has an
intrinsic growth rate less than zero, provided it is
maintained in habitats where it has a positive growth
rate. All else being equal, such ‘spillover’ modes of
invasion by an infection should be most noticeable in
habitats with lower than average host densities (this
result emerges from inspecting the eigenvector
describing the distribution of individuals between
the two habitats, when the invasion has settled into
its equilibrial rate of change).
The above bit of theory provides insight into how
spatial heterogeneity can influence parasite establishment. We would be the first to admit that this
provides just a first pass through this problem.
A full analysis of this issue would require one to
analyse more complex landscapes, alternative
transmission dynamics, additional classes (e.g.
hosts with acquired immunity) and so on.
Moreover, we have not paid attention to feedbacks
via depression of healthy host numbers, or to
transient dynamics.
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Some insights into the consequences of habitat
heterogeneity for disease dynamics can be also
gleaned from parallel studies of the classical
Lotka–Volterra predator–prey model, in which prey
grow exponentially in the absence of predation,
predators die at a constant rate, and the two are
coupled by a mass action term describing predator
attacks. This familiar model emerges as a limiting
case of the standard SI epidemiological model (Holt
and Pickering 1985), when infected individuals
have very low recovery and birth rates. Holt (1984)
analysed two habitat patches with Lotka–Volterra
interactions occurring in each, and predator movement. With some simple reinterpretation of parameter definitions, this is also the SI host–parasite
model for two habitats, with movement of infected
individuals. (A number of authors have found general Lotka–Volterra models to provide useful limiting cases for explorations of host–parasite ecology
and evolutionary dynamics, for example, Frank
1997). Spatial heterogeneity is broadly stabilizing,
because it permits source–sink populations to
develop, in which some host species are more
heavily exploited than expected from just local
conditions alone.
When healthy hosts are also allowed to move
(Nisbet et al. 1993), more complex scenarios are feasible in heterogeneous landscapes. The basic point is
that in some circumstances spatial heterogeneity
coupled with dispersal can lead to stability, and in
others, it leads to instability (Holt 2002). Despite
this potential for a diversity of effects of spatial heterogeneity, our sense is that more often than not,
spatial heterogeneity is broadly stabilizing (Hoopes
et al. in press).
The above remarks pertain to heterogeneity that
arises from variance in local conditions (e.g. productivity, or rates of infection). In other systems,
heterogeneity in rates of movement or mixing can
itself also promote stability (Holt 1984 notes this
case for the Lotka–Volterra model). Gubbins and
Gilligan (1997) carried out an experiment and
demonstrated that heterogeneity in parasite establishment (due to incomplete mixing) promoted the
persistence of the mycoparasite Sporidesmium sclerotivorum, a biological control agent on Sclerotina
minor (a fungus on lettuce).
In a heterogeneous landscape, flows among habitats can permit greater parasite loads to be maintained in some habitats than would be expected just
from local dynamics. Hochberg and Ives (1999)
show that if there is substantial spatial variation in
host productivity, flows of natural enemies (e.g.
pathogen transmission stages among habitats) can
lead to restriction of species from particular habitats, and even define the edges of geographical
ranges for hosts. The model of Holt (1984; see also
Holt 2002) mentioned above shows that ‘spillover’
limitation of a host in a low productivity habitat
can readily arise, if this habitat is coupled with a
high productivity habitat. This can be viewed as a
kind of apparent competition, linking the dynamics
of host populations that live in different habitats.
Hosts that occupy low productivity habitats are
vulnerable to the impact of parasites maintained in
more productive habitats. This is true regardless of
whether the populations are the same biological
species of host, or are different host species. In the
latter case, one may observe indirect exclusion of
one host by another via shared parasitism (Holt
and Pickering 1985), even though the two hosts
never cooccur in the same habitat patch (a specific
metapopulation model of this effect is in Holt 1997).
All of these landscape effects depend on the movement of parasites across space, either because
infected hosts themselves move, or because the
parasites have free-living, mobile life history stages
(e.g. aerial spores), or because movement is
provided by the behaviour of vectors.
5.5 Epidemics in a spatial context
One broad class of examples of spatial host–parasite
interactions, to which we will not attempt to do real
justice, is the study of epidemic waves across space
(e.g. of dengue fever emanating from foci in
Thailand, Cummings et al. 2004). The theoretical
models which have most often been used in this
context are partial differential equations describing
invasive waves of epidemic disease. Just to mention
one interesting example, Murray et al. (2003)
explored a spatially distributed mass mortality
event in an Australian pilchard (Sardinops sagax)
population. Their model tracked susceptible,
T H E S PAT I A L D I M E N S I O N
infected and latent, infected and infectious, and
finally removed (dead or recovered) individuals. As
in most such models, the wave velocity is sensitive
to diffusion coefficients, viral transmission rates
(which enter into local intrinsic growth rates, see
above), and latency period. Large-scale spatial
heterogeneity in these parameters can help explain
differences among regions in the time course, spatial development, and intensity of the epidemic.
The broad ecosystem consequence of these epidemic waves is that they act as major disturbances
in the ecosystem, with potential ripple effects on
many other species. An example of such a perturbation is provided by the chestnut blight fungus
(Cryphonetria parasitica), which decimated the
American chestnut (Castanea dentata) throughout
the eastern deciduous biome of the United States in
the early decades of the twentieth century. This
species was once the dominant tree in this biome,
but the fungus destroyed approximately 3.5 billion
trees (Taylor 2002). Other species of tree have filled
in the gaps left by the demise of this species. Its
wood is resistant to decay, and there are still many
places in the southern Appalachians where chestnut logs are prominent features of the understory
(personal observation). Although the ecosystem
consequences of this epidemic (say on soil properties) are not well documented, they are doubtless
profound and long-lasting in these systems.
5.6 Effects of space in homogeneous
environments
Spatial dynamics can influence stability and persistence of host–parasite systems, even in the
absence of heterogeneity. For instance, Jansen and
de Roos (2000) analysed the Lotka–Volterra model
for two coupled habitats, with uniform predator
movement, and no parameter differences between
the two habitats. Ultimately, these systems settle
into spatially uniform, neutrally stable oscillations.
In a single patch, these oscillations can be arbitrarily
large. But the transient dynamics (which may be
very long) in the two patch model can be very different. In particular, Jansen and de Roos show that
in the long run, fluctuations of large amplitude will
not be observed, for nearly all inhomogeneous
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starting conditions. Such stability effects become
greatly amplified when one pays due attention to
the discreteness of individuals. Because interactions are spatially localized, and occur between
individuals who experience the chance vicissitudes
of birth, death, and movements, stochastic variation alone can lead to a shifting pattern of heterogeneity in host–pathogen interactions even in a
homogeneous environment. This basic insight
underlies a vast array of recent studies of space in
ecological systems (Tilman and Kareiva 1997).
Space becomes particularly important when infection occurs only over short distances among individuals who themselves do not move (e.g. plant
populations). Keeling et al. (2000) provide a general
argument on how limited movement in naturalenemy victim systems generically leads to spatial
structure, which in effect provides refuges for the
host/prey, and generates exploitative competition
among parasites/predators.
Introducing demographic stochasticity creates
many challenging mathematical problems, but also
a consideration of demographic stochasticity points
to some important potential implications of spatially localized infection processes. Rand et al.
(1995) and Keeling (1999, 2000) considered a system
in which a virulent disease is spreading through a
slowly growing, sessile population (e.g. a fungal
pathogen on a plant population). The model is a
probabilistic cellular automata model for a
host–parasite system, which attempts to capture in
a simple way the consequences of localized
infection and host renewal processes. The system
consists of a lattice of sites, each of which can be
empty, occupied by a healthy host, or, occupied by
a parasitized host. What happens at each site
depends upon its current state and that of its
immediate neighbours. Healthy hosts send offspring
into empty adjacent sites (e.g. a plant sending out
seeds over a short distance); if healthy hosts are
next to an infected host, they can be infected, with
a fixed probability. For simplicity, Keeling assumes
that infection is lethal.
This model suggests a number of important messages that appear to characterize a much broader
range of models. First, there is a range of transmissibilities, within which the pathogen persists, and
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outside of which it cannot. If transmission rates are
too low, then the ‘birth’ rate of new infections will
not exceed the rate at which infections are lost to
mortality. This of course describes nonspatial infection dynamics, too. More interestingly, if transmission rates are too high, then persistence may also be
unlikely. The reason for this is that the pathogen in
effect overexploits its hosts in localized arenas, and
then itself is vulnerable to extinction. The interaction between the host and pathogen leads to a fracturing of both populations into small isolated
patches; the pathogen can then easily disappear
locally due to demographic stochasticity. Second,
given that the interaction persists, it can do so at
very low levels of overall prevalence, compared to
expectations drawn from homogeneous, meanfield models, in effect because the localization of
interactions and dispersal permits the emergence of
ephemeral transient refuges. In a sense, the localization of interactions can be viewed as a reduction
in the overall rate of infection, per host, so that the
impact of the parasite upon the population dynamics of its host is reduced. Third, because the system
is probabilistic and tracks integer numbers of individuals, the local environment is often found in a
state which is very far from the global average, and
there are dramatic fluctuations in infection at a local
level. Fourth, there is an emergent spatial structure,
in which parasites spread as wave fronts through
the susceptible hosts, with patches empty of hosts
left behind in the wake of the wave.
Many of these results appear in a wide range of
models. Haraguchi and Sasaki (2000) examined
how spatial structure influenced the evolution of
virulence and transmission rate in a parasite interacting with a host in a lattice. The host was
assumed not to be evolving. Constraining transmission so that it only occurs through local contact
leads to evolutionarily stable traits of parasites that
are completely different than expected with complete mixing. Viscosity tends to select for an intermediate ESS rate of transmission, even without the
classical tradeoff between transmission and virulence. They found an interaction between the host
growth rate and parasite evolution; at low host
growth rates, the parasite had difficulty persisting
near its ESS, whereas at high host growth rates, the
parasite could overexploit its host, with both risking extinction. This is an evolutionarily driven analogue of the classical ‘paradox of enrichment’.
Analysis of a similar system by Rauch et al. (2003)
using techniques which tracked genetic phylogenies revealed some interesting features. Mutant
strains continually arise with higher transmission
and virulence. However, these strains, after a
period of growth, deplete hosts within regions, and
then themselves go extinct. This leaves behind
pathogens with intermediate virulence. Thus, the
evolution of the whole system reflects a selforganized spatial structure (which amounts to a
kind of group selection).
If these results prove to be general, they obviously have important consequences for ecosystems.
For instance, the spatial localization of interactions
may mean that some pathogens may be less important factors regulating population size (and thus
exert a relatively weak influence on biomass production, nutrient pool fluxes, and so on) than
expected judging from the direct impact of the
pathogen upon individual hosts. Such ecosystem
effects, moreover, may be highly heterogeneous
across space and through time.
Properties of the ecosystem may in turn feed
back on the host–pathogen interactions observed.
One general finding in lattice models (which is usually treated as an inconvenience by theoreticians) is
that the size of the lattice can influence the probability of persistence of the infection. There are two
distinct reasons for this. First, there is often a characteristic length scale describing the correlation
among nearby cells, reflecting the emergence of
spatial asynchrony in dynamics. A lattice that is
smaller than this characteristic scale will not contain sufficient spatial heterogeneity among patches
in the phase of the host–parasite interaction to persist. Second, in models which are stochastic (e.g.
individual-based models), the probability of randomly fluctuating to extinction over a given time
frame goes up rapidly as the maximal number of
individuals declines (a result which in general ecology goes back at least to MacArthur and Wilson
1967). This is closely related to the concept of a ‘critical community size’ in epidemiology, which is
defined as the minimum size of a population
T H E S PAT I A L D I M E N S I O N
required for a disease to persist (Bartlett 1957).
Wilson et al. (1998) explored a tritrophic host–
parasitoid–hyperparasitoid interaction. Within each
cell in a lattice, interactions tended to be unstable,
and dispersal occurred among adjacent cells. There
was a very strong lattice size effect on the persistence of the system, and the full tritrophic interaction
required a much larger lattice to persist than did the
host–parasitoid interaction along. It is often difficult
to gauge the critical size theoretically (Dye 1995),
but it is clear that ecosystem size is an important
ecosystem factor which can influence the character
of the host–parasite interactions one might observe
in natural systems. We suspect that characterizing
the effects of ecosystem size on host–parasite systems is a topic that will receive much more attention
in the future (for related thoughts on how ecosystem
size governs food web attributes, see Holt et al. 1999,
Post 2002, and Holt and Hoopes, in press).
The generalization that the spatial localization of
interactions may quite broadly facilitate the persistence of parasites in ecosystems emerges in many
situations. For instance, Grenfell et al. (1995, see also
Keeling 1997) modelled the dynamics of measles.
Here, the patches are cities or large towns, and spatial coupling reflects traffic among towns. With 10
such identical cities, a very weak amount of coupling
(0.1% individuals moving) was shown to increase
the persistence of the disease overall. The reduction
in extinction rate provided by spatial localization of
interactions in large measure reflects the rescue effect
(Brown and Kodric-Brown 1977). The decorrelation
of dynamics among different sites permits some
populations to be large, even when others are quite
rare; the former can then provide immigrants which
boost numbers in the latter, preventing local extinctions. This effect tends to increase when spatial
localization is assumed (rather than weak global
mixing among patches), as well as when the model
explicitly considers birth, death, and movement at
the level of individuals (demographic stochasticity).
Both factors tend to decrease the correlation among
sites in population dynamics.
In the real world, spatial localization of interactions may make it more difficult for many
pathogens to persist. Phocine distemper in the harbour seal (Phoca vitulina) in the North Sea provides
79
a potential example. This species is distributed in
well-defined local populations, separated by
unsuitable habitat. Colonies can go extinct and then
become re-established. From the point of view of
the virus, each group of seals is a patch in a
metapopulation. Swinton et al. (1998) parameterized a model, so as to analyse conditions for persistence. They concluded that a very large
population, indeed one larger than the entire population of seals in the North Sea, was required to
maintain the disease. The reason is that within each
local population, there is a rapid fadeout of the disease, followed by a slow entry of new susceptibles
via birth. This suggests that even larger spatial
scales must be considered if one is to understand
the origin and maintenance of this disease.
A consideration of extinctions and patchy populations leads naturally to the theme of metapopulation perspectives on host–parasite dynamics. Often,
local disease dynamics seem to imply that extinction
is expected (e.g. due to ‘fade-out’), but persistence
actually occurs. Analyses of plant–pathogen interactions at landscape scales can reveal considerable
stochasticity, suggesting the importance of recurrent
colonization and extinction events (Burdon and
Thrall 2001). Often, host–pathogen systems exist in
ecosystems where there are other drivers that
determine local extinctions (e.g. episodic disturbances). In this case, metapopulation perspectives
should be particularly useful.
This observation suggests that the pattern of connectivity may be critical in governing the importance of parasites in ecosytems. In conservation
biology, for many years there has been a concern
with how fragmentation reduces connectivity and
thus may foster the erosion of biodiversity (ranging
from the loss of genetic diversity within species, to
extinctions of entire clades of extinction-prone
species). This in turn has led to considerable attention being given to the potential value of corridors
linking habitat patches. Hess (1994, 1996a,b)
pointed out that there was a dark dimension to corridors, namely that they might promote the spread
of infectious diseases, which could in turn reduce
the conservation value of the habitat patches themselves. He developed metapopulation models to
explore this idea. These models suggest that if a
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disease is highly contagious, and moderately
severe (in terms of enhanced local extinction risks),
it could become widespread in strongly connected
landscapes, thus increasing the probability that the
host would go extinct.
One metapopulation model considered by Hess
(1996a) has the following simple form:
dS/dt ⫽ mS(1⫺I⫺S)⫺eS ⫺ mpIS,
dI/dt ⫽ mI(1⫺I⫺S)⫺e′I ⫹ mpIS.
Here, S is the fraction of patches occupied by
disease-free populations, and I is the fraction
containing the disease. The fraction of patches that
are empty is 1⫺I⫺S. This model assumes that empty
patches are equally likely to be colonized from
either healthy or infected patches, and that crossinfection (scaled by p) can occur, leading to the conversion of healthy into infected patches. In the
absence of the disease, the model reduces to the
familiar Levins formulation, with an equilibrial
occupancy of S* ⫽ 1⫺e/m. It should be noted that
formally, this model is an example of ‘intraguild
predation’ (Holt and Polis 1997). Healthy and
infected patches both compete for empty patches,
and in addition healthy patches can be exploited by
infected patches. There is a general tendency for the
top predator to exclude the intermediate predator
in intraguild predation; in this model, the infection
can dominate the population if the extinction rate
of infected patches is not elevated too much.
A simpler version of the model is to assume that
infected patches can only infect healthy patches. In
this case, the model becomes identical to a special
case of a predator–prey metapopulation model considered in Holt (1997), where a model is sketched for
two host species occupying distinct habitats, but
sharing a parasite that both increases local extinction
rates and can colonize across habitats. Holt (1997)
demonstrates that indirect competitive exclusion can
occur in this system. The species which occupies the
rarer habitat is particularly vulnerable to exclusion.
5.7 Spatial dimensions of host–parasite
evolution
There is a rich and rapidly growing literature on the
implications of space for genetic and evolutionary
aspects of host–pathogen interactions (e.g. Hochberg
and Holt 2002, and references cited therein).
Although of considerable intrinsic interest, it should
be cautioned that many evolutionary studies may not
actually directly bear on ecosystem processes. If all
pathogens do is alter relative fitnesses of individuals
within host species, without any overall impact upon
population size, turnover, or stability, it is not clear
that these studies have direct implications for ecosystem processes. For instance, in theories of sexual
selection in which mate choice is based upon parasite
load, an assumption is often made of ‘soft selection’,
in which parasites and hosts reciprocally determine
fitnesses in each other, but parasites do not directly
affect host population size. The most useful class of
models for the purposes of ecosystem ecology are
those which simultaneously examine population
dynamics and evolutionary genetic processes, and in
particular those which elucidate the interplay of ecological and evolutionary phenomena. In the next few
paragraphs, we discuss some major themes in host–
parasite coevolutionary dynamics. Essentially none
of the literature we consider is directly concerned
with the ecosystem implication of these dynamics.
There is considerable evidence for spatial variability in adaptation in host–parasite systems
(a very useful review is by Dybdahl and Storfer
2003). Local adaptation may be defined as occurring
when the mean fitness of a population when measured in sympatry is greater than in allopatry
(Gandon and Michalakis 2002); operationally, one
can carry out a series of cross-population infectivity
studies, and assess relative performance of parasites and hosts, when paired with the population
they normally encounter, compared with ‘foreign’
populations. There is a remarkable variety of patterns that have been reported in empirical studies
of host–parasite coadaptation.
One popular theory of host–parasite coevolution
leads to the expectation that parasites should be
locally adapted to their hosts (with greater replication rates and prevalence in sympatric hosts, to
which they have evolved) than to allopatric hosts
(to which they have not evolved). This could arise
for instance because parasites often have large
effective population sizes and short generation
lengths, relative to their hosts, and so should be
T H E S PAT I A L D I M E N S I O N
able to track slow shifts in the genetic composition
of local host populations (Dybdahl and Lively 1998;
Lively 1999). There are some excellent examples of
local adaptation by parasites to their hosts (e.g.
Morand et al. 1996). Thrall and Burdon (2003), for
instance, show that virulent pathogens dominate in
host populations with resistant hosts, whereas avirulent pathogens characterize host populations
with more susceptible hosts.
But in other systems, exactly the opposite patterns
are found. For instance, Altizer (2001) examined
variation among geographical races of the Monarch
butterfly and its protozoan parasite Ophryocystis
elektroscirrha. The prevalence of this parasite varies
dramatically among populations, as does host resistance and parasite virulence. The migratory populations tend to have higher resistance and experience
lower virulence. The parasite is not in this case more
infectious to their native hosts, and indeed may be
more maladapted. Altizer proposes that this pattern
is due to selection being strong in the migratory population (where small parasite loads could translate to
large fitness disadvantages, due to the energetic
requirements of migration), and to correlated shifts
in the relative importance of horizontal and vertical
transmission routes. Another potential cause is that
migratory populations may experience more effective gene flow, and so tend to have the genetic variation needed to mount strong adaptive responses to
parasitism.
Theoretical studies of host–parasite coevolution
suggest that which patterns are observed depends
on a number of factors, and in particular on the relative rates of dispersal of the interacting species,
and the presence of spatial differences in patch
quality (Gandon et al. 1996; Nuismer et al. 1999,
2000; Gomulkiewicz et al. 2000; Gandon 2002).
Lively (1999) also notes that the pattern one
observes is likely to shift with time; because the systems are expected to be dynamic at both a local and
global level, local adaptation at any given site, for
either species, is likely to wax and wane with time.
As with analyses of spatial effects on host–parasite
ecology, it is useful to distinguish scenarios in
which space solely matters because interactions
and dispersal are localized, and those in which
there exists spatial heterogeneity in extrinsic
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environmental factors. Biotic and abiotic factors are
rarely uniform across a species’ range, and such
variation has implications for the strength and even
direction of selection (Thompson 1994, 1999).
Thompson (1994) refers to sites where each of a pair
of species has strong, reciprocal effects upon the
other’s fitness as coevolutionary ‘hotspots’.
Typically, for a variety of reasons such hotspots will
be embedded in landscapes with many coevolutionary ‘coldspots’, where just one species responds
to the other, or evolution is locally decoupled
(Thompson 1994, 1999). Environmental gradients in
climate or resource availability may for instance
account for spatial variance in the virulence of
parasitoids of Drosophila melanogaster (Kraiijeveld
and van Alphen 1995). Patterns of local adaptation
can be strongly influenced by the spatial mixture of
hot and cold spots (Gomulkiewicz et al. 2000).
The primary ecosystem driver of environmental
productivity in particular has been identified as a
factor that indirectly governs the strength of coevolution between hosts and pathogens (Hochberg and
van Baalen 1998; Hochberg and Holt 2002), leading to
the prediction that virulence should decline to lower
levels when productivity is lower. The mechanistic
reason for this is that in host–pathogen systems (as
for resource–consumer interactions in general), an
increase in local productivity indirectly increases the
abundance of the pathogen. This automatically
increases the strength of selection on the host via
selection to reduce attack rates. In the simple SI
model discussed above, note that as host intrinsic
growth rate increases (b–d), which should be facilitated by increased productivity, the relative number
of hosts that are infected, versus healthy, will
increase. This in turn implies that the strength of
selection on withstanding the infection (e.g. by
recovering) will increase, as gauged against potential costs of such defence for reproduction by healthy
hosts. In systems with top-down regulation of hosts
by parasites, increases in productivity also tend to
reduce the strength of density dependence. This
makes the relative advantage of defence against
parasitism increase, and so indirectly also increases
the likelihood of an evolutionary response.
Depending upon the details, these effects on the
host can in turn alter evolution in the parasite. In
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some (though not all) situations, selection on the
parasite to overcome host resistance will increase.
Moreover, if the increase in host productivity translates into greater parasite numbers, more genetic
variation should become available via mutation,
upon which selection can then act. Thus, high productivity sites should be coevolutionary ‘hotspots’.
Patterns of dispersal should also include coevolution between hosts and parasites. Complex patterns
of local maladaptation and adaptation may arise,
because of the mixing of traits among populations
that are pulled in different evolutionary directions
(Thompson et al. 2002). The idea that gene flow can
hamper local selection is a familiar, old idea in
evolutionary biology. A countervailing factor is that
gene flow permits an infusion of genetic variation,
providing the raw material for evolution by natural
selection (Gomulkiewicz et al. 1999; Holt et al. 2003).
The degree of local adaptation should strongly
depend on the magnitude of dispersal relative to the
strength of selection. It is an open question whether
mismatching, or matching, of coevolved traits is the
typical condition of natural systems.
Dispersal should interact with productivity. If
there is weak dispersal, then in effect sites with different conditions provide distinct, largely closed arenas for adaptive evolution. Moreover the only sites
where the species will be present will be those where
they can sustain viable populations. Small amounts
of dispersal in this case may mainly matter as providing avenues for the infusion of useful genetic variation; in any case, dispersal is not likely to create local
maladaptation, if it is sufficiently weak. Indeed, in
this case high immigration tends to corrode local
adaptation. However, if the population is unable to
persist without immigration (i.e. the habitat is a sink),
dispersal will tend to enhance the initial stages of
adaptation to the environment (Gomulkiewicz et al.
1999; Holt et al. 2003). Whether it does so may depend
upon the quantitative magnitude of mutational
effects upon fitness (Kawecki and Holt 2002), and the
impact of dispersal upon fitness (given intraspecific
density dependence, Gomulkiewicz et al. 1999). In
severe sinks, it may be difficult for evolutionary
responses to occur at all (Holt and Hochberg 2002). In
heterogeneous environments, dispersal is likely to be
asymmetric between environments varying in
productivity. Environments with low productivity
and population sizes are likely to be net recipients,
rather than sources, of immigrants. All else being
equal, these are also potentially sites where a host, or
pathogen, can be maladapted (Holt and Hochberg
2002; Nuismer et al. 2003).
5.8 Ecosystem drivers of host–parasite
interactions: from parasitism to
mutualism
Because parasites live intimately in the bodies of
their hosts, there is the potential for selection to
favour avirulence, or even the transformation of a
parasitic association into a mutualism. Different
environmental conditions can shift the balance
between mutualisms and antagonistic interactions
(e.g. Herre et al. 1999). Hochberg et al. (2000) explored
how this transition from negative to positive
interactions might be modulated by demographic
differences among locations. They found that
virulence tended to emerge most often in habitats
where host population growth was highest. The
reason for this was twofold. First, total host
numbers could be higher there, so if virulence was
associated with transmission, it could be selected.
Moreover, there was greater opportunity for crossinfection among strains, so that virulent strains
could replace avirulent strains within hosts.
Conversely, when host populations were unproductive, as in marginal habitats, avirulence and
mutualisms could be favoured.
This relationship between levels of productivity
and the shift between parasitism and mutualism
has potentially significant implications for ecosystem processes. Many mutualisms are associated
with resource acquisition (e.g. nitrogen fixation in
plants). If parasitic associations are labile, and tend
to evolve towards mutualism in unproductive
environments, this provides a kind of buffering in
terms of ecosystem productivity.
5.9 On the topic of maladaptation
One important implication of spatial flows is that
moderate (and at times severe) degrees of
maladaptation are to be expected. Thompson et al.
T H E S PAT I A L D I M E N S I O N
(2002) discuss in particular how geographical
structuring in coevolutionary systems can lead to a
substantial incidence of maladaptation.
There are several basic reasons to expect maladaptation in geographically structured coevolving
systems.
1 Change leads to evolutionary lags. When the
selective environment changes, there will usually
be an evolutionary lag before a focal species settles
into a new adaptive equilibrium. The length of time
of the lag depends upon a variety of factors, such as
the degree to which adaptation depends upon
standing variation available at the time of the environmental change, or instead upon novel variation
generated by mutation. Such lags are expected even
to changes in the physical environment. Host–
parasite interactions can exhibit dynamical instability
in the selective environments faced by one or both
species, either because of fluctuations in population
size, or because evolution in one species in effect
amounts to a deterioration in the environment for
the other species.
2 Gene flow perturbs local adaptation. If there are
fixed differences among populations, such differences could lead to differences in fixed local outcomes (Hochberg and Holt 2002). In this case,
movement among populations can displace species
from their local adaptive optima, because of the
interplay of gene flow and selection.
3 Gene flow provides adaptive genetic variation.
Adaptation by natural selection depends upon
genetic variation; the migrational input of variation
can permit one species to evolve more rapidly or
effectively than another. Mathematical models of
coevolution with migration at different rates for the
interacting species reveal an interesting pattern.
Gandon et al. (1996) predicted that if parasites
migrate much more than do hosts, the parasites
should be locally adapted. Conversely, if hosts
migrate more than do parasites, hosts may be better
adapted. The latter can arise for instance if the dispersing stage of the life history is different than the
one harbouring the parasite. Oppliger et al. (1999)
tested this prediction with a lacertid lizard (Gallotia
gallota) from the Canaries, and a haemogregarine
blood parasite. Juveniles appear to be parasite free,
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and are the life stage when dispersal occurs.
Cross-infection experiments revealed that parasites
performed better on hosts from allopatric populations, revealing that the parasites are maladapted
to the hosts with which they live.
4 Hosts and parasites have different spatial ranges.
In this case, different geographical arenas determine evolution for hosts and parasites. Nuismer
et al. (2003) have recently explored implications of
the general pattern that hosts and parasites do not
typically have completely congruent geographical
ranges. Their model suggests that spatial zones of
maladaptation in one or both species are to be
expected in spatially distributed host–parasite
systems.
As we noted earlier, at the ecosystem level, these
emergent patterns of adaptation and maladaptation
will be reflected in overall rates of death for hosts,
which in turn should alter the ecosystem fluxes
associated with particular host species. Spatial
dynamics could have an important and underappreciated impact on ecosystem processes,
mediated through the realized death rates of hosts
across spatially heterogeneous landscapes.
5.10 Concluding remarks
We have argued that the ecosystem implications of
host–pathogen interactions are likely to have
important spatial dimensions. The empirical examples we reviewed above suggest that there is often
substantial variation in host–pathogen interactions,
for instance because of nonconcordant geographical ranges, and differences among sites in the
degree of aggregation. If pathogens can regulate
host abundance and productivity, spatial variation in
the impact of such regulation can lead to corresponding spatial variation in biomass and productivity. The theoretical studies of host–pathogen
interactions in spatially distributed systems we
have reviewed reveal that in many situations,
patchiness and spatial heterogeneity can help stabilize otherwise unstable dynamics, and lead to some
sites with much heavier loads of parasites than can
be sustained by local dynamics alone. The spatial
localization of interactions between parasites and
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hosts can lead to systematic deviations from the
expectations of nonspatial theory (e.g. as in the
evolution of virulence, see above), and make it
likely that ecosystem area or volume is a critical
aspect of the persistence of host–pathogen systems.
Together with the potential for rapid evolution,
spatial localization can also lead to complex spatial
patterns of local adaptation and maladaptation in
these systems. All of these points bear on current
concerns about the implications of global change
for the viability of ecological systems.
Most components of global change involve a spatial dimension and this could result in parasitism
playing an especially important role via these spatial dimensions (see also Chapter 7). Increased fragmentation due to human activities can affect
dispersal of host and parasites, and thus influence
the persistence of their interactions at different
scales, as well as the emergence of new diseases.
Climate change should lead to geographic change in
species’ ranges and habitat productivity which, as
seen above, are critical for the dynamics of
host–parasite interactions. Finally, increasing rates
of introduction of species to foreign ecosystems can
also result in dramatic shifts in the role of parasitism,
either directly via the introduction of parasitic
species, but also more indirectly by the introduction
of potential hosts for parasites. The spatial dimension of the role of parasitism in ecosystems should
thus become even more relevant in future attempts
to understand and predict the ecological effects of
global change (see also Chapter 7).
CHAPTER 6
Parasitism and hostile environments
Richard C. Tinsley
Parasite transmission involves location of the host in an external
environment typically regarded as hostile (where parasite survival is
precluded) and the host is considered the safe ‘patch’. However, lethal factors
operate within the host, provoked by the parasite’s presence, and the
interaction represents a distinguishing feature of parasitism. The parasite’s
response to hostile conditions determines whether infection causes pathogenic
disease, coexists asymptomatically, or becomes eliminated. What is the
empirical evidence of parasite mortality within hosts? What circumstances
lead to the ultimate expression of a hostile environment—extinction?
6.1 Introduction
Parasites occur in the widest diversity of
environments: they are recorded not only in all the
inhabited regions of earth, but also within the environments created by the free-living organisms that
inhabit those regions. It is axiomatic that hosts represent favourable ‘patches’ on which parasite
growth and reproduction occur; the spaces between
these ‘patches’ may typically represent adverse
conditions where parasites, with an obligatory
need for the host, cannot survive. The difficulties
inherent in patch location are traditionally associated with the notorious fecundity of parasites.
However, the degree of hostility created by these
gaps between hosts is variable. In many life cycles,
the medium for transmission is generally not intrinsically hostile to ‘off-host’ stages. This is illustrated
by life cycles involving water-borne infection, especially in marine environments where osmotic and
other conditions create relatively little physiological stress. Often, the major losses of offspring are
determined by the limited lifespan of the transmission stage, governed by its fixed energy reserves, in
relation to availability of hosts. Life cycles where
parasites are ‘free-living’ in the external environment
School of Biological Sciences, University of Bristol, Bristol BS8
1UG, UK.
typically incorporate a dispersal stage that is not
equipped to exploit exogenous nutrients. So, the
strategy of mass production of energetically cheap
infection stages has low survival probability not
because of hazardous environmental conditions
but because of time. Where transmission stages
are quiescent eggs or protected larvae, then other
determinants such as frequency of encounters
with prospective hosts—always a key factor in
life cycle strategies—assume greater importance.
This, too, is the major influence in life cycles based
on the feeding activities of other organisms (intermediate hosts involved in food chains, arthropod
vectors that effect transfer through their bloodfeeding on successive hosts). In many cases,
the transferred stages occur exclusively within
environments created by hosts. For these, hostile
conditions are experienced through the body of
the host (such as temperature for parasites in
ectotherms) or are determined by the hazards to
survival faced by that host.
Parasite life inevitably involves an interaction
with adverse conditions, as is the case for free-living
organisms. These are influences that have a fundamental role in regulating animal populations. This
chapter begins with this broad remit but then
focuses specifically on elements of the environment
that are particular to parasitism, emphasizing the
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distinctive characteristic of this way of life—the
nature of the conditions encountered within
the host.
6.2 Adaptation to hostile environments:
abiotic factors
There are two types of adaptation to adverse
conditions. Capacity adaptation enables an organism to grow and reproduce whilst experiencing
conditions that would be regarded as extreme for a
majority of other species. Resistance adaptation
enables an organism to suspend normal activity
and survive environmental extremes until the
return of favourable conditions when growth and
development can resume (see reviews by Perry
1999; Wharton 1999, 2002).
There is extensive documentation of the adaptations of parasites to survive in environments that
may be judged—by a range of criteria—to be
extreme: representing conditions at the limits for the
survival of life when protein structures and cellular
functions should be damaged beyond repair. One of
the key survival mechanisms involves exclusion of
water that is, of course, a basic requirement of life
but whose physical properties create great vulnerability. Anhydrobiosis enables survival of almost
total loss of body water (with water content only
1–5%) (Perry 1999): metabolism is brought virtually
to a standstill with metabolic rate of desiccated
Ditylenchus dipsaci below 1/10,000 of that of
hydrated larvae (Wharton 2002). Many of the adaptations are linked. Thus, nematode stages that are
tolerant of desiccation, in anhydrobiosis, will also
survive low temperatures since there is no water to
freeze. There are also interactions with survival
mechanisms to osmotic and oxygen stress that may
operate simultaneously under natural conditions.
Nematodes in an anhydrobiotic state can survive
exposure to radiation and chemicals that would kill
a hydrated nematode (Wharton 2002). The records
are remarkable for demonstrating the ability of living organisms to tolerate the most extreme conditions (appropriate for survival during transport
through space!). Trichostrongyle nematode larvae
have been reported to remain infective after years of
storage in liquid nitrogen (–196 °C) (Halvorsen and
Bye 1999). Records for long-term survival during
desiccation include 32 years for the plant parasite
Anguina tritici (by Wharton 2002) and 39 years for
the free-living nematode Filenchus polyhypnus
(by McSorley 2003).
Wharton (1999) has reviewed the adaptive significance of cold tolerance in parasites, for which most
data concern nematodes and ticks. There is little
information for other parasite groups. Parasites of
endotherms are protected by the behavioural
responses and thermoregulation of their hosts.
However, parasites of ectotherms may be exposed
to lethal low temperatures within their hosts. For
amphibians and reptiles that tolerate subzero temperatures, their nematodes are also subjected to
freezing. Experimental studies on Wetanema sp., a
parasite of a New Zealand insect, the alpine weta,
show that this nematode can survive freezing
to – 61 °C within its host (Wharton 2002). So, the
survival mechanisms of the host may intensify
selection of corresponding adaptations by parasites.
Nematodes may also survive freezing in the
carcasses of their hosts; this is a valuable trait for
parasites such as Trichinella nativa transmitted to
scavengers in Arctic environments (see below).
In general, the survival mechanisms are not
special to parasites, they are found also across a
series of free-living invertebrate groups (including
rotifers, tardigrades, and nematodes), and represent adaptations to a range of unstable, fluctuating
environments. Nevertheless, the survival strategies
are important for parasites in providing the means
of ‘patch location’ where the spaces between
patches are exceptionally hostile (as in the Arctic
environments considered below) and where timing
to exploit availability of patches is crucial to life
cycle success.
In nature, adaptations to environmental constraints may involve complex interactions in which
timing is a key factor, enabling synchrony of
development of infective stages with favourable
environmental conditions, including host availability (see Wharton 2002). In Nematodirus battus,
autumn conditions induce eggs to enter diapause;
chilling overwinter prior to a temperature increase
in spring is required to stimulate mass hatching of
larvae, and this coincides with grazing by the new
HOSTILE ENVIRONMENTS
cohort of lambs. Trichostrongyle larvae may survive winter conditions as infective 3rd stage larvae
on pasture but, in some species, larvae acquired in
autumn may become arrested within the host
(hypobiosis) and delay development to adults
until spring. Deposition of eggs onto pasture and
development of infective larvae then coincides with
the availability of new-born susceptible hosts.
This pattern may be a response by the preceding
free-living stages exposed to low temperatures in
autumn that trigger arrest following host invasion,
but the host’s immune response has also been
implicated (Wharton 2002). In these cases, survival
of specific hostile factors by parasites becomes part
of a wider strategy for exploitation of hosts.
6.3 Adaptation to hostile environments:
ecosystems
6.3.1 The deep sea
The deep sea may sometimes be overlooked in
assessing the extent of parasite infection; however,
over half the earth’s surface is covered by water
with a depth of over 3200 m, and there is enormous
faunal diversity (Bray et al. 1999). Bray et al. emphasized that, on the basis of its total volume,
the abyssal ocean and its inhabitants represent the
most typical environment of this planet. From the
perspective of life near to sea level, the constraints
are exceptional, including physical conditions such
as high pressure, low temperature, and lack of
light. Bray et al. (1999) listed the physiological
effects of high pressure on living organisms, noting
that animal and bacterial life occurs even at pressures of 1100 atmospheres. For parasites, there are
additional factors concerning spatial distribution
of hosts, the nature of food chains and the characteristic of pelagic animals that there is no ‘platform’
on which transmission can occur.
In a review of digenean parasites of teleost fishes
in the deep sea (defined as below 200 m depth),
Bray et al. (1999) recorded over 200 species from
18 families. Certain of these appear to be adapted
to a very wide depth (and hence pressure) range:
for instance, Gonocerca phycidis occurs from 200 to
4850 m. Prevalence of infection at depths below
87
4000 m seems remarkably high, ranging from over
30% to nearly 60%. Bray et al. (1999) noted the
relatively great diversity and density of potential
intermediate hosts for digenean life cycles in
continental slope samples at depths of 1500–2500 m:
one study reported 798 species in a 21 m2 surface
area including 106 mollusc species, 385 annelid
species, and 185 arthropod species. Certainly there
is no suggestion of a restricted fauna ‘struggling’ to
survive in limiting conditions.
Hydrothermal vents on the ocean floor represent
a further amplification of the constraints of the
deep sea making this one of the planet’s most
extreme environments (Lee 2003): there may be
extreme temperature variation (from 400 °C within
vents to 1–2 °C in surrounding areas) and high concentrations of specific chemical elements (Rothschild
and Mancinelli 2001). Buron and Morand (2004)
documented 126 species of parasites found at
depths of 1000 m or below, not associated with
hydrothermal vents. Digeneans and copepods
represented 65% of this total; cestodes, digeneans,
and acanthocephalans were recorded down to
about 5000 m and copepods to 7000 m. In contrast,
few parasites are known to occur in hosts associated with deep-sea vents: Buron and Morand (2004)
reported records of a leech (at 2500 m), a nematode
(at 3600 m) and several species of digeneans
(2600–3600 m), acanthocephalans (2300–2600 m),
and parasitic copepods (2250–2600 m), but these
scattered data probably represent only the beginnings of parasitological documentation. There is
a relatively low diversity of potential host species at
vents, but their high population densities might
favour exploitation by co-adapted parasites (Buron
and Morand 2004). The records give little idea of
specialist adaptation to these conditions.
6.3.2 Deserts
Desert ecosystems exemplify environmental conditions that are hostile for parasite life cycles. Indeed,
deserts provide some of the harshest tests of life
in general, defined by extremes of water deficit
(a combination of low precipitation and high
evaporation) and temperature (above and below
survival thresholds for most living organisms). For
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prolonged periods of each year, the harshest
environmental conditions may preclude activity by
most desert organisms, and their survival typically
involves corresponding periods of dormancy. As a
consequence, deserts are characterized by very low
food availability. However, in most of the world’s
deserts, especially the hot deserts, periodic weather
patterns produce rainstorms that create favourable
conditions for life. It is well documented that rainfall in deserts may be followed by a sudden pulse of
activity, both of plants and animals. The organisms
that exploit these conditions generally have exceptional abilities to tolerate or avoid drought, temperature fluctuations, and prolonged starvation.
In addition, their suite of adaptations typically
includes a quick response to unpredictable opportunities and a lifestyle geared to rapid growth,
reproduction, and accumulation of reserves during
favourable periods that then enables survival
through the next period of hostile conditions
(Tinsley 1999a,b).
Given the constraints on life in general, it might
be predicted that desert ecosystems would impose
a severe challenge for host-to-host transmission.
Free-living stages, released into the external
environment, may experience hostile conditions
directly (especially extremes of temperature and
desiccation). For helminths with indirect life cycles,
there may be limited opportunities during the brief
activity season for infective stages to enter and
complete development within an intermediate host
and then to be transferred to another definitive
host. Life cycles employing arthropod intermediate
hosts may benefit from their abundance during
favourable conditions; however, transmission may
have the disadvantage of low probability that intermediate hosts, carrying parasites at an infective
developmental stage, are ingested by appropriate
final hosts. In deserts where there is, typically, a
relatively short activity season, indirect life cycles
must rely on rapid development of successive
stages (for within-season transmission) or extended
survival in intermediate hosts (permitting infection
in one year and onward transmission in the next).
A strategy of between-season transfer is vulnerable
to intermediate host mortality, both by parasiteinduced pathology and by environmental effects
during the long period of hostile conditions. Some
parasite life cycles are virtually precluded by failure of intermediate host groups to tolerate desert
conditions: thus, digeneans are typically rare or
absent in desert ecosystems because of the absence
of snails. These factors contribute to a low species
diversity of parasites in desert ecosystems, a feature
characteristic of extreme environments in general
(see Combes and Morand 1999).
Paradoxically, there is comprehensive information
for life cycle adaptations in a host–parasite system
that should not exist in a hot desert ecosystem
(Fig. 6.1). Pseudodiplorchis americanus belongs to a
platyhelminth group, the Monogenea, that principally comprises parasites of fishes. Typically, these
possess a ciliated, swimming infective larva, lack
resistant stages, and have no tolerance of desiccation.
Host-to-host transfer in the direct life cycle occurs
exclusively in water. The host is an amphibian, an
equally improbable inhabitant of hot deserts, with
the typical life history requirement that breeding
occurs in water. In the southwestern deserts of
North America, the toad, Scaphiopus couchii, spends
the major part of each year dormant underground
to escape the harshest desert conditions. Emergence
is triggered by torrential rainfall, normally beginning
in early July. The toads breed in newly created
ephemeral pools and are then active on the desert
surface when they feed on desert invertebrates and
accumulate energy reserves. By early September,
increasing drought and declining temperatures
force a return to dormancy. This annual schedule, of
about 2 months activity and 10 months inactivity, is
actually more restricted. S. couchii is nocturnal, so
activity is confined to the period between 21.00 h
(dusk) and 04.00 h (dawn). Foraging occurs only
when the desert surface is relatively damp, after
rainfall, and is probably limited to fewer than 20
nights each year (Tinsley 1999b). Spawning typically occurs on only a single night each year (sometimes two or three nights for a given population in
a ‘wet’ summer), and toads are otherwise entirely
terrestrial. These strict constraints on host ecology
are reflected in a very limited parasite fauna:
S. couchii is infected by only five species of helminths
and, for four of these, prevalence is less than 5%
with very low worm burdens (Tinsley 1990a).
HOSTILE ENVIRONMENTS
Control of parasite
oviposition by host
cue linked with
sexual activity
Control of invasion duration
by host behaviour
(hence initial recruitment)
89
Maximum temperature 35 °C
Control of initial establishment
(hence pulmonary infection levels,
pathology etc)
Exposure to external
environmental conditions
Max 7 h
Exposure at air/water
interface to surfactants,
immune factors in
respiratory tract
Control of transmission
opportunities by
(a) external environmental
conditions (rainfall)
(b) host behaviour
Control of parasite
developmental rate,
reproductive preparation
and survival by external
temperature via
(a) direct rate limiting
effects,
(b) indirect effects
operating through
a temperature-dependent
immune response
(hence control of worm
burden, pathogenic effects,
infrapopulation output
of infective stages)
3–4 weeks
OCT
JAN
Exposure to increasing
osmotic concentrations
of urine in urinary bladder,
putative immune attrition
48 weeks
Exposure to digestive
enzymes, pH variation, bile
anaerobic conditions in gut
Control of parasite
migration by host cue
5 min
linked with activity;
this, in turn, controlled
by ext. environmental
factors (rainfall, temperature)
(hence control of size
of reproducing parasite
infrapopulation)
minimum temperature <7 °C
Figure 6.1 Summary of the constraints operating during successive phases of the life cycle of Pseudodiplorchis americanus.
Notes: Inner ring of annotations lists the variations in environmental conditions experienced by the parasite; outermost annotations identify the accompanying
environmental controls on parasite biology. Central diagram correlates parasite life cycle events with the annual activity cycle of the host, S. couchii:
transmission occurs during host spawning ( ); juvenile development and internal migration during host feeding ( ); maturation and accumulation of embryos
in utero during host hibernation ( ). The cycle follows one cohort of parasites, but adult worms ( ) producing infective stages ( ) in one season’s transmission
may also survive to reproduce in the next year(s). Additionally, juveniles failing to migrate may remain in the respiratory tract throughout hibernation and then
migrate to the bladder when the host becomes active. (Reproduced from Tinsley 1999b).
Field data show that, during exposure to external environmental conditions (the period of host-to-host transmission), about 30% of infective larvae
succeed in invading a host. However, between initial establishment and the opportunity for transmission, only 3% of worms survive, reflecting the hostility of
the internal host environment (see text).
Paradoxically, the helminth that is most common
in this desert host is the monogenean that relies
on water for transmission. Patent infections of
P. americanus occur in around 50% of S. couchii
with a mean intensity of around 6 worms/host.
Alongside these, post-infection juvenile parasites
have a prevalence of 100% and a mean intensity
typically about 100 worms/host (Tinsley 1999b).
The knowledge of host ecology allows these
infection levels to be linked precisely to the period
of transmission: invasion by ciliated oncomiracidia
is possible only when S. couchii enters water to
spawn, usually a maximum of 7 h but even in ‘wet’
summers always less than 24 h in the entire year.
The effectiveness of this transmission period, probably briefer than for any other platyhelminth, is
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PA R A S I T I S M A N D E C O S YS T E M S
attributable to a series of exceptional specializations
of parasite reproductive biology.
Clearly, deposition into the external environment
of recently-assembled egg capsules (as in the majority of monogeneans and digeneans) could not meet
the demands of this desert system. However, there
are many platyhelminth examples in which eggs
are retained and complete development in utero,
hatching usually just after release into the external
environment. This strategy, reviewed by Tinsley
(1983), avoids the hazards of development away
from the host and eliminates the time delay
between oviposition and invasion. In a diverse
range of circumstances in platyhelminth life cycles,
release of immediately infective offspring permits
the transmission process to be concentrated in both
time and space to exploit periods of host vulnerability (Tinsley 1990b). In P. americanus, the key
reproductive adaptation is a long uterus in which
encapsulated embryos develop to the point of
hatching and are then stored for mass release during the once-per-year transmission opportunity
(Fig. 6.1).
The adaptations for production of infective
stages by P. americanus have no close parallels elsewhere in the Platyhelminthes. The egg capsule is
built up from around 12 layers of membranes
derived from the uterus wall, forming a thin elastic
‘shell’ which is able to expand as the larva inside it
develops. Nutrients are supplied directly to the
embryo via a system of cytoplasmic processes connecting the lining of the egg capsule to the tegument of the developing larva. This placenta-like
system ensures that oncomiracidia are maintained
in a continuous state of readiness for discharge and
that, despite the unpredictable timing of transmission, they have maximum energy reserves for host
invasion (Cable and Tinsley 1991). A suite of other
adaptations complements the demands of the life
cycle (reviewed by Tinsley 1999b, 2004).
Alongside these parasite adaptations for instantaneous transmission in a desert environment, the
key determinant of the numerical success of invasion is host behaviour. The ‘explosive’ breeding of
S. couchii ensures that, when the once-per-year
opportunity arises, maximum numbers of potential
hosts are concentrated together in confined bodies
of water. Samples of mating populations taken at
intervals during the 7 h exposure show a more or
less exponential increase in infection levels (Tinsley
1999b). However, host behaviour also regulates the
overall input of larvae: the mating toads leave
water at dawn and this abruptly terminates the
invasion episode. A series of field studies based on
the Pseudodiplorchis/Scaphiopus system in Arizona
have shown a consistent ‘saturation’ of the host
population, with all individuals infected at the end
of each transmission season (reviewed by Tinsley
1999b).
Viewed critically, while this life cycle involves
adaptations in a host–parasite system found in a
very hostile environment, the process of host-tohost transfer is actually accomplished remarkably
easily. The precise targeting of mass release of
infective larvae into water with high densities
of host results in a very efficient transmission.
Tinsley (1999b) calculated that larvae have a probability of about 0.3 of successfully invading a host, a
success rate probably higher than for any other
platyhelminth. This process depends absolutely on
an infallible trigger factor that synchronizes larval
release with the brief periods of host vulnerability,
but the parasite’s excursion into the external
environment does not involve exposure to ‘hostile’
conditions (Fig. 6.1).
Regarding the effects of harsh desert conditions
during the other 364 days each year, the most important constraint imposed by the external environment
involves low temperatures rather than high. Winters
in the Sonoran Desert are cold: soil surface temperatures (weekly minima) are below freezing from
November to March. In the buffered environment
15 cm below the soil surface, temperatures are below
10 °C for 4 months and below 15 °C for 6–7 months
each year. Laboratory experiments by Tocque and
Tinsley (1991a) showed that parasite development
and reproduction are strongly temperaturedependent and are virtually halted at 16 °C, that is,
from October to April. So, although P. americanus has
one year for preparation from one transmission
opportunity to the next, optimum temperatures for
reproductive preparation (25 °C) occur for only
about 12 weeks each year and this allows 1st year
worms to make only a minor contribution to
HOSTILE ENVIRONMENTS
transmission. Older worms, having completed
initial body development, can produce progressively greater numbers of infective stages during
this restricted period, but numbers of parasites
decline significantly after 2 years and survival to
4 years post-infection is exceptional (Tinsley 1999b).
These interactions, including time, temperature, and
parasite survivorship, are responsible for limiting
mean lifetime reproductive output to only around
150 offspring per worm (Tocque and Tinsley 1991b).
6.3.3 Arctic ecosystems
Svalbard reindeer in the high arctic experience a
long cold winter, with the upper metre of ground
frozen and snow-covered from October to the end
of May or early June. Halvorsen and Bye (1999)
showed that the nematode species of Svalbard
reindeer are not specialists of Arctic environments
but instead are generalists, widely distributed
outside the Arctic, that are capable of sustaining
populations under relatively more extreme environmental conditions. It could be predicted that
transmission might be restricted to the period of
more favourable conditions, in summer. However,
Halvorsen et al. (1999) demonstrated that infection
occurs throughout the year, even in the most severe
conditions of mid-winter. These authors cited
previous studies where larvae remained infective on
herbage from autumn until the following summer.
Indeed, larvae of the nematodes Marshallagia
marshalli and Teladorsagia circumcincta survive
storage in liquid nitrogen (see above and Halvorsen
and Bye 1999).
An illustration of parasite establishment de novo
in a hostile environment is provided by the records
of Henttonen et al. (2001) of introduction of
Echinococcus multilocularis into Svalbard. Arctic
foxes, final host of E. multilocularis, range widely
across the pack ice between Svalbard and the
Siberian mainland where infection is present.
However, the parasite could not have become
established naturally on Svalbard because of the
absence of native rodents. The sibling vole,
Microtus rossiaemeridionalis, was introduced accidentally by humans in the early to mid-twentieth
century and is assumed to have acquired infection
91
from migrating arctic foxes (Henttonen et al. 2001).
In this severe environment, in which major fluctuations in vole populations are driven by winter
mortality, E. multilocularis is maintained in a very
simple cycle with only a single species of both final
and intermediate hosts. Prevalence in the intermediate host approaches 100% in older animals and
field data suggest that transmission occurs
throughout the year, even in winter (Henttonen
et al. 2001).
Trichinella nativa is superbly adapted to Arctic
ecosystems. The carnivore/scavenger transmission
route means that there are no free-living stages
passed into the external environment to encounter
hostile abiotic conditions directly. However, this
feature—a key adaptation in the Arctic—is also
found in all other ecosystems exploited by Trichinella
species, including mesic and tropical environments.
Kapel et al. (1999) found that larvae of T. nativa
from Arctic foxes (from Greenland and Svalbard)
remained infective for 4 years at –18 °C and suggested that freeze resistance is positively correlated
with geographical latitude. Survival ability also
varies in different host species: parasite isolates
from arctic hosts (polar bear and wolf) survived
many months at –15 to –20 °C but failed to survive
relatively short exposure (5–7 days) at –10 to –15 °C
in mice. Kapel et al. (1999) attributed differences in
freeze tolerance to dissimilar development of the
nurse cell–larva complex in different host tissues.
6.3.4 Ecosystems showing extreme variation
In considering the adaptations of parasites to
hostile conditions, it is instructive to examine the
success of parasites that thrive in a wide diversity
of environments. Fasciola hepatica is considered to
be native to Europe and it represents a remarkable
test of adaptation that fascioliasis currently creates
a public health problem in 51 countries on five
continents (Mas-Coma et al. 2001). Indeed, it has
the widest latitudinal, longitudinal and altitudinal
distribution known amongst vector-borne diseases.
Thus, hyperendemic human infection extends from
below sea level (in Iran) to altitudes exceeding
4000 m (in Venezuela, Peru, and Bolivia) (Mas-Coma
et al. 2003).
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PA R A S I T I S M A N D E C O S YS T E M S
The epidemiology of F. hepatica is apparently
strictly constrained by temperature-dependency of
the life cycle stages external to the mammalian host.
Development of both eggs and intramolluscan
stages ceases below 9 °C, so transmission is virtually
arrested for a major part of each year in temperate
climates. In the United Kingdom, this period
extends from October to May. Even with this
6-month limitation, life cycle efficiency permits
epidemics with high mortality to develop within a
single season in cool wet conditions in the British
Isles (Ollerenshaw 1974). Nevertheless, year-round
low temperatures would be expected to preclude life
cycle completion. Mas-Coma et al. (2003) provided
summary data for the temperature regimes at sites in
South America where fascioliasis causes human
disease at very high altitude. At a series of localities
in the Andes, monthly and annual temperatures
exhibit means consistently below the 9 °C minimum
for free-living and intra-molluscan stages. Thus,
at Mérida, Venezuela, mean annual temperature
is only 6.1 °C with monthly range from 5.0 °C (in
January) to 6.6 °C (in September); at Cotopaxi,
Ecuador, mean annual temperature is 7.8 °C,
monthly range 7.4 °C (June and July) to 8.1 °C
(March); at Puno, Peru, mean annual temperature is
7.0 °C, monthly range 3.6 °C (July) to 8.8 °C
(December). These data suggest that F. hepatica
should not survive. Mas-Coma et al. measured life
cycle characteristics of Northern Bolivian high altitude isolates maintained under controlled environmental conditions and compared these with
equivalent data for European isolates. At the
selected temperature, 20 °C, there were no rate differences in developmental periods and infectivity.
This could indicate that there has been no significant
evolution, within the past few hundred years, of the
major parameters that might permit parasite development at temperatures below the limits for
European isolates. However, critically, there are no
data for the developmental biology of parasites
exposed to field conditions in these extreme environments. Thus, while temperatures remain consistently below 9 °C throughout the year, as represented
by monthly means, there is no information on effects
of regular short periods of higher temperatures such
as would occur daily around mid-day. Diurnal
fluctuations may allow development to proceed in
pulses: the gradual accumulation of these increments could permit survival at average temperatures far below recognized minima. Diurnal
temperature variation may be more pronounced in
the very shallow water typical of wet pasture where
F. hepatica transmission is so effective; indeed, parasite stages within the intermediate host may benefit
additionally from heat absorption by snails exposed
to sunshine above the water surface.
It is possible that the temperature constraints on
parasites infecting fish may be more predictable:
diurnal temperature fluctuations should have
limited influence in relatively deep water. So,
for the salmonid parasite, Discocotyle sagittata, the
inhibitory effect of environmental temperatures
below 10 °C, predicted by laboratory studies
(Gannicott and Tinsley 1998), is likely to be more
directly relevant to transmission patterns in nature.
A series of other systems have well-documented
temperature thresholds that determine inhibition of
parasite transmission for a significant part of each
year, as in P. americanus where, paradoxically for a
hot desert, winter temperatures represent the major
constraint on life cycle preparation (Tinsley 1999b).
For Ascaris suum, egg development ceases below
15 °C (Larsen and Roepstorff 1999). These
conditions cannot be considered ‘hostile’, yet they
actually have the most serious effect on parasite
population dynamics by precluding transmission.
6.4 Hostile environments created by
parasites
6.4.1 Competition
Hostile conditions for parasites within hosts may
also be created by other parasites. One of the most
violent interactions is demonstrated by echinostome
rediae that feed upon larval stages of other digeneans within the tissues of mollusc intermediate
hosts (for this and other competitive interactions,
see Esch et al. 2001).
Intraspecific competition has been shown to
affect a range of parasite life history parameters
including pre-patent period, egg production rate,
and life cycle span, all indicative of suboptimal
HOSTILE ENVIRONMENTS
conditions. For measures such as reproductive
output, it is rare to be able to establish how these
constraints affect individuals within parasite
infrapopulations: most data relate to mean rates of
output averaged across the total worm burden
within a given host. However, the reproductive
specializations of P. americanus, involving retention
of an entire year’s offspring production in utero,
provide this detailed insight. Tocque and Tinsley
(1991b) recorded a significant density-dependent
reduction in the per capita rate of reproduction and,
in particular, demonstrated unequal effects on individual worms: the majority of parasites produced
offspring at reduced rate as density increased, but a
few worms retained high rates of production even
in large burdens. These intraspecific effects may
have a significant impact on parasite population
regulation, but hostile interactions are illustrated
more dramatically by interspecific competition.
Studies on the reproductive biology of
Protopolystoma species, parasites of the urinary
bladder of Xenopus species in Africa (reviewed
by Tinsley 2004), illustrate a series of negative
interactions in mixed species infections.
Reproductive interference has been demonstrated
in concurrent infections of P. fissilis and P. ramulosus
in X. fraseri in central Africa. Viability of eggs
produced from two-species infections was significantly less than that from single species infections,
suggesting genetic incompatibility following interspecific cross-fertilisation (Jackson and Tinsley
1998a). In another two-species combination,
antagonistic interactions between P. fissilis and
P. simplicis in X. wittei result in the absence of
concurrent patent infections in the same host
individual: expulsion of established infections of
one species coincided with arrival of the second
species in the bladder habitat (Jackson et al. 1998).
This mutual exclusion would avoid the reproductive wastage (and potential resource competition)
that accompanies the two-species infections found
in X. fraseri (above). Strict host specificity is
normally observed in polystomatid monogeneans,
including Protopolystoma where single parasite
species are generally restricted to single species
of Xenopus (Tinsley and Jackson 1998, 2002).
However, different Xenopus species frequently occur
93
in sympatry (see Tinsley et al. 1996) and might
be expected to experience accidental invasion by
foreign Protopolystoma species. Jackson and Tinsley
(1998b, 2003a) showed that infective larvae do
not discriminate between normal (compatible) and
non-normal (incompatible) Xenopus species but,
following invasion, failed to survive in an inappropriate host species. Nevertheless, in experimental
infections of P. xenopodis (specific to X. laevis) and
P. orientalis (specific to X. muelleri), abortive invasion
of an incompatible Xenopus species induced resistance to subsequent infection by the natural parasite
species. Thus, in the absence of effective host species
discrimination, two negative effects of the host–
parasite interactions could be envisaged. First,
accidental cross-infection by heterospecific larvae
may induce cross-resistance, reducing future reproducing populations of the host-specific parasite
species. Second, incompatible hosts may represent
a ‘trap’ for infective larvae of parasites specific to
other host species, reducing transmission efficiency
(Tinsley and Jackson 2002: Jackson and Tinsley 2003a)
(Fig. 6.2). These negative effects are avoided in cases
where parasite specificity is determined by precise
host species recognition by infective stages.
Comprehensive evidence of competitive interactions comes from very elegant field and experimental studies of schistosomes by Southgate,
Tchuem Tchuenté, Jourdane, and colleagues. Male
and female schistosomes locate one another in the
hepatic portal system of the definitive host and
form pairs as a prelude to maturation and egg
laying. There are no barriers to interspecific pairing
and this can lead to hybridization between closely
related species. Experiments involving sequential
infections of two different schistosome species have
revealed a world in which usurping males can
pull females away from their established mate and
pair with them. Hostile interactions may also be
mediated via the host’s immune response: an initial
infection may induce resistance that reduces
survival of invading worms from subsequent exposure. This immunity, important in single species
infections, also confers protection in experimental
two-species interactions. Among several potential
advantages (discussed by Cosgrove and Southgate
2002), one effect of this heterologous immunity is
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PA R A S I T I S M A N D E C O S YS T E M S
Table 6.1 Survival of Protopolystoma
(A) Hosts in which parasites survive and reproduce
In single species infections of hosts, parasites establish, develop to maturity, and contribute to onward transmission. But
♦
Survival to reproduce is influenced by compatibility (host ⫻ parasite genotype interactions, ‘strain’ differences). For P. xenopodis in X. laevis
(under standard conditions of experimental exposure, in full-sib, naïve hosts) prevalence at patency varies from 15% to 70% (Jackson and
Tinsley 2003b). Adult burdens are generally 1–2 (max 6) worms/host (Tinsley, 1995). Following successful establishment, parasite mortality
before first reproduction is >95% (Jackson and Tinsley 2003c).
♦
In successful adult infrapopulations, in primary infections, reproductive performance shows wide variation, attributable principally to host x
parasite interactions:
(a) Pre-patent period: median 9 weeks, max 19 weeks;
(b) Rates of egg production/host: range of max output 6–66 e/h/d;
(c) Reproductive lifespan, 1–27 months (Jackson and Tinsley 2001).
♦
In secondary infections, survival is reduced (see C) and in surviving adult infrapopulations reproductive performance is significantly depressed
in comparison with primary infections in the same hosts:
(a) Pre-patent period: median 21 weeks, max 28 weeks;
(b) Rates of egg production/host, max output 6–13 e/h/d;
(c) Reproductive lifespan, max 10 months (Jackson and Tinsley 2001).
(B) Hosts in which negative parasite–parasite interactions affect reproduction
♦
♦
♦
Reproductive output is affected by intraspecific density-dependent reduction in egg production (Tinsley 2004).
In some combinations, two species infections may co-occur in the same host, but reproductive interference leads to reduced egg viability (failure
of interspecies cross-fertilization?) (Jackson and Tinsley 1998a).
Prior abortive infection by heterospecific larvae results in reduced egg production by the normal species subsequently establishing in this host
environment (Jackson and Tinsley 2003a).
(C) Hosts in which parasite survival is blocked
♦
♦
♦
♦
♦
Converse of A above, in primary infections of normal host species, 30–85% of worm burdens are eliminated before reproduction (zero survival to
patency) (Jackson and Tinsley 2003b).
In secondary infections of normal host species, acquired immunity eliminates 85% of worm burdens (compared with failure of 6% of primary
infections (Jackson and Tinsley 2001).
All parasites invading a non-normal host species are killed in early development (Jackson and Tinsley 1998b, 2003b).
Parasites invading a normal host species that has previously experienced an abortive heterospecific infection show reduced survival (heterologous
immunity) (Jackson and Tinsley 2003a).
Parasites successfully established may be displaced/eliminated by the arrival of a second species in the same infection site (Jackson, Tinsley, and
Hinkel 1998).
(D) External environmental factors affecting parasite reproduction and survival
♦
♦
Increased temperature accelerates developmental and reproductive rates but survival is significantly reduced leading to lower prevalence and
intensity (see Fig. 6.5) (Jackson and Tinsley 2002).
Low temperatures permit increased parasite survival in hosts with suppressed immunity, but reproductive contribution is delayed: prepatent period
is extended (see Fig. 6.5) (Jackson and Tinsley 2002), and reproductive output reduced (Tinsley and Jackson 2002).
(E) Host population factors affecting parasite population biology
♦ Resistance
non-normal host species, and
normal host species with acquired immunity from normal species infection, and
normal host species with experience of non-normal parasite species
represent a trap for infective stages: these show no discrimination at the point of invasion but are killed during juvenile development.
Continued overleaf
HOSTILE ENVIRONMENTS
95
Table 6.1 Continued
♦
Susceptibility
Host reproduction generates cohorts of naïve individuals that ‘flood’ the population with susceptible targets for invasion (but, parasite mortality
between invasion and first reproduction is still >95% in primary infection of juvenile hosts, and even the youngest host age groups can develop
strong acquired immunity (Jackson and Tinsley 2003a)). However, primary infections in these young cohorts support a reproducing parasite
population that will contribute to transmission for up to 2 years during which further host cohorts are normally generated.
♦
Host survivorship
Factors that prejudice host survival also affect parasite survival and reproduction, including parasite-induced pathology. Protopolystoma infections
are strongly regulated but repeated infection of juveniles in the kidneys may be pathogenic (Tinsley and Jackson 2002). Other parasite
species, including the nematode Pseudocapillaroides xenopodis, may cause host mortality and prejudice concurrent Protopolystoma infection
(Tinsley 1995).
Notes: Experimental data, above, are based on exposures of Xenopus laevis (naïve, full-siblings) to Protopolystoma xenopodis under standard conditions;
interspecfic data based on P. fissilis, P. ramulosus, P. simplicis, P. orientalis (see references cited).
A. Hosts in which parasites survive and reproduce
B. Hosts in which negative parasite–parasite interactions affect reproduction
C. Hosts in which parasite survival is blocked
D. External environmental factors affecting parasite reproduction and survival
E. Host population factors affecting parasite population biology
Figure 6.2 Confrontation between species of Protopolystoma and hosts Xenopus spp. leads to successful invasion: consistently in laboratory
exposures ~30% of each infection dose establishes up to 1 week p.i. (There is no host species discrimination by infective larvae.) However,
subsequent survival is influenced by a complex of host effects, past experience of infection, parasite interactions, and biotic factors. The reactive
environment is made more or less hostile by increased or decreased temperature respectively.
Note: The outcome of infection of different categories of hosts and interacting factors is listed in Table 6.1 (opposite).
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PA R A S I T I S M A N D E C O S YS T E M S
to create an interspecies reproductive isolating
mechanism (as in the Protopolystoma species, above).
These case studies demonstrate that the environment inhabited by parasites may acquire hostile
characteristics because of co-infections and this may
be moderated, in part, via the immune response.
6.5 Hostile environments created
by hosts
are restrained in gut contents for some hours, the
store of vesicles is eventually exhausted, the tegument disintegrates and the worms die. However,
movement (by looping locomotion) is rapid, and
migration along 80–100 mm of gut typically takes
only 5 min (Cable and Tinsley 1992). The nature of
the secretions and the cue for their release have not
been determined (Tinsley 1999b).
6.5.1 The host gut
6.5.2 Man-made hostile environments:
chemotherapeutic drugs
The vertebrate alimentary tract, especially stomach
and intestine, constitutes a very hostile environment for parasites. Function is specifically designed
to reduce complex biological molecules into small
monomeric components. It has long been an
assumption that gastrointestinal parasites must
inhibit host enzymes. In the case of cestodes, for
which the interface exposed to host digestion is
also the absorptive surface of the parasite, specific
protective mechanisms have been determined by
Pappas and Uglem (1990). Hymenolepis diminuta
liberates an inhibitor of the proteolytic enzymes in
the intestinal contents of its rat host. In addition,
the tapeworm excretes organic acids produced
by anaerobic metabolism that regulate its
micro-environment to about pH 5.0, at which
level trypsin activity is inhibited (Uglem and Just
1983). This ability to modify the immediate environment may be important in the alkaline posterior
of the small intestine and where tapeworms are
not of sufficient mass (because of small size or
numbers) to acidify the bulk-phase of the intestine
(Pappas and Uglem 1990).
Protection from digestive attack will have been an
early evolutionary challenge for parasites exploiting
the gastrointestinal tract. However, it is intriguing to
consider how certain parasite groups that are typically absent from sites of digestion can cope with this
hazard. Very few monogeneans inhabit regions of
digestive activity but, exceptionally, developing
juveniles of P. americanus migrate from the host’s respiratory tract to the urinary bladder along the length
of the alimentary canal. Protection is mediated by
membrane-bound vesicles that accumulate in the
tegument prior to migration and are discharged at
the surface during migration (Fig. 6.1). If migrants
Parasite evolution has recently been confronted by an
entirely novel factor: one host species has devised
hostile environmental conditions specifically to eliminate parasites, both from itself and from a wide
range of other animal and plant species which cooccur in a symbiotic/exploitative association. The
hostile agents are chemicals that interfere with
biological processes essential for parasite survival.
There are precedents of naturally occurring chemicals that have a parasiticidal effect; however, many
of the modern antiparasitic chemicals are synthetic,
and hence represent a new challenge for parasite survival. Target effects of these chemicals are usually
highly specific but they may not necessarily be lethal:
disruption of muscular activity may result in elimination. Toxic effects in nematodes have been
reviewed by Conder (2002) and Sangster and Dobson
(2002). Thus, benzimidazoles bind to parasite tubulin
and disrupt microtubule formation and function.
Imidothiazoles, including levamisole, act as agonists
at an acetylcholine-gated cation channel in muscle
membranes. Avermectins act by irreversibly opening
glutamate-gated chloride channels and have a
primary effect on pharyngeal function (disrupting
feeding, regulation of hydrostatic pressure, and/or
secretion). Piperazine, a GABA-agonist, causes
hyperpolarization of muscle membrane and flaccid
paralysis. Organophosphates inhibit acetylcholinesterase, resulting in paralysis. Nitroscannate
affects glucose metabolism. Several drugs also have
immunostimulant effects (imidothiazoles) or increase
susceptibility to immunological attack (diethylcarbamazine) (Conder 2002; Sangster and Dobson 2002).
The creation of host environments pervaded by
these novel hostile factors has generated an ‘experimental system’ in which parasite adaptation to
HOSTILE ENVIRONMENTS
environmental conditions can be followed. In nematodes, selection and evolution of drug resistance has
taken place over less than 40 years and now affects
every modern anthelmintic (Sangster and Dobson
2002). Even those drugs considered highly effective
because they eliminate ‘almost all’ parasites provide
the potential for resistance to develop—among the
very few surviving. Indeed, the most effective drugs
create the most intense selection pressure because
only worms carrying resistance alleles survive and
reproduce. Sangster and Dobson (2002) emphasized
this impact of selection pressure in the evolution of
resistance. Resistance is more likely to develop in
large parasite populations (with higher genetic
diversity); it is favoured in parasites with direct life
cycles and short generation time; selection pressure
is increased by frequent treatment and by underdosing (when parasites carrying recessive resistance
alleles as heterozygotes may survive treatment).
This hostile environment can be made even more
relentless (in an effort to limit drug resistance) by
treatment with combinations of drugs and with
annual rotation of drug compounds. Then, only
worms simultaneously resistant to both drugs survive. However, Sangster and Dobson (2002) noted
that multiple resistance has developed in sheep nematode infections in South Africa and Australia, and
triple drug resistance has been reported in the United
Kingdom (Bartley et al. 2001; Yue et al. 2003). In
worms resistant to levamisole, higher concentrations
of cholinergic compounds are necessary to cause the
contraction response shown by susceptible worms,
up to 13-fold higher for the most resistant isolates.
The change in the ACh receptor which occurs in levamisole resistance also confers resistance to
organophosphate compounds that cause ACh accumulation. The review by Sangster and Dobson (2002)
emphasizes lucidly that each new strategy, with
improved drug and treatment regimens, simply
selects ultimately for greater resistance. This is a clear
demonstration of the ability, and remarkable speed,
of parasites to adapt to hostile conditions.
6.5.3 Other hostile factors: predation
Hostile factors affecting ectoparasites include
deliberate removal through grooming, by the
host individual itself and conspecifics, and by
97
heterospecific cleaner organisms (birds on terrestrial mammals, cleaner symbionts on client fish).
Among monogenean skin parasites, there is evidence that this selection pressure may have led to
the development of camouflage (pigmentation) or
body transparency as a means of evasion
(Whittington 1996; Kearn 1999).
6.5.4 The host immune response
There is extensive documentation of the functioning
of the vertebrate immune system against protozoan
and metazoan parasites, principally concerning
mammals, but also in other tetrapods and fish. There
is also much information on the internal defence
systems of invertebrates, including molluscs and
arthropods, protecting against parasitic infection.
The hostility of this natural factor in the parasite’s
environment represents a distinctive feature of parasitism: the reciprocal interaction with another living
organism. A major approach of current research aims
to elucidate the complex machinery of the hostimmune response, and this area is well reviewed in
the immunological literature. This chapter takes a
parallel approach in assessing some of the evidence
that quantifies the outcome of interactions within
this hostile environment—the scale of host-induced
mortality in parasite populations. In most hostparasite systems, there is relatively little quantitative
information on these lethal effects, measured as the
proportion of parasites successfully invading but not
surviving to reproduce within the host. This chapter
explores, in particular, a series of naturally occurring
host–parasite associations, rather than familiar laboratory models, in which field and lab evidence gives
unambiguous evidence of the extent of parasite
mortality post-invasion.
6.5.4.1 Regulation of polystomatid populations in
amphibians
Empirical studies on the polystomatid monogeneans
described above have the advantages first, that they
concern entirely natural host–parasite systems for
which exact and comprehensive field data can be
obtained by dissection and, second, that laboratory
experiments can be carried out under controlled
environmental conditions closely simulating natural
events.
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PA R A S I T I S M A N D E C O S YS T E M S
Complementary field and laboratory studies
indicate that the reproducing populations of most
polystomatid monogeneans are strongly regulated.
Despite a wide diversity of life cycle patterns that
might, intuitively, be expected to produce variations in transmission dynamics, infection levels of
adult worms are universally low (Tinsley 2003).
Tinsley (2004) summarized studies that confirm the
influence on parasite population biology of external environmental factors (including temperature),
parasite factors (including age and density), and
host ecology (including behaviour and life history
schedules). However, these studies also provide
exact data quantifying the scale of host-induced
parasite mortality: it emerges that immune attack
represents the dominant influence. Field data
for P. americanus demonstrate that the typical single
annual wave of invasion (described above)
produces consistently high infection levels. The
clear-cut schedule of events in this life cycle allows
the fate of these infrapopulations to be followed in
detail. In the period until the first opportunity for
the newly established cohort to contribute to
transmission, parasite mortality is around 97%
(Tinsley 1999b).
In the case of P. xenopodis, with a permanently
aquatic host (X. laevis), transmission is more or less
continuous and host individuals would be expected
to carry a succession of generations of parasites.
Field data confirm the predicted relatively high
prevalence and intensity of post-invasion juveniles.
However, very few survive to maturity: the prevalence of adult worms is consistently around 40%;
about 80% of infected hosts carry only one or two
mature worms and maximum intensity rarely
exceeds 6 worms/host (Tinsley 1995). Experimental
evidence, reviewed by Jackson and Tinsley (2001,
2002, 2003a,b,c) and Tinsley and Jackson (2002),
indicates that the major part of this attrition is
host-mediated. In naïve X. laevis, initial establishment is highly successful: laboratory exposures
typically produce 100% prevalence measured
immediately after invasion and around 30% of each
exposure dose establishes successfully. However,
in hosts exposed to the same larval doses and
examined at the time of parasite maturity (90 days
p.i. at 25 °C), less than 3% of the worms that initially
established survived to maturity (Jackson and
Tinsley 2003c). Consistently in these experimental
infections, the numbers of worms surviving to begin
reproduction were only 1–3, most commonly a
single worm per host. The loss of established worms
continues in adult burdens. Although the maximum
life span of P. xenopodis is 2.5 years, studies recording lifetime reproduction in laboratory infections
showed that median duration of survival was only
6 months p.i., and only 16% of infections survived
12 months or more (Jackson and Tinsley 2001;
Tinsley and Jackson 2002).
These experimental data relate to single exposures of previously naïve hosts, but continuous
invasion in nature might be expected to result in
progressive addition to worm burdens. In the study
of Jackson and Tinsley (2001), the survival of a
secondary infection was followed in the same host
individuals from which primary infection characteristics had been monitored. In comparison
with 94% prevalence in the primary infection, only
15% of these hosts retained a secondary infection
until patency. The experimental evidence of strong
acquired immunity indicates that most of the
individuals recorded as uninfected in natural
populations are likely to be resistant to re-infection
and this immunity may be relatively long lasting
(Jackson and Tinsley 2001) (Fig. 6.2).
These findings lead to the prediction that highest
infection levels in nature should occur in juvenile
X. laevis, experiencing their first invasions. This is
supported by field studies on feral populations of
X. laevis in the United States and the United
Kingdom where there is a strong age-dependent
effect on prevalence of patent infection (unpublished). However, even the youngest stages of postmetamorphic X. laevis are capable of developing
acquired immunity to secondary infection (Jackson
and Tinsley 2003a).
Further indication of the hostile nature of the
environment in hosts with prior experience of
infection is provided by measures of reproductive
performance in secondary infections. In the small
proportion of hosts in which secondary infections
survive, the period to patency is more than doubled
(median 9 weeks in a primary infection, 21 weeks in
a secondary infection of the same host individuals),
HOSTILE ENVIRONMENTS
6.5.4.2 Dynamic environmental change affecting
Gyrodactylus species
In most host–parasite interactions demonstrating
acquired immunity, the host environment may be
considered ‘benign’ at the time of initial invasion
but there is a change, over a variable time course, to
a profoundly hostile environment. This is illustrated
very clearly by the infrapopulation dynamics of
Gyrodactylus species. For these fish ectoparasites,
worm numbers can be counted on individual living
hosts as the interaction proceeds. Gyrodactylids
have a unique form of viviparity in which an offspring developing within the uterus of a parent
worm has, in its uterus, another developing embryo
and this, in turn, may carry another. The reproductive processes (reviewed by Cable and Harris 2002)
result in a sequence of parasites that are already
adult at birth, released directly onto the infection
site. This generates the potential for exponential
population growth that may have serious pathogenic effects. However, the host has the capacity to
limit and eventually eliminate infection by an
immune response. A typical pattern of infection is
shown in Fig. 6.3 (curve a) for G. turnbulli parasitic
on guppies (Poecilia reticulata). In this tropical
system, at 25 °C, mean parasite burden rises to a
18
16
Mean parasite burden
and rates of egg production are much less than half
(Jackson and Tinsley 2001).
Further studies based on field isolates have
demonstrated a complex pattern of parasite infectivity and host susceptibility in natural populations
in Africa: different parasite isolates showed consistent differences in infection success in a single
group of full-sibling laboratory-raised hosts.
Infectivity was found to change during laboratory
passage, especially when bottle-necked through a
small number of host individuals. These and other
studies indicate that the key factors influencing
survival in this host–parasite relationship are
highly heterogeneous and emphasize the importance of compatibility between host and parasite
‘strains’ in determining infection success. In other
words, the nature of the host environment—reflecting its hostility to parasite infection—varies in
different host and parasite genotype combinations
(Jackson and Tinsley 2003b) (Fig. 6.2).
99
14
(a)
12
10
8
6
4
(b)
2
0
4
8
12 16 20 24 28
Days post–infection
32
36
40
Figure 6.3 Population dynamics of Gyrodactylus turnbulli on guppies,
P. reticulata, following experimental infection of naïve fish (a) Parasite
burdens rise rapidly to a peak and then decline; (b) re-infection of the
same fish after the primary infection leads to rapid elimination of the
challenge infection confirming acquired immunity.
Note: Bars represent one standard error.
Source: Reproduced, with permission, from Scott (1985).
peak at about 10 days post-experimental infection
and then falls, initially very rapidly, leading to
extinction after 38 days (Scott 1985). Fish that
have eliminated a primary infection are refractory
to challenge infection (Fig. 6.3 curve b), and their
acquired immunity is maintained for at least
6 weeks. Equivalent characteristics have been
demonstrated in many Gyrodactylus species (with
variations in time course attributable in part to
species-specific natural temperature ranges).
However, there is also significant variation between
hosts of the same species in susceptibility to infection, and this is heritable (Madhavi and Anderson
1985).
Buchmann and Lindenstrøm (2002) reviewed the
range and action of a series of host molecules interacting with infecting skin monogeneans, including
lectins, complement factors, antibodies, acute phase
proteins, lysozyme, and anti-microbial peptides.
They interpreted the variation in the response of the
host environment to gyrodactylids particularly in
terms of the binding affinities of different isoforms
of complement factors. Parasite survival may be
100
PA R A S I T I S M A N D E C O S YS T E M S
determined by possession of particular epitopes:
presence leads to binding by specific complement
factor isoforms and activation of the destructive
cascade; absence allows parasite survival. Likewise,
release of mediators from damaged host tissue may
trigger a cascade of cellular and humoral reactions:
Buchmann and Lindenstrøm (2002) reported that
G. derjavini infection switches on IL-I genes and
initiates expression of interleukin in the skin of
rainbow trout. Clearly, fish skin represents a highly
reactive substrate for life by monogenean ectoparasites, as well as representing an inherently difficult
surface for parasite attachment (see Kearn 1999).
Buchmann and Lindenstrøm (2002) also reviewed
potential immune evasion mechanisms that might
contribute to survival of monogeneans in this
hostile environment, but it is significant that the
response is typically local and temporary respite can
be gained by migration of worms to other body
areas.
The unstable environment that is encountered by
a growing population of fish ectoparasites over
a relatively short time period is illustrated by many
studies of Gyrodactylus infection dynamics, demonstrating variable outcomes through subtle
differences in factors. Cable et al. (2000) compared
reproductive characteristics of experimental infections of G. salaris on different stocks of Atlantic
salmon (Salmo salar), originating from two rivers in
Norway and one in the Baltic. Detailed measurements of life history schedules revealed small
differences in parasite fecundity, developmental
time and mortality between infections on these host
genetic strains. On hosts of Baltic origin, fewer
parasites (45%) survived to give birth once in comparison with hosts of Norwegian origin (60–63%
survival); maximum number of births per worm
was only two on Baltic hosts (mean 0.6) compared
with four on Norwegian stocks (means 1 and 1.3
respectively); mean developmental period of the
first offspring was 2.3 days on Baltic and 1.8 days
on Norwegian hosts. These and other variations
were sufficient to cause fundamental differences in
infection dynamics, with predicted exponential
growth on Norwegian fish (R0 = 1.07 and 1.08) but
negative growth and eventual extinction on Baltic
fish (R0 = 0.94). This work demonstrates very
precisely the small scale of the host effects that can
determine whether parasite populations may
increase rapidly to cause pathogenic disease,
coexist asymptomatically, or become eliminated.
The studies of Bakke, Cable, Harris, and
co-workers on G. salaris provide further rich insight
into variations in the effects of host environment on
parasites because this gyrodactylid species has an
exceptionally wide host species range, adding the
extra dimension of host specificity. Salmonid
species range from highly resistant (brown trout,
whitefish), through moderately resistant (char,
grayling, rainbow trout), to highly susceptible
(Norwegian strains of salmon). Bakke et al. (2002)
suggested that these states may be part of a single
spectrum of response to gyrodactylid infection, and
that the same mechanism, probably polygenic, controls resistance throughout the range of different
host-parasite interactions.
For a parasite individual, faced with a natural
assemblage of fish species in a given habitat, the
alternative host environments that it encounters
will determine the potential for survival and reproduction (Fig. 6.4). At one end of the range, nonsalmonids may act as transport hosts maintaining
worms (probably without feeding) for several days.
Resistant hosts may permit a brief ‘round’ of reproduction and onward transmission. The distinctive
feature of gyrodactylids, that transmission is
effected by established adult worms, means that
parasites eliminated from one host may survive to
infect others. Highly susceptible hosts that present
the most favourable conditions for parasite population growth may be overwhelmed by infection and
die, producing a massive short-term boost to the
transmission potential of the suprapopulation.
One implication of the experimental studies of
Gyrodactylus infection dynamics is that the host
environment is entirely permissive during the initial exponential phase of parasite population
growth. Then, after a time delay, the host response
develops and infection levels begin to fall. This is
illustrated by the ‘classic’ pattern shown in Fig. 6.3.
However, the very detailed analyses of G. salaris
population biology by Bakke et al. (2002) revealed,
remarkably, that parasite reproductive rate declines
throughout an infection and not, as would be
Characteristics of host
Characteristics of parasite
Infection duration
innately resistant
Survives for limited period
on carrier hosts
Parasite population fails to
grow, eventually eliminated
responder
Factors controlling host-parasite interaction
Initial parasite population growth,
Host species/strain/individual variation
reduced by immune response
Heterogeneity in ability to respond
to low level or eliminated
susceptible
Parasite population grows
without check until host dies
± Short
(no feeding)
Population establishes and
grows at variable rates and
for varying periods
Processes modulating host response
Competition, density, pollution, starvation,
disturbance, linked to stress/immunosuppression
permitting parasite population growth
Population size
Population able to increase
exponentially for a limited
period
Significance for parasite population
persistence, transmission
Low
(no reproduction)
± Long
± Short
± High
± High
Temporary survival prolongs
infectivity, transport hosts
permit dispersal
Transfer potential determined by
duration (time for new encounters)
and density (worm numbers available
to transmit)
Production of maximum worm
numbers in unit time, massive
potential limited by duration of
host survival
Processes modulating parasite population growth
Temperature, salinity, water chemistry,
host response
Parasite effects
High burdens represent stressor,
immunosuppression permits parasite population
growth; previous experience of infection
enhances immune response,
accelerates elimination
Temperature effects
On parasite, influence reproductive rate;
on host, regulate immune response
Parasite diversity/strain variation
(Not yet documented)
Figure 6.4 Variability of the host environment for Gyrodactylus salaris infecting the spectrum of salmonid and non-salmonid fish available in natural habitats. Categories based on the overview by
Bakke et al. (2002). Conditions on resistant hosts preclude feeding and reproduction (whilst permitting survival); responder hosts have inherent capacity to create hostile conditions but the course
of the interaction is highly variable, subject to effects of abiotic, biotic, host and parasite factors, and these determine the extent of parasite population growth and transmission potential;
conditions on completely susceptible fish provide no restraint, permitting runaway parasite population growth that kills the host. The factors controlling the interaction (second column) have the
effect of shifting the outcome along the gradient of host and parasite characteristics, changing the potential for parasite population growth and transmission.
PA R A S I T I S M A N D E C O S YS T E M S
6.6 Complex interactions between
parasite, host, and external
environmental factors
For ectothermic vertebrates, activity of the immune
system is highly temperature-dependent, and this
has a fundamental effect on seasonal dynamics of
parasite infection. For Protopolystoma spp. infecting
species of Xenopus, experimental studies have
shown that increase in temperature significantly
reduces adult parasite populations. Jackson and
Tinsley (2002) compared laboratory infections of
P. xenopodis resulting from a standard dose of infective larvae and maintained at either 15 or 25 °C during development to maturity. These are temperatures
experienced in natural habitats in southern Africa at
different seasons of the year and at different altitudes. The period to patency was three times longer
at 15 °C (150 days p.i.) than at 25 °C (50 days), but
prevalence was 96% at the lower temperature and
only 38% at 25 °C. The overall parasite population
surviving to begin reproduction at 25 °C was only
one-third of that at 15 °C (Fig. 6.5). This effect is
consistent with the temperature dependency of the
immune response in amphibians. Equivalent effects
were evident when infections of P. americanus were
maintained in S. couchii hibernating under different
temperature regimes in the laboratory. At 15–20 °C,
parasites survived without significant decrease for
over one year. However, at constant 25 °C, worm
burdens declined progressively and all parasites
(a)
Frequency
expected, from the time of the host response. This
suggests that the host environment reacts (becomes
hostile) from the initial encounter with the parasite.
The response is not density-dependent (and hence
not influenced by factors including pathogenic
effects) but instead is time-dependent. So, the initial
process of parasite infection and establishment
immediately ignites a fuse leading, in most cases, to
extinction on that host individual. Among other
interacting factors, especially parasite reproductive
rate and intensity of host response, a key factor
determining the overall outcome is time: the
duration of infrapopulation survival and the
opportunities for onward transmission.
20
15
Mean = 1.66 (n = 25)
Prevalence = 96%
10
5
0
0
4
5
6
1
2
3
Infrapopulation size (urinary bladder)
(b)
20
15
Frequency
102
Mean = 0.96 (n = 24)
Prevalence = 38%
10
5
0
1
2
3
4
5
6
0
Infrapopulation size (urinary bladder)
Figure 6.5 Interaction of multiple factors determining the outcome of
infection in an ectothermic host, illustrating direct effects and indirect
significance: (i) temperature affecting parasite processes (feeding,
developmental rate), (ii) temperature affecting host immunity (ability
to respond to infection), (iii) parasite affecting host (worm burden and
nutrient drain determining pathology), and (iv) host affecting parasite
(immune regulation of burden size, and probably also growth rate,
reproductive output).
Histograms show frequency distributions of Protopolystoma
xenopodis surviving to start reproduction in X. laevis following
exposure to 20 infective stages at (a) 15 or (b) 25 °C (n = 25 and 24,
respectively).
Notes: Prepatent period was 50 days at 25 °C, 150 days at 15 °C; 62% of
hosts lost their infections at 25 °C, only 4% at 15 °C; total parasite population
was 2.8 times higher at 15 °C than at 25 °C. Regarding potential pathogenic
effects, at lower temperatures, while most hosts are infected and have higher
burdens, parasite feeding is reduced; at higher temperatures, when blood
removal is greatest, worm burdens are reduced. Regarding parasite
reproduction, at lower temperatures, slow development delays start
of egg production and this proceeds at low rates; at higher temperatures,
development and per capita reproductive output are greater but the
surviving adult parasite population is small.
Source: Figure from Jackson and Tinsley (2002), with additional
interpretation from Tinsley and Jackson (2002).
were lost after 10 months (Tocque and Tinsley 1994;
Tinsley 1995).
In experimental studies of G. salaris infecting
salmonid fish, different trajectories of parasite
infrapopulation growth are highly sensitive to
HOSTILE ENVIRONMENTS
differences in abiotic environmental factors
(temperature, salinity, water chemistry, and pollution), biotic and host genetic influences. Bakke et al.
(2002) reviewed the key effects of temperature controlling the strict seasonality of population dynamics. For G. salaris, maximum life span is negatively
correlated with temperature (8 days at 19 °C but 53
days at 2.5 °C) while reproductive rate is positively
correlated (r = 0.02 at 2.6 °C, 0.22 at 19 °C). So, parasites survive at low infection levels in winter, but
populations increase with rising spring temperatures. However, while elevated temperature
increases parasite reproductive rate, it has a relatively greater effect on population dynamics by
enhancing the host immune response. Therefore,
when water temperatures are highest in late summer, and parasite populations should be largest,
low prevalence and intensity is characteristic
(Bakke et al. 2002). There are other significant interactions between environmental factors, especially
those conditions that cause stress (pollution, fish
density, starvation) and reduce host immunocompetence (Fig. 6.4). Most importantly, a major determinant of parasite population dynamics is past
experience of infection. Extrapolating from the pattern shown in Fig. 6.3 to natural host populations,
individuals that have recently eliminated an infection would be unavailable to the parasite
suprapopulation for some weeks or months. It
remains to be established how repeated stimulation
from attempted invasion might affect this refractory
period.
Another impact of the parasite in affecting this
spectrum of environmental constraints is recorded
by Bakke et al. (2002). A rapidly growing gyrodactylid infrapopulation can potentially elevate
host blood cortisol, causing immunosuppression.
This could act as a positive feedback mechanism,
leading to runaway parasite population growth
and host death.
Studies on the nematode, Strongyloides ratti
by Viney (2002) provide further insight into the
complex interactions of environmental factors that
affect parasite life cycles. Adult female worms in
the rat intestine produce eggs that develop in the
external environment along two alternative pathways. One produces larvae that directly re-infect
103
the host population and develop into adult
females that are genetically identical to each other
and to their mother. The other produces larvae that
develop into free-living adult males and females
that reproduce sexually: eggs from these matings
develop into infective larvae that invade the rat
host. The proportions of offspring developing by
these two routes, involving asexual or sexual reproduction, changes during the course of infection in
individual rats. Viney (2002 and references) established that the developmental switch is determined
by the host immune response. This leads to an
increase in the frequency of sexual reproduction
over the direct developmental route that involves
mitotic parthenogenesis. External environmental
temperature also affects parasite development: low
temperatures favour direct development to infective larvae that reinvade the rat; high temperatures
favour indirect development to free-living adult
females that reproduce sexually. These two environmental effects, host immunity and temperature,
interact during the course of an infection so that
sensitivity of developing larvae to temperature
increases as a result of their experience of the
immune response. This implies that larvae developing in the external environment must have a
‘memory’ of the immune status of the host from
which they were passed (Viney 2002).
Viney noted that the developmental switch in
S. ratti conforms to the general trend that sexual
reproduction occurs at times of environmental
stress. In the case of S. ratti, the host immune
response constitutes this environmental stressor for
parasites within the host, but the stages that undergo
sexual reproduction are in the external environment.
So, Viney suggested that the immune response is
used as a predictor of the host environments that
may be encountered by future infective larvae.
Viney (2002) argued that the developmental
switch in the S. ratti life cycle is unlikely to be
caused directly by increasing hostility of the parasite’s environment as the immune response develops. Certainly the change involves a specific anti-S.
ratti immune response, but the parasite may assess
a change in its internal physiology affected by host
immunity as a measure of the intensity of the
immune response. Ultimately, the changes in the
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PA R A S I T I S M A N D E C O S YS T E M S
parasite’s environment completely eliminate the
infection, after which rats are strongly immune to
re-infection.
environment encountered by parasites within their
hosts is in a dynamic state, influenced by the
interaction of a complex of factors.
6.7 Host control of hostility
6.8 Parasite control of the hostile
environment
Creation of the hostile environment within the
host’s body carries a cost in terms of resources:
diversion of energy and materials to the immune
response may reduce the host’s investment in
growth and reproduction (i.e. its fitness). The costs
of defence influence the evolution of resistance,
especially the relationship between the fitness
reduction imposed by immunity and the negative
effects of infection in a susceptible host (Kraaijeveld
et al. 2002; Medley 2002).
Medley (2002) considered this interaction from
the perspective of an individual host, modelling
how the host should optimally distribute resources
between reproduction, survival and immunity to
maximize fitness. Results showed that, under
conditions of continuous infection, optimum
resource allocation by the host allows tolerance of
some parasite infections. In other words, the hostile
environment created by the immune response may
be regulated by the host, permitting a proportion of
invading parasites to survive. However, Medley
(2002) also demonstrated the sensitivity of this state
to variations in resource acquisition: with poorer
nutrition, hosts should invest less in immunity and
parasite burdens increase. Each host has a different
optimal response, determined especially by different resource bases, and this translates into each host
having its own optimum immune response and,
therefore, its own parasite burden. This perspective
attributes variations in the hostility of the parasite’s
environment to a ‘decision’ (optimization) by the
host. However, the costs of immunity (which determine the parasite burden tolerated) are subject to
manipulation by the parasite. Medley (2002) raised
the complicating factor that resources devoted to
immunity may contribute to both protective and
non-protective responses. A parasite that induces
production of non-protective antibodies increases
the resources required for a host defence of reduced
effectiveness: this would tend to increase the
optimum burden tolerated. Clearly, the hostile
The comprehensive studies on Gyrodactylus and
Strongyloides species concern systems where the
parasites appear to be ‘on the run’ from an environment that becomes increasingly hostile. The life
cycle strategy of both can be interpreted in terms of
achieving maximum reproduction while the environment permits survival. However, significantly,
the mode of reproduction involves initial asexual
production of offspring, suited to the current environment, followed by sexual reproduction that generates diversity better equipped to meet variation
in future environmental conditions. Nevertheless,
the course of infection in the present host automatically provokes conditions eliminating infection
in that microenvironment. In other host–parasite
systems, it is well documented that parasites faced
with a host immune response can evade or modulate the developing hostile conditions. For several
intensively studied parasites, these interactions
have been examined in very considerable detail:
there are comprehensive reviews in the literature
interpreting the mechanisms of immune evasion by
schistosomes, malaria, trypanosomes, and others,
and of modulation of immune attack. It is unlikely
that these sophisticated processes have evolved in
only a limited range of parasites (selected for intensive research because of their relevance to humans);
it might be predicted that equivalent adaptations
exist widely among parasites to counter what is,
arguably, the dominant environmental factor
influencing survival within the host (Tinsley 1999a).
Alongside the documentation of host immune
mechanisms and parasite survival strategies based
on parasites of medical and veterinary importance,
it is interesting to consider interactions in other
wildlife systems. Studies by Riley and co-workers
provide this wider insight for members of the phylum Pentastomida, parasites whose adults infect
the respiratory tract of tetrapod vertebrates, principally reptiles. Fossil representatives of this group
HOSTILE ENVIRONMENTS
occur in the early Palaeozoic, and molecular studies
confirm its origin from crustacean ancestors
(Lavrov et al. 2004). Riley and Henderson (1999)
emphasized the ancient association of pentastomids with reptiles and documented complex
survival adaptations that probably evolved very
early in the relationship.
The vertebrate lung might seem to provide a
favourable habitat for macroparasites, with its delicate pulmonary epithelium, rich blood supply, and
direct entry and exit route for infective stages.
However, relatively few helminths have colonized
vertebrate lungs to reside in or on the respiratory
epithelium (reviewed by Riley and Henderson
1999), and this is likely to reflect fundamental difficulties for survival in this highly specialized
microenvironment. A key component regulating
lung function is pulmonary surfactant, a complex
mixture of phospholipids, neutral lipids, and
proteins. This has an essential biophysical role and
is also vitally important in protecting the lungs from
infection. Lung-dwelling pentastomids are typically
large (some are 5–10 cm in length), long-lived (in
some cases many years), and feed on blood from
the pulmonary capillaries; but, they cause little
observable pathology. Riley and Henderson (1999)
attributed the success of these parasites to their
adaptations for immune evasion that involve
secretion of their own surfactant. Pentastomids
have a prominent system of glands that discharge
membrane-dominated excretory/secretory (E/S)
products onto the surface of their cuticle. This coating has a lipid composition very similar to that of
lung surfactant and is therefore immunologically
compatible with host secretions. Alongside its role
in evading immune surveillance, pentastomid surfactant also reduces inflammatory reactions and
this explains the characteristic lack of pathology in
long-term infections (Riley and Henderson 1999).
Adults of T. spiralis occur in an increasingly
hostile environment, in the intestine, that leads to
parasite elimination and acquired immunity (see,
for instance, Bell 1998). The life cycle requires that
larvae, in the muscles of the same host, remain
infective for months or even years. As in the case of
limited exploitation of the vertebrate lung luminal
environment (above), striated muscle tissue has
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a very restricted list of colonizing protozoans and
helminths (Despommier 1998): this may reflect significant problems for parasite survival. The larva of
T. spiralis occupies an individual muscle cell without killing it and remains metabolically active
(unlike the encysted, dormant stages of other muscle
parasites including cestode larvae). Exceptionally
among helminths, Trichinella reprogrammes host
genomic expression via secreted peptides to
produce a nurse cell devoid of muscle proteins that
supports growth and maintenance of the parasite
(Despommier 1998). This achieves relatively longterm survival, but the combined effect of infection
is to reduce muscle activity and induce fatigue,
increasing the possibility of predation by the next
host in the life cycle.
Among intracellular habitats exploited by protozoans, macrophages represent an exceedingly
hostile microenvironment. Following uptake by
phagocytosis, Leishmania species survive within
phagolysosomes (although some parasites may
enter cells such as fibroblasts which are less hostile
than macrophages, and this strategy may contribute to long-term survival within the host (Rittig
and Bogdan 2000)). Macrophages should, upon
activation, be able to kill intracellular organisms,
but Leishmania has mechanisms to subvert these
lethal effects including inhibition of production
of superoxide and hydrogen peroxide in the
parasitophorous vacuole (Handman and Bullen
2002). While Leishmania can avoid direct attack by
the host’s immune system, the infected cell can still
counteract resident parasites by initiating its own
death via apoptosis. This defence mechanism is
considered to have put selective pressure on intracellular parasites (viruses, bacteria, and intracellular protozoans) resulting in strategies to inhibit the
apoptotic programme of the host cell (reviewed by
Heussler et al. 2001). Such a dangerous manipulation may have lethal consequences. In immunocompromised hosts or in infections with virulent
strains of Leishmania, the balance may be disturbed
leading to rapid apoptosis of T cells, so that an
effective immune response does not develop and
the host is overwhelmed. Interference with apoptosis by Theileria results in proliferation of infected
host cells that cannot be controlled by the immune
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system, setting off unspecific responses that result
in host death (Heussler et al. 2001). In these cases,
the escalation of the evolutionary arms race leads to
mutual destruction.
6.9 The outcome of hostile
environmental conditions: extinction
The preceding discussion of hostile environmental
conditions has explored factors that limit parasite
distribution—within geographical areas, within
species, within populations, and within particular
host individuals. Typically, it is possible to identify
a gradient of unfavourable conditions and, ultimately, a threshold beyond which adaptations fail.
The most hostile conditions experienced by organisms may be defined as those completely prohibiting survival, resulting in extinction. Hostile factors
may cause mortality of organisms directly and their
deaths accumulate to eliminate populations, or hostile conditions may prevent recruitment so that surviving organisms are not replaced when mortality
occurs naturally.
6.9.1 Extinction risks from external
environmental factors
A case study of local population extinction attributed to the influence of external environmental
conditions was reviewed by Tinsley (1999b).
Relatively long-term population studies on the
Pseudodiplorchis/Scaphiopus system in the Sonoran
Desert, Arizona, demonstrated that infection levels
at specific field sites were stable from the early
1980s to early 1990s (Tinsley 1995). However, a
series of severe summer droughts began in 1992
and continued until 1995. This provided a test of
the ability of the host–parasite system, which is
entirely dependent on water for reproduction, to
tolerate exceptional perturbation. Age determination of all host and parasite individuals enabled
reconstruction of population effects on age specific
cohorts (details in Tinsley 1999b).
For the host populations, the weather conditions
precluded almost all Scaphiopus recruitment in
1993–95 and again in 1997, either because poor
rainfall prevented spawning (lack of suitable
breeding sites) (1995, 1997), or because very brief
rainfall triggered spawning but all tadpoles subsequently desiccated (1993, 1994). The outcome,
assessed from counts of annual growth rings in
toad bone, was that younger individuals corresponding to these recruitment years were entirely
absent from populations surveyed in 1997. Instead,
these populations comprised progressively ageing
individuals: half of the toads in some populations
were aged 10 years or more, up to a maximum age
of 17 years, and none was aged less than 7 years.
Heavy rainfall in 1996 and 1998 permitted successful host recruitment and the beginnings of recovery
were documented at the conclusion of the study
(Tinsley 1999b).
The effects on the parasite population were more
complex. In the initial drought years, when brief
isolated storms triggered host spawning, parasite
transmission—geared to ‘instantaneous’ episodes
(typically a few hours)—was successful. Although
the tadpole populations subsequently died, the
mating toads carried away the products of very
efficient invasion. Thus, a mass input of larvae in
1994 was recognizable by high prevalence and
intensity of 2-year-old adult parasites in 1996 and
3-year-olds in 1997. In 1995, the rainfall was insufficient to produce breeding sites so there was a
failure both of host spawning and, therefore, of
parasite transmission. In 1996, very heavy rainfall
produced extensive flooding and, although host
spawning occurred, breeding toads were dispersed
in moving floodwaters. Infective stages that are
typically released into small pools of standing
water were washed away. This 1996 cohort of
P. americanus was missing at most sites in the following years. The 1997 summer rainfall and environmental conditions resembled those in 1995 and,
at most localities, parasite recruitment was reduced
or absent for a third successive year (Tinsley 1999b).
Maximum lifespan of P. americanus is generally
3 years (about 0.5% of worms may survive 4 years)
(Tocque and Tinsley 1991b), and interruption
of transmission for the three successive years
(1995–97) could not be tolerated. At sites where
P. americanus had been stable in previous long-term
studies, the local suprapopulations were found to
be extinct in 1998 (Tinsley 1999b).
HOSTILE ENVIRONMENTS
6.9.2 Extinction involving parasite–parasite
interactions
A dramatic illustration of the effects of interspecies
hybridization, leading to replacement and local
extinction, is provided by studies on schistosomiasis
in Loum, Cameroon (updated by Webster et al.
2003). Until the late 1960s, human schistosomiasis
in this area was caused by a single species,
S. intercalatum (infecting intestinal blood vessels).
However, records in 1972 revealed that S. haematobium (in urinary bladder blood vessels) had become
established and that hybridization between the
species was occurring. Subsequent studies showed
that hybrids resulting from S. haematobium male X
S. intercalatum female crosses were more viable than
the reverse cross. Pairings with S. haematobium males
had an advantage in transmission since the pair
located in the vesical site and egg output more easily evaded basic sanitation controls. Several environmental changes were implicated in this introduction,
including local forest clearance that favoured the
snail host of S. haematobium. Parental parasite species
were found to be strictly specific to single snail
species, but their hybrids were able to utilize both
snail species as intermediate hosts. Over the next 25
years, a series of field studies demonstrated a progressive change from intestinal to urinary schistosomiasis and, finally, the complete replacement of
S. intercalatum through introgressive hybridization.
In 1990, one-third of schistosomes were of hybrid
origin, but molecular studies showed that the proportion of hybrids in the overall population fell to
5% in 1999 and 2000 with the overwhelming majority being S. haematobium (Webster et al. 2003).
This impressive documentation has revealed a
rapid evolutionary process in which external environmental change (including forest clearance) created a zone of sympatry (both outside and inside the
definitive host). The resulting interspecies interactions produced conditions detrimental to one of the
species and, although genes of S. intercalatum may
persist in recombinants, the outcome has been extinction. A similar risk of partial or total exclusion of one
species by another has now been recognized in other
two-species schistosome interactions, including the
progressive replacement of S. haematobium by
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S. mansoni in the Fayoum, Egypt (Webster et al. 1999;
Cosgrove and Southgate 2002).
6.9.3 Evidence for extinctions in ecosystems
Environmental conditions that are responsible for
complete extinction may be considered to define
the most hostile factors facing parasites (and all
other organisms). Extinction of the host, by definition, removes the environment of a host-specific
parasite and is equivalent to loss of an essential
component of the ecosystem for free-living organisms. However, the occurrence of such extinction
events in the past, involving total loss of genetic
information from evolutionary lineages, is difficult
to document for parasites. It would be entirely
plausible to imagine that the dinosaurs, dominant
land vertebrates for over 150 million years during
the Triassic, Jurassic, and Cretaceous, possessed a
parasite fauna that largely disappeared with their
extinction. Indeed, the well-documented mass
extinctions of major animal groups that have punctuated the history of life must inevitably have been
accompanied by undocumented mass extinctions
of their stenospecific parasites. With the general
absence of fossil evidence, these extinctions remain
speculation, but there are some exciting glimpses of
this fauna in recently discovered fossils. Upeniece
(1999) reported a series of putative parasite fossils,
represented by groups of radially arranged hooks,
on the bodies of Late Devonian fish belonging to
the extinct Placodermi and Acanthodii. Poinar
(2002, 2003) recorded well-preserved nematode
parasites in ants and dipterans fossilized in Baltic
amber (dated at 40 mya).
An alternative exploration of evidence for
parasite extinction could be provided where host
groups persist but have significant gaps in their
parasite assemblages that might reflect past loss.
The pipid amphibians have a long evolutionary
history, with representatives amongst the earliest
fossil anurans in the early Cretaceous. These are
animals that overlapped the dinosaurs, but survived. The lineage including extant Silurana and
Xenopus originated about 64 mya (Evans et al. 2004)
and has a very rich parasite fauna with over 25
genera from 7 invertebrate groups (including
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protozoans, digeneans, cestodes, monogeneans,
nematodes, a leech, and an acarine mite) almost all
strictly specific to this anuran group. Tinsley (1996)
interpreted two distinctive components contributing to this assemblage: one group comprises parasites related to those in other anurans, reflecting
inheritance from a common stock; the other has
nearest relatives among the parasite fauna typical
of fishes, representing species transfers (through
common ecology, shared habitats, and diet).
Significantly, the very distinctive taxonomic position of almost all these parasites (in their own genera, families and higher taxonomic groupings
specific to Xenopus) suggests an ancient origin (for
both presumed sources) and a subsequent isolated
evolution. Among this richness and diversity, it is
conspicuous that the phylum Acanthocephala, with
a strong representation in other anuran amphibians
and in fish (i.e. both potential sources of origin), is
entirely absent from Xenopus. This is despite ecological links (especially diet) that should provide an
infection route. Similarly, the lungs of anuran
amphibians are well known as sites for abundant
metazoan parasite infections, including digeneans
and nematodes, yet the well-developed lungs of
Xenopus are unexploited (Tinsley 1996). It is entirely
conjectural that these empty niches reflect past
extinction events. The alternative explanation
would be that prospective parasites ‘missed the
boat’ (Paterson and Gray 1997), but it is surprising
that they subsequently failed to ‘get on board’
throughout the long voyage, unless they were
prevented.
Tinsley (2003) assembled evidence to suggest that
the present distribution of polystomatid monogeneans infecting anuran amphibians may be indicative of widespread extinction. The evolution of the
Polystomatidae is intimately associated with that of
the tetrapod vertebrates. A molecular interpretation
of host–parasite co-evolution (Verneau et al. 2002)
calibrated the diversification of parasite lineages
with earliest estimates of the major divisions within
vertebrate phylogeny. There are about 200 polystomatid species currently recognized (Bentz et al.
2001) with an almost worldwide distribution. Most
known species infect anuran amphibians and
Verneau et al. (2002) estimated that the polystomatids
specific to this host lineage diverged at c.250 mya.
Given the diversity of the Anura (over 3,500
species, almost equivalent to the mammals), a very
rich polystomatid fauna might be predicted.
However, Tinsley (2003) reviewed data indicating a
remarkably poor exploitation of anuran amphibians. First, at the host species level, field data for
relatively well-studied areas of the world show
consistently low representation of polystomatid
taxa. In North America, with nearly 1000 species of
anurans, only three polystomatid species have been
recorded. In Western Europe, also with a wellstudied fauna of amphibians and their parasites,
only four anuran species are infected by polystomatids. Relatively comprehensive studies of anurans
in specific geographical areas of Africa have
revealed very low parasite occurrence in the host
species potentially available within the area.
Second, at the host population level for those anuran species known to carry polystomatids, prevalence and intensity of infection are (with a few
specialized exceptions) uniformly low. Data from
extensive field surveys of Polystoma species in
Africa show a prevalence of 10% or less in nearly
half of the studies and intensity only very exceptionally exceeding 6 worms/host, most commonly
only one or two. For the majority of African
Polystoma species records, there is less than one
adult parasite for every five host individuals in
natural anuran populations (Tinsley 2003). Very
low infection levels cannot be explained in terms of
life cycle difficulties imposed by intermittent host
links with water. Thus, P. xenopodis, transmitted
throughout the year between aquatic hosts, does
not achieve higher prevalence and intensity than
P. americanus, transmitted during less than 24 h each
year between desert hosts. Tinsley (2003) drew
upon the field and laboratory data outlined above
which demonstrate that polystomatid populations
are subject to powerful regulation by the host
immune response. For P. xenopodis, with the ‘easiest’
of all polystomatid life cycles, 60% of X. laevis in
natural populations are free of patent infection and
most of those infected carry only a single adult parasite (Tinsley 1995). For P. americanus, the attrition
of successfully established worms post-infection is
such that only 3% survive to the first opportunity
HOSTILE ENVIRONMENTS
for onward transmission. The exceedingly narrow
margin between survival and complete failure suggests the possibility that relatively simple environmental perturbations could tip the balance towards
extinction.
Experimental studies on these polystomatids,
outlined above, demonstrate that increase in temperature significantly reduces infection levels. For
P. xenopodis (with continuous transmission), an
overall increase in temperature operating proportionally throughout the year, or a longer period of
elevated summer temperatures each year, could
have a critical negative effect on reproducing parasite
population size. For P. americanus (with once-per-year
transmission), if environmental temperatures were
to remain high during winter, parasites would not
survive from one transmission season to the next
(Tocque and Tinsley 1994; Tinsley 1995). Rainfall
variations interrupting parasite transmission
represent an alternative environmental perturbation
that could prejudice polystomatid survival. In the
case study documented by Tinsley (1999b), three
successive years of interrupted transmission led to
extinction of P. americanus in local host populations
(see above).
Based on these lines of evidence, Tinsley (2003)
proposed that relatively simple environmental
changes, such as those characteristic of past
climatic oscillations and operating over longer time
scales, could have led to extinction of polystomatid
lineages. The critical factor in this process is the
powerful attrition of parasite burdens by host
immunity evident in present-day host–parasite
associations, resulting in a very narrow margin
between survival and extinction. In natural host
species populations, the majority of individuals are
parasite-free by virtue of acquired immunity. In
natural anuran communities, a majority of species
may be free of polystomatid exploitation because of
past interactions leading to extinction of hostspecific parasites. This scenario would reflect combined operation of the most hostile conditions for
parasite survival: an interaction of host immunity
that achieves very effective regulation of reproducing parasite populations with critical climatic
changes that further reduce these infections and
precipitate extinction.
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6.10 Discussion and concluding remarks
The dominant theme of this review has concerned
the environmental conditions experienced by parasites within the host, and this has been explored
particularly with examples of natural host–parasite
systems. Among the many fundamental effects of
human activity on ecosystems, the management of
societies and agriculture has typically created
unnaturally close confinement of some animal
populations (including humans themselves) (see
Chapter 10). One effect has been reduction in the
hazards of the external environment that regulate
transmission of infection, producing conditions in
which the hostile interactions between host and
parasite are most intense. In attempts to control disease, humans have devised lethal factors to eliminate specific target organisms with anti-parasitic
chemicals. However, these have become potent
agents of natural selection, amplifying those parasite genotypes that have any capacity to blunt the
population impact. The efficiency of the evolutionary response by parasites is exemplified by the
rapid development of drug resistance. Other
medical interventions have also been important in
manipulating the hostility of the host environment.
Immunosuppressive therapy removes the capacity
to create a hostile environment and predisposes to
uncontrolled infection. Vaccination creates hostile
conditions before the experience (and the costs) of
a primary infection (although it reflects the complexity of interactions with protozoan and helminth
infections that effective vaccines to these parasites
have proved difficult to develop).
While it is ironic that human social organization
may have assisted the success of some parasite
infections (see Chapter 10), studies of truly natural
host–parasite systems emphasise an alternative
view: despite the superb adaptations of parasites,
the host constitutes a highly hostile environment.
These systems provide relatively rare quantitative
data on the extent of host-induced parasite
mortality. Even the ‘favourable environments’, in
which parasites can survive and reproduce, may be
responsible for major mortality within parasite
infrapopulations and this contributes to the regulation of host–parasite interactions. The consistent
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estimates of >95% mortality between successful
invasion and first reproduction in polystomatid
monogenean life cycles (above) testifies to this
hostility.
Hostility of the environment cannot be considered
a characteristic property of the conditions that define
that environment (with respect to high and low temperature, pressure, availability of water, oxygen etc.).
Adaptations of the organisms inhabiting the environment determine whether processes of growth
and reproduction can occur or whether survival is in
jeopardy. This applies both to the external macroenvironment and to the microenvironment provided
by a host which, to a parasite specific to that host,
may appear favourable whereas, to an unnatural
infection, it may cause rapid destruction.
In many parasite life cycles, major external environmental constraints with the power to block transmission and population growth can be identified,
but they sometimes do not actually represent conditions that could be described as hostile. In a series of
unrelated examples, the temperature threshold
below which parasite development is arrested is
remarkably ‘moderate’: about 10–15 °C in different
species. In temperate regions, this limitation
precludes new contributions to transmission for up
to 6 months each year (except for the pool of alreadyinfective eggs, larvae, or encysted stages accumulated, in some life cycles, during the preceding
warmer period). There should be significant selective advantage for parasite adaptations exploiting
lower temperatures and reducing this long interruption. Given the evidence of rapid parasite adaptation
in the evolution of drug resistance, for example, it
seems a paradox that temperature effects should
halt recruitment into parasite populations for such
a major part of each year.
There are remarkable examples of parasite adaptations to extreme abiotic stress: survival mechanisms including anhydrobiosis in nematodes are
important in maintaining life cycles despite normally lethal constraints. Nevertheless, in environments where macro-conditions are most hostile,
there is evidence that parasites may exploit specific
micro-environments where conditions are ameliorated. Thus, transmission of nematodes of reindeer
and Echinococcus multilocularis in voles and foxes
may continue over winter on Svalbard when air
temperatures may be as low as –40 °C. However,
the environment is not so extreme under protective
snow cover, where infective stages may occur.
Fasciola hepatica must be assumed to exploit regular
short periods when temperatures are above the
minimum threshold permitting development in the
high Andes. Parasites of ectotherms, that might be
expected to experience external temperature conditions directly, may also benefit from amelioration of
environmental conditions resulting from host
behaviour. The behavioural responses of S. couchii
in selecting optimum sites in the desert (including
excavation of hibernation burrows) coincidentally
provides its parasites with the most equable
micro-environmental regime.
An important requirement in strategies involving
a wait for the return of favourable conditions is
a trigger factor and its recognition by the waiting
parasite stage. With appropriate life cycle timing,
the conditions experienced in hostile ecosystems
may not be hostile at all. In its brief excursion into
the desert environment, P. americanus encounters
conditions that are entirely ‘benign’, both in terms of
physical factors (transmission in water) and factors
affecting invasion (host density). This is reflected in
transmission success that is higher than in any other
platyhelminth (see above). In this case, the conditions typically associated with a hot desert have relatively limited direct impact on parasite survival:
the most important constraints on parasite life history are a product of the interaction with the host.
The extensive documentation of the complex
interactions involving host immunity and parasite
evasion provides evidence that the hostile environment created by the immune response has been
a potent force selecting for parasite adaptation. The
complex array of anti-parasite killing mechanisms
brought into action by an infected host gives
a vivid impression of an exceedingly hostile environment; but, the survival of Schistosoma mansoni
in the human blood stream for over 20 years is
testimony to the effectiveness of immune evasion
mechanisms.
The hostile conditions created within the host
have lethal effects, but this is a dynamic interaction:
the severity of conditions is dependent on resource
HOSTILE ENVIRONMENTS
allocation by the host but can also be manipulated
by the parasite. The parasite, too, incurs a cost in
deployment of survival mechanisms.
The distinctive characteristic of parasitism is that
the immediate environment is provided by another
living organism. There are two effects. First, as
argued by Combes and Morand (1999), parasites
provoke the hostile conditions. There are no parallels in the ecology of free-living organisms that the
environment reacts specifically to the presence of
that organism, producing a lethal effect to eliminate
it. Indeed, the environment may be more or less
benign in this respect until invaded. The second
interaction is also a special feature of parasitism: a
capacity to modify the host environment. Thus,
parasites can reduce or suppress the hostile conditions; they can also manipulate processes that
should be hostile to benefit their survival. Freeliving animals can exploit existing variations in
external environmental conditions and they can
moderate the microenvironment that they actually
experience (by behavioural thermoregulation, for
instance); but they rarely change the environment
(Homo sapiens is, of course, a notable exception).
Combes and Morand (1999) considered that,
once adapted to a particular environment, an
organism’s fitness is highest in that environment
irrespective of anthropomorphic views regarding
the severity of conditions experienced. They concluded that it is more comfortable to live inside a
polar bear than outside on the pack ice: ‘The polar
bear does live in an extreme environment. Its parasites do not.’ However, the principal indication of
this review is that the most hostile of all environments experienced by parasites is that encountered
within the body of the host. Thus, one of the parasites of polar bears, T. nativa, has the distinction that
it may never encounter the external environment
during its life cycle, transmitted directly from one
endothermic host to the next. If this thermostatic
regulation should fail (at host death), then encysted
larvae can still survive prolonged periods in frozen
carrion until eventual ingestion by a scavenger. For
maturing parasites in the intestine, the inside of the
host is exceedingly hostile: survival of adult worms
is limited to only a few weeks or months. In
immunocompromised hosts, this brief lifespan is
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extended, demonstrating that it is the hostile
immune environment that imposes the lethal effect.
Within the host’s body, T. nativa larvae provide
superb illustration of the ability of parasites to modify their environment, taking over the developmental machinery of individual muscle cells to create a
protected home. However, even in this state, the larvae are subject to attrition: calcification begins after
9–12 months. Larval mortality is more rapid in some
host species (including pigs) than others (laboratory
rodent models). Paradoxically, T. nativa larvae may
survive longer within a dead host in the frozen
environment of the Arctic (4 years at –18 °C) (Kapel
et al. 1999) than when inside a living host buffered
from the extreme environment outside!
For several independent host–parasite interactions systems, it has been suggested that increased
lifespan represents an important adaptation for survival in a hostile macroenvironment. Thus, in studies of F. hepatica at high altitude in the Andes,
Mas-Coma et al. (2001) noted that high infection
levels were associated with increased longevity of
infections within snail hosts. In the case of
trichostrongyle nematode transmission, although
the adaptations of these free-living stages are not
related specifically to Arctic environments, the
comparatively long life expectancy of adult worms
in Svalbard reindeer might represent an adaptation
to extreme conditions. The life cycle of P. americanus
in a desert ecosystem demonstrates the strong
selective advantage of increased lifespan when
transmission events are strictly annual: body size is
age-related and longer lifespan has an important
influence on fecundity. Relatively long life
expectancy may also have selective advantage in
bridging gaps between transmission opportunities,
and in compensating for limits on reproductive
investment imposed by hostile external conditions.
However, the Protopolystoma/Xenopus system
shows that lifespan is not simply a characteristic of
the parasite, it is actually strongly influenced by
the interaction with the host. Parasites make the
longest contribution to reproduction when in the
most compatible combinations of host and parasite
genotypes. This, too, was the explanation proposed
by Mas-Coma et al. (2001) for hyperendemic fascioliasis in the Bolivian Altiplano: reproduction by
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selfing from the snail(s) originally introduced has
generated a homogeneous intermediate host
population highly susceptible to infection.
Within host and parasite populations, variations in
parasite infectivity and host susceptibility may determine that, at a ‘micro-level’, some host environments
are more hostile than others. This has been documented in many systems illustrating ‘local adaptation’. Amongst the case studies emphasized in this
review, quantitative evidence is provided by data
from experimental infections of P. xenopodis in X. laevis. Using full-sibling groups of lab-raised hosts (with
reduced genetic variation), survival to patency for
different isolates of parasites (from both local and distant localities) showed major variation (Jackson and
Tinsley 2003b). Development within the host at
higher or lower temperatures (within the natural seasonal range experienced by host and parasite) may
result in significant differences in survival (Jackson
and Tinsley 2002). Studies of lifetime reproductive
performance showed marked variation between
infections in survivorship, egg output, etc. (Jackson
and Tinsley 2001). All this combines to illustrate, for
this natural host–parasite system, variations in the
degree of hostility that may exist in nature.
In considering the hostility created by the
immune response, there are fundamental differences between endothermic and ectothermic vertebrate hosts. The components of immune attack are
broadly equivalent (for instance, Xenopus has most
of the immune attributes better-documented in
mammals), but the intensity of interactions is
modulated in ectotherms by natural temperature
variation. In ectotherms, host–parasite interactions
experience periods of respite at low temperatures:
parasite feeding rate and host metabolic loss are
reduced; the activity of the host immune response
is, to a greater or lesser extent, suppressed. The outcome, demonstrated by the detailed quantitative
studies on monogeneans such as Gyrodactylus,
Pseudodiplorchis, and Protopolystoma species (above),
shows that during periods of reduced parasiteinduced pathology, host-mediated attack on parasite populations is also reduced. At higher
temperatures, when there are rate increases in
parasite activity (including feeding, reproduction
and transmission), the host immune response is also
correspondingly upregulated. In endotherms, by
contrast, both pathogenic effects and immune attack
are continuous at constant temperature—both are
relentless in provoking and generating hostile conditions within the host micro-environment. It might
be speculated that improved immune defence
against infection was a major selective advantage in
the evolution of endothermy, developing in just
two classes of one animal phylum (and perhaps
also in the now-extinct advanced reptiles that were
ancestral to the mammals and birds). However,
while the increased activity of immune defences
will have been a major benefit of endothermy, the
concomitant change in the thermal environment of
parasites will have escalated the evolutionary arms
race, so that parasite pathology and reproductive
output, in an endotherm, is also relentless. The evolution of endothermy may therefore have been a
critical factor in increasing the virulence of parasite
infections, so that the capacity for creation of highly
hostile environmental conditions has also selected for
improved adaptation to survive in and circumvent
these hostile conditions.
CHAPTER 7
Parasitism and environmental
disturbances
Kevin D. Lafferty1,2 and Armand M. Kuris2,3
Several new diseases have gained celebrity status in recent years, fostering a
paradigm that links environmental stress to increased emergence of disease.
Habitat alteration, biodiversity loss, pollution, climate change, and
introduced species are increasing threats to the environment that are
postulated to lead to emerging diseases. However, theoretical predictions and
empirical evidence indicate environmental disturbances may increase some
infectious diseases but will reduce others.
7.1 Introduction
To build a predictive framework for how environmental disturbances can affect parasitic diseases,
we limit our scope to those environmental disturbances that result from human activities.
Anthropogenic change that may affect parasite
communities can be divided into five broad types:
habitat alteration, biodiversity loss, pollution,
climate change, and introduced species. We do not
limit ourselves to the facile prediction that environmental change will lead to increases in parasitism.
As we will make clear, there are substantial theoretical and empirical reasons to expect the opposite
will also often result from such changes.
With the possible exception of invasive species,
environmental disturbances can collectively be
considered as stressors (Lafferty and Kuris 1999).
Perhaps the first thing that comes to mind when one
thinks about the effect of stress on disease is our
own health. Studies link stress to reduced immune
function and various associated maladies of the
modern age (Yang and Glaser 2002). Immune systems are costly to maintain and stressed individuals
1
USGS Western Ecological Research Center.
Marine Science Institute, University of California, Santa
Barbara, California.
3
Department of Ecology, Evolution and Marine Biology.
2
may lack sufficient energy to mount an effective
defence (Rigby and Moret 2000), making them more
susceptible to opportunistic infections (Scott 1988;
Holmes 1996). But stress is not just fretting about
how to make an unreasonable deadline or frustration over being late for an appointment while sitting
in stalled traffic. Toxic chemicals (Khan 1990), malnutrition (Beck and Levander 2000), and thermal
stress (Harvell et al. 1999) are all examples of stressors hypothesized to increase individual susceptibility to infectious diseases. This line of thought
suggests that environmental stress should aggravate infectious disease. An opposing prediction
emerges if one considers population dynamics.
Abundant species have more parasites (Arneberg
et al. 1998a). The likelihood and impact of an
epidemic increases with host density because
density determines contact rates between infected
and uninfected individuals (Stiven 1964; Anderson
and May 1986). Infectious agents require a threshold
host density for transmission (McKendrick 1940).
Outside stressors that reduce host vital rates will
depress host population density, thereby reducing
the chance of an epidemic process, or even the ability of a parasite to persist at all in a declining or low
density population.
Stressors may also induce a more negative
impact on parasites than on their hosts. This should
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increase recovery rates of infected individuals and
mitigate the population-level impacts of the disease.
In addition, infected hosts might experience differentially high mortality when under stress. This
would remove parasites more rapidly from the host
population than would occur without the stressor.
While this increases the impact of disease on infected
individuals, it simultaneously decreases the spread
of an epidemic through the host population. Such a
relationship underscores the point that population
effects of stress and infectious disease cannot necessarily be predicted from their effects on individuals.
It is more likely that stress will have multiple
effects on hosts and parasites such as increasing
host susceptibility to disease while impairing host
vital rates. This makes it unclear how a particular
stressor should affect disease in a host population.
Although stressed individuals should be more susceptible to infection if exposed, the stressor will
likely also reduce the contact rate between infected
and uninfected individuals to the extent that the
stressor reduces host density. Simulation models
help resolve the opposing predictions stemming
from these alternative effects. Stress is most likely
to reduce the impact of closed system, host-specific
infectious diseases, and increase the impact of other
types of disease (Lafferty and Holt 2003).
Bustnes et al. 2000). Increases in trematodes are of
particular concern for those trematode species that
cause human disease. Deforestation reduces acidic
leaf litter and increases algal growth in ponds and
streams, creating conditions suitable for snails that
serve as intermediate hosts for schistosomes
(Southgate 1997). The Aswan Dam that created
Lake Nasser also created excellent habitat for the
snails serving as the intermediate host for the
trematodes that cause human schistosomiasis
(Heyneman 1979). Construction of other large
impoundments throughout Africa (e.g. Paperna
1969) has substantially increased schistosome
transmission, resulting in increased human morbidity and mortality (Gryseels et al. 1994).
Due to concerns for human health, the literature
tends to focus on the types of habitat changes that
increase disease. However, there are many ways that
habitat alteration, through its effects on biodiversity
loss, should decrease infectious disease (as discussed
below). In particular, the wholesale draining and
conversion of wetlands has dramatically reduced the
transmission of various infectious diseases (Lafferty
and Kuris 1999; Reiter 2000). Management of water
sources for breeding mosquitoes, through drainage
and controlled water levels, was instrumental in the
successful malaria control campaigns in the southern
United States and Israel/Palestine (Kitron 1987).
7.2 Habitat alteration
Humans have altered nature in ways that can affect
diseases (Lafferty and Kuris 1999) (see also
Chapter 10). Conversion of forest to agricultural
land dramatically changes the environment for parasites and their hosts; and this has raised concerns
for human health (Patz et al. 2000). In particular,
deforestation, damming, road construction, fish
farming, and rice farming increase malaria transmission by creating mosquito breeding habitat
(Smith 1981; Desowitz 1991). In addition, domestic
animals may provide new food sources for mosquitoes, leading to increased malarial transmission in
the associated human population (Giglioli 1963).
Habitat alteration has also created conditions
conducive for the transmission of trematodes. For
instance, dumps and fish farms attract seagulls
which fuel trematode life cycles (Kristoffersen 1991;
7.3 Biodiversity loss
Although authors disagree on the present rate of
extinction associated with human induced environmental degradation, there is no denying that it is
orders of magnitude above background levels
(Regan 2001). None of these estimates considers
extinctions of parasites which, for some host groups,
may exceed the extinction rate of host species
(Sprent 1992). Few will lose sleep over the notion of
parasites going extinct but one only need imagine
the diversity of now extinct parasites specializing on
dinosaurs (Kuris 1996) to realize that parasite extinction has been a vast, but hidden, component of evolutionary history (see also Chapter 6). In addition,
given the possible role of parasites in stabilizing
ecosystems (Freeland and Boulton 1992) conservation biologists may one day come to appreciate the
E N V I R O N M E N TA L D I S T U R B A N C E S
potential need to protect parasites (Combes 2001,
see also Chapter 8). Two caveats are: (1) many parasites are not strictly host specific and the fates of
these parasites are not tied to the extinction or persistence of single host species; and (2) parasites, due
to the nature of density-dependent transmission
dynamics, are likely to go extinct well before their
hosts (Lyles and Dobson 1993). For this reason, host
extinction may not be the key for understanding
parasite extinction. Reduced host species densities
and host species ranges are more likely to be good
predictors of parasite losses.
As mentioned previously, a decline in host density below a transmission threshold can cause host
specific infectious diseases to go locally extinct. The
number of species put on endangered lists is a good
example of cases where host densities have been
reduced to such low levels that parasite extinction
seems likely. Sometimes, we have enough evidence
for wide-scale declines in whole groups of taxa or
habitats. For instance, amphibians (Houlahan et al.
2001) and British birds (Balmford et al. 2003) are
now thought to be at substantially lower densities
than during prior decades. Populations of monitored species from a wide range of taxa have
declined appreciably in marine, estuarine, and
freshwater ecosystems; this is likely because
aquatic habitats are particularly susceptible to the
sort of degradation that leads to reductions in host
densities (Balmford et al. 2003).
About half of the primordial terrestrial habitats
have been cleared or converted to human use
(Balmford et al. 2003). However, habitat loss does
not necessarily translate into reductions in host
density if the remaining habitats are not degraded.
Under this condition, disease transmission would
be maintained. Transmission might even increase, at
least temporarily, if habitat loss leads to crowding in
the fragmented remaining habitats (Holmes 1996).
Despite this potential maintenance of transmission
on a local scale, habitat contraction and fragmentation reduces the geographic range of host species.
Since most parasite species exploit a host only over
a subset of the host’s range, we predict that host
range contraction will eliminate a proportion of the
parasite species from a host species. A better understanding of the rate at which parasite communities
115
change over the landscape would provide more
insight into this potentially large effect.
Parasites, particularly those with complex life
cycles, should generally decline with a decrease in
biodiversity (Robson and Williams 1970; Pohley
1976; Hughes and Answer 1982; Hudson et al.
1998). Digenetic trematodes are a good example.
Trematode communities can vary considerably
within a wetland (Lafferty et al. 1994; Stevens 1996;
unpublished thesis) and among wetlands ( Lafferty
et al. 1994; Huspeni 2000, unpublished thesis). This
is likely a direct consequence of the biodiversity of
final hosts that use a particular area. A healthy
marsh ecosystem provides rich feeding grounds
and habitat for dozens of species of birds that act as
definitive hosts for 20+ species of trematodes. The
primary first intermediate host for the trematodes,
the California horn snail, occurs throughout the
marshes (Lafferty 1993a,b). Huspeni and Lafferty
(in press) found that degraded sites in an estuary
had fewer trematode infections and lower species
richness relative to undisturbed control sites. This
seems most likely because estuarine birds, the
definitive hosts, should be less abundant and
diverse in disturbed areas (Kuris and Lafferty 1994;
Lafferty 1997). Correlations between trematode
species richness and bird species richness at different sites in an estuary (Hechinger and Lafferty in
review) and demonstration that the addition of bird
perches to an estuary leads to increased prevalence
of trematodes in snails (Smith 2001), further support
the hypothesis that functioning ecosystems facilitate
parasite communities.
Deforestation, particularly clear cutting, along
lakes and streams, also leads to a significant decrease
in the prevalence of trematodes and other parasites
with complex life cycles. In the most heavily cut
watersheds, rates of fish parasitization declined to
the extent that only unparasitized fishes were present in those lakes (Marcogliese et al. 2001). Since
other parasites with direct life cycles (copepods and
monogenes) actually increased in the most
impacted lakes, this supports the hypothesis that
biodiversity maintains parasites with complex life
cycles in ecosystems.
These effects can be seen over time as well.
A decline in trematode species richness at Douglas
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Lake, Michigan, is postulated to result from half a
century of increasing human disturbance, and an
associated reduction in shorebirds (Cort et al. 1937;
Keas and Blankespoor 1997). Habitat restoration
can generate the same pattern, but in reverse.
Restoration of degraded salt marsh was followed
by an increase in trematode prevalence and species
richness so that after 7 years trematode communities at restored sites were comparable to control
sites (Huspeni and Lafferty, in press). In addition to
providing substantial evidence for the link between
biodiversity and parasites, these studies indicate
how parasites can be used to monitor changes in
the environment over time (Lafferty 1997).
The cessation of hunting and other protections has
favoured many marine mammal species. In the
United States and elsewhere, regulations such as the
Marine Mammal Protection Act of 1972 fully protect
pinniped populations and these have soared (Stewart
and Yochem 2000). Not surprisingly, the prevalence
and intensity of larval anasakid nematodes in fish
that use marine mammals as final hosts increased
when and where seals became common (Chandra
and Khan 1988). The combination of increased susceptibility due to stressors, and increased population
density due to marine mammal protection regulations suggests that marine mammals are one group in
which host specific diseases will increase.
In contrast, fishing and hunting can reduce
populations of targeted species, even to extinction.
Reduction in seal populations that are still hunted is
expected to reduce the intestinal nematode parasites
of seals by reducing host-density thresholds (Des
Clers and Wootten 1990). Recent studies show how
fishing has dramatically reduced populations of
many species across the globe (Jackson et al. 2001;
Myers and Worm 2003). In depleting a stock, a fishery can ‘fish out’ a parasite. This is possible if the
fishery takes the population below the host density
threshold for the parasite and can even be profitable
if the host threshold density is higher than the density for Maximum Sustainable Yield (Dobson and
May 1987). Fishing out a parasite at a local scale is
most probable for host-parasite interactions where
the parasite has a recruitment system that is relatively closed compared to the recruitment of its
host (Kuris and Lafferty 1992). For example, in the
Alaskan red king crab (Paralithodes camtschatica)
fishery, nemertean worms can consume nearly all
crab eggs in some areas. Nemerteans develop rapidly, are probably transmitted locally and king crab
larvae disperse widely. Hence, fishing king crabs
intensively (including females) in certain fjords has
the potential to extirpate the nemertean locally in
those fjords (Kuris et al. 1991).
Several examples illustrate the potential to fish
out parasites. Fishing reduces the prevalence of
the tapeworm, Triaenophorus crassus, in whitefish,
Coregonus lavaretus, (Amundsen and Kristoffersen
1990) and has apparently extirpated a swim
bladder nematode from native trout in the Great
Lakes (Black 1983). Similarly, the prevalence of a
bucephalid trematode in scallops declined from
50–70% (Sanders 1966) to 1–2% (Sanders and Lester
1981) following intensive fishing of scallops and
of the final host, the leatherjacket filefish. These
examples suggest that parasites of fished species
should be declining over time. In contrast, a fishery
may be inadvertently managed to increase parasite
populations (Lafferty and Kuris 1993). In some
cases, as happened with bitter crab disease, fisheries can spread parasites by releasing infected
animals because they cannot be marketed
(Petrushevski and Schulman 1958). Further,
inadvertent management, by targeting unparasitized stocks, can also protect parasites in the
unharvested infected stocks. This may be able to
sustain parasite populations that might otherwise
collapse as host abundance is greatly reduced in
efficient fisheries. For example, some fishermen avoid
areas where fish have high intensities of sealworm,
because this reduces the value of the catch (Young
1972). Fishing practices may unintentionally
protect parasites. Crab fisheries often protect
reproductive output by releasing trapped females.
This protects parasites of females or parasites that
feminize males (nemertean worms, rhizocephalan
barnacles) (Kuris and Lafferty 1992).
While removal of top predators may break transmission of parasites with complex life cycles it can
also have indirect positive effects on some diseases
of prey populations (Hochachka and Dhondt 2000;
Jackson et al. 2001). At the California Channel
Islands, lobsters historically kept urchin populations
E N V I R O N M E N TA L D I S T U R B A N C E S
at low levels and kelp forests developed in a
community-level trophic cascade (Tegner and
Levin 1983). Where lobsters were fished, urchin
populations increased and they overgrazed kelps
(Lafferty and Kushner 2000). In 1992, an urchinspecific bacterial disease entered the area where
urchin densities well exceeded the host-threshold
density for epidemics (Lafferty in press). This study
found that epidemics were more probable and led
to higher mortality in dense urchin populations.
Hence, this bacterial disease acted as a densitydependent mortality source. Another example may
be the removal of sea otters and Native Americans
as black abalone predators on the Channel Islands
in the 1800s. This facilitated an increase in black
abalone populations to great abundance which
then enabled a previously unknown rickettsial disease to cause a catastrophic collapse of the black
abalone populations (Lafferty and Kuris 1993).
These examples show how fishing top predators
can favour disease transmission in prey populations (Hochachka and Dhondt 2000). Indeed, this
may be the major cause of increased diseases in
marine organisms at lower trophic levels, rather
than climate change (Jackson et al. 2001). Predator
removal is a management strategy sometimes used
to protect livestock or increase wild prey populations of conservation concern or (because they are
endangered or hunted for sport) (Packer et al. 2003).
Mathematical models find that this practice can
inadvertently increase the incidence of parasitic
infections, reduce the number of healthy individuals
in the prey population and decrease the overall size
of the prey population, particularly when the parasite is highly virulent, highly aggregated in the
prey, hosts are long-lived, and predators formerly
selected infected prey (Packer et al. 2003).
7.4 Pollution
Pollution interacts with parasitism in complex
ways, making it difficult to generalize broadly
about its effects on disease (Lafferty 1997). This is
most clear in reviews of parasites of fishes
(MacKenzie et al. 1995). Some pollutants are toxins
and these can impair host immune systems and
host vital rates. Pollutants may also impair parasite
117
vital rates and some may even preferentially
concentrate in parasite tissues (Sures et al. 1997).
However, sometimes parasites have reduced levels
of toxicants in their tissues (Bergey et al. 2002).
These possibilities lead to a diverse set of predictions about the effect of toxic pollutants on parasites (Overstreet and Howse 1977). However,
specific predictions for some parasite–pollution
pairs are possible.
Perhaps the best case for a link between toxic pollution and an increase in infectious disease is from
parasitic gill ciliates and monogenes of fishes (Khan
and Thulin 1991). Intensities and prevalences of
ciliates increase with a wide range of pollutants
(Lafferty 1997). This appears to be due to an
increase in host susceptibility. Toxins somehow
impair mucus production which is a fish’s main
defence against gill parasites (Khan 1990).
Marine mammals have the potential for interactions between pollutants and increased susceptibility to parasites. As top predators, marine
mammals bioaccumulate lipophillic toxins that can
be broadly pathogenic (O’Shea 1999). These contaminants can affect the mammalian immune system
(Swart et al. 1994); for example, harbour seals fed fish
from polluted areas have lower killer cell activity,
decreased responses to T and B cell mitogens and
depressed antibody responses (DeStewart et al. 1996).
In seals, such immunosuppression may be a cofactor
in the pathology associated with morbillivirus (Van
Loveren et al. 2000), Phocine Distemper (Harder et al.
1992), Leptospirosis and calicivirus (Gilmartin et al.
1976). Similarly, marine contaminants may increase
sea otter susceptibility to infectious diseases (see
Lafferty and Gerber 2002).
Toxic chemicals have a consistent negative effect
on helminths (Lafferty 1997). For example, selenium
is more toxic to tapeworms than to fish hosts (Riggs
et al. 1987). Free-living stages of parasites may be particularly sensitive to toxins (Evans 1982). Trace metals
kill free-living trematode cercariae and miracidia,
reducing infection rates of snails in polluted waters
(Siddall and Clers 1994). This can help otherwise
heavily infected snail species compete with other
species, greatly altering snail communities (Lefcort
et al. 2002). Additionally, if infected hosts are differentially killed by pollution, the parasite population
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will decline (Guth et al. 1977, Stadnichenko et al.
1995), further reducing prevalence. For instance,
cadmium kills amphipods infected with larval
acanthocephalans more readily than it kills uninfected amphipods (Brown and Pascoe 1989). In
addition, pollution can negatively affect fish vital
rates. For example, oil pollution causes liver disease
and reduces reproduction and growth (Johnson
2001). Such effects should reduce density and contact
rates, further reducing parasitism.
In contrast to toxic pollution, eutrophication and
thermal effluent often raise rates of parasitism in
aquatic systems because the associated increased
productivity can increase the abundance of intermediate hosts. Parasites that increase under eutrophic
conditions tend to be host generalists and have local
recruitment; cestodes with short life cycles and
trematodes seem to be particularly favoured
(Marcogliese 2001). The most dramatic examples
include parasites whose intermediate hosts favour
enriched habitats. These include some species of
tubificid oligochaetes and snails. Myxozoan parasites of fishes, which require oligochaete hosts, are
frequently more prevalent at sites polluted by
sewage (having high coliform counts) (Marcogliese
and Cone 2001). Beer and German (1993) described
how eutrophication improved conditions for snails
that serve as first intermediate host for the digene,
Trichobilharzia ocellata. Similarly, Valtonen et al.
(1997) found that eutrophication correlates positively with greater overall parasite species richness
in two fish species. An increase in frog deformities
has been linked to eutrophication of ponds which
increases the density of snails infected with Ribeiroia
ondatrae, a trematode known to cause abnormal
growth in second intermediate hosts (Johnson et al.
2002). The association between eutrophication and
pollution is not likely to be linear. At high nutrient
inputs, toxic effects may occur and parasitism can
decline (Overstreet and Howse 1977). The influence
of pollutant stressors, must be analysed in the context of natural history. Some tubificids require clean
water and will not be present at enriched sites
(Kalavati and Anuradha 1992).
Evaluating the changes in the fish parasitofauna
of oligotrophic and eutrophic lakes in Michigan,
Esch (1971) recognized that eutrophication opens
up the scale of interactions in an aquatic ecosystem.
As biomass increases due to increased productivity,
birds and mammals increasingly feed at enriched
sites. Hence, snails and fishes acquire increasing
numbers of larval parasites that will be trophically
transmitted to the non-piscine top predators. In
oligotrophic lakes, some of these same fishes are the
top trophic level and harbour mostly adult parasites. Since larval parasites are more pathogenic
than adult parasites there will be a further cascade
of disease effects on a eutrophic ecosystem.
Acid precipitation associated with air pollution
can negatively effect parasites in waters with poor
buffering capacity. Marcogliese and Cone (1996)
found that yellow eels (Anguilla rostrata) from Nova
Scotia have an average of 4 parasite species at
buffered sites, about 2.5 parasite species at moderately acidified sites, and 2 parasite species at acidified sites. This decline in parasite richness with
acidity is due to drops in the prevalence of monogenes and digenes. The latter require molluscs as
intermediate hosts and these cannot survive in
acidified conditions. Parasites that use freshwater
crustaceans as intermediate hosts may be similarly
impacted by reduced access to calcium ions.
7.5 Climate change
The most notable prediction of anthropogenic global
change is widespread increases in average temperatures (Houghton et al. 1996). This is particularly
troubling to most parasitologists from temperate
climes because many of the most deadly human
parasitic diseases we teach about, but are not at
direct personal risk to, are tropical (Rogers and
Randolph 2000). The fear is that if our world
becomes more tropical, tropical diseases will go
hand in hand with the more benign benefits of
pleasant weather. This is a bit simplistic; forecasts of
climate change do not predict that the weather in
Milwaukee will necessarily resemble that in
Manaus. Still, there is a general expectation that
temperatures will rise and precipitation patterns will
change. The distributions of parasites, as for all
species, are bounded by suitable climatic conditions.
Thus, climate change should alter the future distribution of parasitic disease (Marcogliese 2001).
E N V I R O N M E N TA L D I S T U R B A N C E S
Some parasites should be more sensitive than
others to warming. Temperature would seem particularly important when hosts are ectotherms that
do not actively regulate their temperature. In addition, parasites with free living stages should have
more opportunity to interact with climatic conditions (Overstreet 1993). For example, trematodes of
littorine snails that have free swimming cercarial
stages are not able to persist in arctic regions, presumably due to the effect of harsh weather
(Galaktionov 1993).
Moderate increases in temperature are likely to
alter birth, death, and development rates in ways
that could conceivably favour parasites or intermediate hosts. For example, if individuals are infectious
for longer time periods under warmer conditions,
then disease will increase with temperature. The
impact of parasites on their hosts may increase with
temperature if parasites are, as a result, able to
grow more or mature more rapidly (Chubb 1980).
More complicated situations arise in vector-borne
diseases where increased temperature may simultaneously increase pathogen development and vector
mortality rates (Dye 1992). Much of the research on
the effects of temperature on disease concerns fungal
pathogens of plants. In general, fungal pathogens
induce most damage to their plant hosts at warm
(but not too warm) temperatures and at high
humidities.
Studies of seasonal variation in parasites provide
insight into the effect of temperature. Direct life cycle
parasites (such as some monogenes) may be able to
reduce generation times in warm water, leading to
increases in these parasites (Pojmanska et al. 1980).
However, aquatic helminths vary in their optimal
temperature (Chubb 1979), making it impossible to
make a general prediction about the effect of warming. The cestode Cyathocephalus truncatus has poor
establishment success in trout if the water is warmer
than 10 °C (Awachie 1966), presumably because host
resistance is stronger at warm temperatures (Leong
1975). Other parasites with complex life cycles may
be favoured by warming. Trematode cercariae are
released from snails only when the water is warm
(Chubb 1979), suggesting that the season for completion of trematode life cycles will be prolonged
under global warming scenarios, a prediction borne
119
out by observations of parasite communities in a
thermal effluent (Sankurathri and Holmes 1976).
Nonetheless, it is hard to predict the effect of warming on the parasite community as a whole. In one
case where this has been studied, parasite communities in turtles declined with increasing thermal
pollution (Esch et al. 1979).
Most fitness traits for hosts and their parasites will
exhibit a peak performance at a thermal optimum. If
the relationship between performance and
temperature differs between host and parasite, the
resulting gene by gene by environment interaction
will either increase or decrease disease at a given
temperature, at least on the level of the individual
host (Elliot et al. 2002). For example, the optimal temperature of a fungal pathogen is higher than the optimal temperature of its sea fan host, placing the sea
fan at risk to global warming (Alker et al. 2001). But
the evidence does not always suggest that warming
will increase parasitism. Insect hosts gain several
advantages with moderate increases in temperature.
Haemocyte production increases and this promotes
general defences (Ouedraogo et al. 2003). The ability
to encapsulate parasitoid eggs (and presumably
other foreign bodies) increases (Blumberg 1991).
Pathogenic fungal cells lyse at high temperatures,
enabling insect host recovery (Blanford et al. 2003).
So, in contrast to the general assumption that parasitism should increase with temperature, there is a
general trend for less parasitism at higher temperatures, at least for insect hosts (Thomas and Blanford
2003). Some hosts use this to their advantage by
changing their behaviour to increase body temperature in an effort to fight infections (Elliot et al.
2002). This suggests that warming may release some
insect pests from their parasitic natural enemies,
potentially leading to a variety of economic and
ecological impacts. If climate change increases the
abundance of insects that transmit diseases, there
may be a subsequent increase in the spread of
diseases such as malaria (see below).
Precipitation is another aspect of climate that may
change with environmental degradation. Increased
precipitation should favour parasites (e.g. trematodes) that have an aquatic phase. Outbreaks of
water-borne diseases may increase with climate
change (Shope 1991), as these are linked to periods of
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increased rainfall (Curriero et al. 2001; Pascual et al.
2002). This should also result in increases in parasites
that require vectoring by biting arthopods with juvenile aquatic stages (particularly mosquitoes, but also
black flies). Despite these direct effects of precipitation, some scenarios do not predict increases in
aquatic habitat with increased precipitation because
increased temperature may increase evaporation
even more than precipitation (Schindler 2001).
Although, in some areas, humidity associated with
increased precipitation should favour some parasites,
especially nematodes transmitted by eggs or with
free-living juvenile stages, elsewhere, higher temperatures will dessicate soil (Kattenberg et al. 1996).
Increased aridity should impair the transmission of
parasites with stages that live in soil.
There are important differences in the effect of climate change on aquatic and terrestrial systems. The
first obvious difference is that atmospheric humidity
is irrelevant in aquatic systems. This means that freeliving stages of fully aquatic parasites are less likely
to be affected by some aspects of climate change. The
second difference has to do with respiration. Because
the ability of gas to dissolve in liquid decreases with
temperature, warmer water contains less oxygen.
This, coupled with the fact that ectotherms have
increased metabolic demands at high temperature,
suggests that increases in temperature can place
aquatic species under respiratory stress. The extent
to which hosts or parasites are differentially sensitive
to such stress has not been studied to our knowledge
but we suspect that hosts, particularly infected hosts,
will, on average, be at a greater disadvantage as
temperatures rise and less oxygen is available. For
example, high temperatures promote rapid reproduction of gill parasites that impair respiration at a
time when oxygen is limited (Pojmanska et al. 1980).
Also, marine snails, infected with larval trematodes,
had elevated mortalities under reduced oxygen
conditions (Sousa and Gleason 1989). Once again,
the ecological consequence of this interaction may be
to decrease or eliminate parasites from such
populations by increasing parasite mortality.
Global warming could shift ranges of parasites
poleward. For example, along the Atlantic coast
of the United States, northward expansion of the
protozoan Perkinsus marinus, which causes Dermo
disease in oysters, is associated with increases in
winter water temperatures, greatly expanding the
economic impact of this disease (Cook et al. 1998).
One likely ramification of increased temperature and
precipitation is a shift in the distribution, and a probable expansion of the geographic range of mosquitoes and other haematophagous insects that serve as
vectors for infectious disease (Shope 1991; Dobson
and Carper 1993). The potential for malaria to
expand is probably the most feared health consequence of climate change (Patz et al. 2000). The
present distribution of malaria in tropical areas and
reports of increasing outbreaks of malaria (Mouchet
and Manguin 1999; Guarda et al. 1999; Keystone
2001; Hay et al. 2003), in conjunction with concern
over warming, has prompted fear that current and
future warming will expand malaria’s distribution.
This hypothesis recognizes that variation in malaria
transmission is associated with climate. In Venezuela
and Colombia, malaria mortality and morbidity predictably increase following El Niño events (Bouma
and Dye 1997; Poveda et al. 2001). Modellers have
used the associations between climate and mosquito
distributions along with predicted patterns of
climate change to further predict that the potential
for malaria transmission will greatly expand in
the future (Martens et al. 1999). This concern has
attracted widespread public attention. However,
other models using multivariate approaches to
consider a range of factors find that the distribution
of malaria is unlikely to expand as a result of global
climate change (Rogers and Randolph 2000). In this
regard, recall that malaria was once endemic in
relatively temperate areas of the Americas and
Europe (Reiter 2000), suggesting that climate, per se,
is not the best predictor of future malaria distribution (Dye and Reiter 2000). Instead, the abandonment of vector control programmes coupled with the
evolution of drug resistance by the parasite and pesticide resistance by the vectors are much more likely
reasons for the current and future spread of malaria
(Hay et al. 2002).
7.6 Introduced species
Humans import animals and plants for pets and
agriculture. Many of these are raised near wild
E N V I R O N M E N TA L D I S T U R B A N C E S
species or have escaped to form feral populations.
In addition, humans intentionally release species
for hunting and fishing, plant them for dune stabilization and use them for biological control. Global
trade and travel accidentally introduced many
additional species (Ruiz et al. 2000). When exotics
bring infectious agents with them, they may expose
similar native hosts that have no evolved defences
to new diseases. Some species have invaded or
were introduced without their parasites and are
apparently not susceptible to local parasites
(Torchin et al. 2002, 2003), while others may bring
with them a subset of their native parasite fauna
(e.g. Lyles and Dobson 1993; Lafferty and Page
1997) (see also Chapter 3). Lafferty and Gerber
(2002) recently reviewed published records of
infectious diseases of conservation concern. For
common native species that were decimated by an
epidemic, the source of the disease was usually
novel and was first recognized as a pathogen of the
species during the epidemic. Sources for these epidemics were usually intentionally introduced
species. Most of these diseases have broad host
specificity and are less severely pathogenic in their
original and abundant (exotic) hosts (McCallum
and Dobson 1995; Woodroffe 1999; Gog et al. 2002).
Relatively low virulence in their coevolved hosts
has contributed to poor management decisions concerning the spread of an avian malaria with introduced wild turkeys (Castle and Christensen 1990).
Chestnut blight (a fungus introduced with Chinese
chestnut trees) is infamous for killing nearly every
American chestnut tree. Infectious diseases from
domestic sheep have extirpated populations of
bighorn sheep (Goodson 1982) and rinderpest
(brought to East Africa with cattle) has devastated
native ungulates (Dobson 1995a,b; see also
Chapter 8). A monogene was introduced into the
Aral sea along with the Caspian stellate sturgeon;
this parasite infected the gills of the native spiny
sturgeon, leading to mass mortalities of this naïve
host (Dogiel and Lutta 1937). Whirling disease, presumed to have originated with introduced
European trout, has spread from stocked trout to
native trout in North America, with severe consequences for native populations (Bergersen and
Anderson 1997; Gilbert and Granath 2003). Canine
121
distemper virus (originating from domestic dogs)
led to the death of 35% of the lions in the Serengeti
(Roelke-Parker et al. 1996) and has created problems for several other species at risk (Lafferty and
Gerber 2002). Similarly, parapox virus may play a
crucial role in the replacement of red squirrels by
grey squirrels in Great Britain (Tompkins et al. 2003).
Perhaps the most tragic example of an introduced
vector is the night mosquito in Hawaii which
permitted avian malaria to exterminate several
malaria-sensitive endemic bird species in the lower
altitudes where the mosquito lives (Warner 1968).
Finally, an introduced tachinid parasitoid uses
abundant exotic gypsy moths as hosts without sufficiently controlling those forest pests. Spillover
from the gypsy moth reservoir has led to substantial declines of native North American moths
(Boettner et al. 2000).
Non-indigenous species are an increasingly
common component of estuarine systems (Cohen
and Carlton 1998). One of these invaders, the
European green crab, Carcinus maenas, and its parasites have been well studied. Torchin et al. (2001)
found that the catch per unit effort of green crabs in
their native range (Norway to Gibraltar), decreases
with the prevalence of parasitic castrators
(rhizocephalan barnacles and entoniscid isopods),
supporting the hypothesis that these infectious
agents control green crab populations. In addition,
samples from introduced regions indicated that
parasites are strikingly less common or absent
where C. maenas is introduced compared to where it
is native. Additional analyses indicate that reduced
parasitism is a principle reason that green crabs
perform better in introduced locations. This is not to
say that introduced species remain completely
unparasitized. As an example, a native nemertean
worm was able to colonize C. maenas in California
by transferring from the native shore crab,
Hemigrapsus oregonensis (Torchin et al. 1996).
Averaging across several taxa, introduced animals
leave an average of 84% of their parasite species
behind; in addition, native parasites do not sufficiently colonize introduced species to make up for this
release from natural enemies, leaving introduced
animals with fewer than half the parasites species
they have in their native range (Torchin et al. 2003).
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The same pattern is true for plant pathogens
(Mitchell and Power 2003). Such a release from natural enemies could greatly facilitate subsequent
impacts of an introduced species.
Introduced species may indirectly impact native
species if they help maintain transmission of native
diseases (Daszak et al. 2000). On average, about
four species of native parasites occur in introduced
hosts (Torchin et al. 2003) and these, by gaining a
wider host base, could increase in prevalence,
intensity, and geographic range. This is particularly
problematic if the disease has little impact on the
invader and a big impact on native species.
7.7 Pollutogens
A distinctive class of infectious agents appears to be
increasing in prevalence and ecological impact. We
define pollutogens as infective agents that have a
source exogenous to the ecosystem, but are able to
develop within a host in that ecosystem yet do not
require that host for reproduction. Two diseases of
California sea otters are good examples of pollutogens; Valley Fever is caused by a fungus that enters
the marine environment from eroded soil and
Toxoplasmosis is caused by a protozoan that enters
the ocean along with faces from domestic cats (see
Lafferty and Gerber 2002). Another example under
extensive investigation is Aspergillus sydowii. This is
a terrestrial fungus that has appeared across the
Caribbean Sea as a severely pathogenic parasite of
several species of sea fans (Garzón-Ferreira and Zea
1992). It is believed to have arrived in the Caribbean
from a terrestrial source and that secondary infection
occurs only when prevalence is high (Jolles et al.
2002). Like other classes of infectious agents, pollutogens have an internal physiological dynamic within
their hosts. They may also elicit defensive responses.
However, unlike other parasites, they have little or
no infectious dynamics within the host population.
Hence, neither macroparasite nor microparasite
models are relevant (no feedback occurs). Pollutogens have no threshold for transmission, no
virulence tradeoff consequences, and no coevolution
(the host can evolve resistance, but the pollutogen
cannot selectively respond because its reproductive
success is very low or nil in those hosts). In a sense,
this new class of emerging infectious disease is an
extreme form of spillover from a reservoir host (even
if they are not actually or primarily parasitic in their
evolved habitat).
7.8 Concluding remarks
Given the diversity of interactions between
environmental disturbance and infectious disease,
is it possible to generalize about whether these
diseases are increasing or decreasing in association
with environmental degradation? Recent attention
has been given to mass mortalities in marine
systems (e.g. Caribbean sea urchins, Lessios 1988),
phocine distemper virus (Heide-Jorgensen et al.
1992), pilchard mortalities (Jones et al. 1997), and
infectious coral bleaching (Hoegh-Guldberg 1999).
This has led several authors to speculate that disease outbreaks in marine organisms have increased
in recent years (Williams Jr. and Bunkley-Willimas
1990; Epstein et al. 1998; Harvell et al. 1999; Hayes
et al. 2001). Unfortunately, a lack of baseline data
precludes a direct evaluation of this hypothesis.
Ward and Lafferty (2004) developed a proxy
method to evaluate a prediction of the increasing
disease hypothesis: that the proportion of scientific
publications reporting marine disease has increased
in recent decades. Reports of parasites and disease,
normalized for research effort, have increased in
turtles, corals, mammals, sea urchins, and molluscs.
There are no significant trends for reports of disease
in sea grasses, decapods, and sharks/rays (though
disease occurs in these groups). Consistent with the
expectation that fishing reduces parasites, disease
reports have significantly decreased in teleost
fishes. The increase in reports of coral disease is
notable, but this is driven by reports of noninfectious coral bleaching, not reports of infectious
disease. These latter results are consistent with the
general theory that environmental degradation
should increase non-infectious and generalist
diseases and parasites (Lafferty and Holt 2003).
Increasing host populations, such as seen in many
marine mammals, should see increases in most
types of infectious disease, while decreasing populations, such as recently experienced by many commercially fished species of fin fish, crabs, lobsters,
E N V I R O N M E N TA L D I S T U R B A N C E S
and shrimps, should result in decreased prevalences
and intensities, and may even prevent transmission
of inefficiently transmitted infectious diseases with
high host-threshold densities. So, although environmental degradation is occurring at an alarming rate,
an increase in infectious disease is not a necessary
outcome of these changes. Some parasites will
increase, but we expect that many more will
decrease, even to the point of extinction. This may
seem a blessing amidst otherwise sobering expectations for the future. However, before we count loss of
parasites as something to look forward to, we
should consider that parasites play important roles
in ecosystems. Fungal pathogens (Gilbert et al. 1994)
and specialized herbivorous insects (Barone 1998),
for example, are thought to be responsible for
maintaining the high diversity of tropical forest
trees through density dependent mortality of
seedlings close to parents (Janzen 1970; Connell 1971,
see Chapter 8). Although their roles are generally
unseen and little appreciated, the loss of parasites
may create more problems for us than it solves.
While the evidence for global warming is strong,
its ecological effects are not obvious. We are faced
with a difficult confound. Other major factors with
strong effects on infectious disease dynamics are
changing in temporal concert. These certainly
include population increases of humans and some
other anthropophillic species, invasive species that
are now so pervasive in some regions that a parasitediminished homogicene has been established;
economic pressures reducing or eliminating
programmes to decrease transmission of diseases;
loss of top predators—mostly long gone from
terrestrial systems and now severely depleted in
aquatic ecosystems; eutrophication; expanded use
123
of pesticides, antibiotics, anthelminthics; and
herbicides in agriculture; and evolution of drug
resistance by malaria, tuberculosis, and other
important infectious diseases. Interpreting changes
over time simply with climate change will hinder
comprehension of the interactions between disease
and the environment. Analysing these specific
effects is now an important task for ecologists,
parasitologists, and public health investigators.
Given that there are no simple answers to the
questions about how environmental disturbances
will affect parasitic diseases, substantial research
effort will be needed to unravel the complex linkages between these two forces. Until recently, this
has been sparsely supported. The US National
Institutes of Health (NIH) has traditionally funded
few studies that consider the relationship between
environmental degradation and infectious disease
because its mission focuses on human health.
Ironically, the National Science Foundation, which
traditionally funds ecological research, has shied
away from issues related to infectious disease (as
these are perceived to be within the mission of the
NIH). Emerging diseases such as Lyme Disease,
West Nile Virus, and SARS have forced health professionals to consider the ecological context of
infectious disease in a changing world (Aguirre
et al. 2002) (see Chapter 10). Now, both agencies are
aware that an ecological perspective seems necessary to meet these challenges and have recently
combined to fund research through their joint
Ecology of Infectious Diseases programme in the
context of anthropogenic changes. These new
research efforts should considerably expand our
understanding of how environmental disturbances
interact with infectious diseases.
CHAPTER 8
Parasitism, biodiversity, and
conservation
Frédéric Thomas,1 Michael B. Bonsall,2 and Andy P. Dobson3
Sharing parasites has wide range of implications for the structure and
diversity of ecological assemblages. Parasites have the potential to affect
ecosystem structure and function by mediating competition between different
host species, influencing trophic cascades, manipulating coexistence through
life history tradeoffs and impacting on persistence of host species. Parasites
impact on the diversity of ecosystems, and the conservation of threatened
species. Understanding the ecology of shared parasites is essential for
protecting endangered species or ecosystems.
8.1 Introduction
One of the major goals of community ecology and
conservation biology is to identify the ecological
and evolutionary processes that generate, maintain,
and erode biological diversity in ecosystems (Begon
et al. 1990; Tokeshi 1999). Ecologists have long realized that interactions between organisms largely
influence the distribution and abundance of
species. However, while competition and predation
have been traditionally considered as major biotic
determinants of community structure, parasites
have been virtually ignored during most of the history of community ecology.
From the pioneering work of Park (1948) showing that one parasite could change the outcome of
competition between two beetle species, ecologists
now acknowledge the importance of parasites not
only on individual hosts, but also on the population
1
Génétique et Evolution de Maladies Infectieuses GEMI/UMR
CNRS-IRD 2724, Equipe: ‘Evolution des Systèmes Symbiotiques’,
IRD, 911 Avenue Agropolis, B.P. 5045 34032 Montpellier Cedex 1,
France.
2
Department of Biological Sciences, Imperial College London,
Silwood Park Campus, Ascot Berks, SL5 7PY, UK.
3
Department of Ecology and Evolutionary Biology, Eno Hall,
Princeton University, Princeton, NJ 08544-1003.
dynamics and community interactions between
species. Over the past 15–20 years, considerable
progress has been made in understanding the functional importance of parasites in ecosystems.
Numerous theoretical and empirical studies have
shown that parasites, in spite of their small size, are
biologically and ecologically important in ecosystems. As a result, most ecologists and conservation
biologists are, for instance, aware that the introduction or elimination of a parasite in an ecosystem can
strongly affect the interactions between a diverse
range of species in the community, and hence affect
biodiversity. However, the link between parasitology and community ecology is still under construction (see Chapter 1). Given the ubiquity of parasites
and the large spectrum of their effects, understanding how they affect species assemblages and ecosystem dynamics is a central question in conservation
biology. The aim of this chapter is to highlight the
different ways in which parasites have been shown,
or are suspected, to influence biodiversity in ecosystems by influencing different ecological processes.
We begin by considering the effects of species sharing parasites, before examining how parasites might
affect the structure of ecosystems through trophic
interactions and as ecosystem engineers. We argue
that the understanding of life history trait tradeoffs
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is fundamental to the influence of parasites on
species coexistence. We conclude the chapter with a
discussion of the diversity and conservation
implication of parasites.
8.2 Parasites and apparent competition
8.2.1 Basic ideas and general processes
The interaction between two species in an ecosystem can often be influenced by a third species. It is
for instance well known that a predator attacking a
highly abundant prey species can facilitate the
coexistence of two or more prey species (Paine
1966). Parasites can also play this role of mediator
by harming some host species more than others.
Parasites indeed do not usually infect host species
at statistically similar frequencies, and virulence
can differ from one host species to another. As a
consequence, the host species whose fitness is
impaired by parasitism is at a selective disadvantage in competition with a relatively unaffected
species (Fig. 8.1). This influence of parasites
is expected to be more pronounced for closely
related host species than for distantly related
species because the overlap in susceptibility to the
parasite community increases with increasing phylogenetic relatedness (Freeland 1983; Holt and
Pickering 1985).
Whether some of the host species involved in the
competition are totally resistant to infection (cannot
Parasite
absent
S1
S2
Parasite
present
S1
S2
Figure 8.1 Basic process through which parasites are known to
influence communities of free-living species. When the parasite is
absent, the species S1 is dominated by the species S2. However,
because of S2 display a higher susceptibility to the infection or its
consequences, the outcome of the competition is changed when the
parasite is present. The thickness of lines represents the relative
strength of interspecific effects. The size of squares represents the
relative abundance of species in the communities.
125
be infected) or tolerant (suffer few fitness reduction
from the infection) is of importance to understand
the different implications of competition. In the first
case, the differential regulation induced by the parasite (effect on survival and/or fecundity) directly
gives an advantage to the resistant species in
exploitation competition. In the second case, competition also occurs through interference as the
tolerant host species negatively interferes with
other species either by directly transmitting the
disease, or by locally favouring the demography of
the parasite.
Interactions between species mediated by parasites through these basic processes is of considerable importance in nature and must even be
regarded as one of the major types of interaction in
ecological systems, comparable in importance to
direct competition and predation (Price et al. 1986,
1988). Not surprisingly, in addition to ‘apparent
competition’ (Holt 1977), this phenomenon has also
been called ‘germ warfare’ (Barbehenn 1969), ‘biological warfare’ (Price 1980), ‘weapons of competition’ (Holmes 1982), ‘agents of interference
competition’ (Rice and Westoby 1982) and also
‘parasitic arbitration’ (Combes 1995). Both mathematical models and empirical evidence show that
apparent competition mediated by parasites
(and/or its cascading effects) clearly has the potential to influence the structure of ecological communities, the viability of each species within a
community and the potential for new species to
invade a community. Net effects for biodiversity
can, however, be positive or negative. Basically, a
non-specific parasite infecting related host species
in a frequency dependent manner, or a more host
specific parasite with a preference for the competitively superior host species can help maintain a
high host species diversity (Fig. 8.1). Endemic
pathogens and parasites may through this process
truly operate as keystone species, playing a crucial
role in maintaining the diversity of ecological
communities and ecosystems. However, a hostspecific parasite can also have a preference for the
competitively inferior species. In this case the
parasite will be detrimental for biodiversity
driving one or several species to local extinction
(Combes 1996).
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8.2.2 Parasites, apparent competition, and
mathematical models
Williamson (1957) first argued that, in the absence
of other limiting factors, the interaction between
two species sharing a natural enemy leads to a variety of outcomes and often to the exclusion of one of
the species. However, it was a further twenty years
before Holt (1977) first formalized the concept that
prey that share a common natural enemy can be
excluded through these indirect competitive effects
(colloquially termed ‘apparent competition’). For
apparent competition to be manifest, the natural
enemy must be primarily food-limited and have a
numerical response to each prey species.
Formulating this biology leads simply to a set of
coupled ordinary differential equations that are
straightforward extensions of the Lotka–Volterra
predation model. It can be shown that the prey
species that wins out in apparent competition can
be predicted from the population growth rate of the
prey species and the transmission rate of the parasite. In the absence of any other limiting factors, an
apparent competition between two prey species
that share a natural enemy can be expressed as:
dH 1
ᎏᎏ ⫽ r1H1 ⫺ ␣H1P,
dt
dH 2
ᎏᎏ ⫽ r2H2 ⫺ H2P,
dt
dP
ᎏᎏ ⫽ ␣H1P ⫹ H2P ⫺ dpP
dt
where r1 and r2 are the growth rates of prey 1 and 2
respectively, ␣ and  are the parasite transmission
rates on prey species 1 and 2, respectively, and dp is
the mortality rate of the natural enemy. If it is
assumed that H2 is rare, then the invasion criteria for
H2 to invade the interaction where H1 and the parasite are present is simply r2 ⫺ P*
1 ⬎ 0 where P1* is
the equilibrium value of the parasites in the presence of H1 only and is given by P*
1 ⫽ r1/␣. Similarly,
if H1 is rare then the invasion criteria is r1 ⫺ ␣P*
2 ⬎0
where, similarly P2* is the equilibrium value of the
parasites in the presence of H1 only and is given by
P*
2 ⫽ r2/. Coexistence requires that both these invasion criteria be satisfied. However, it can be seen
that if the resident host–parasite interaction is at an
equilibrium (H*, P*) then the invasion criteria can be
expressed as r1/␣ ⬎ r2/ and r2/ ⬎ r1/␣.
It is clear that these two invasion criteria are mutually exclusive and there is no possibility for mutual
coexistence (provided there are demographic differences between the host species). This is known as the
P* rule: the host species expected to win out in
apparent competition is the one that can withstand
the higher parasite attack and maintain a positive
population growth rate (Holt et al. 1994). Apparent
competition is therefore most likely in interactions
where the predator limits host numbers to levels at
which they experience little density dependence. As
such any increases in the host’s carrying capacity is
likely to magnify any effects of apparent competition. Further Holt and Pickering (1985) argue that
sustained coexistence of alternative hosts limited
principally by a shared parasite requires that the
within-species transmission of the disease be greater
than the between-species disease transmission. If
parasites are capable of excluding alternative hosts
then it is possible (and predicted from simple
host–parasite models) that the outcome of shared
parasitism might result in habitat partitioning or
segregation of geographical ranges of hosts.
Relaxing the assumption that only parasitism
limits host growth rate or that the natural enemy
has a positive numerical response weakens the
effects of apparent competition and may introduced ecological processes that foster species
coexistence. In particular, under certain circumstances apparent competition can give way to
apparent mutualism (Abrams et al. 1998). Hosts
that share a common natural enemy can interact
not only through the numerical response, but also
through the functional response of a natural enemy.
If the functional response saturates at high prey
densities (and the natural enemy is limited by factors
other than host consumption) then there may be
positive indirect effects or apparent mutualisms
between hosts. More recently, it has been illustrated
that understanding not only the mean response, but
also the variance in the response of natural enemies
to distributions of hosts can affect the probability of
coexistence. In particular, natural enemy responses
can be either dependent or independent of host
densities. In single pairwise interactions, it is the
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
variability in these two responses that is sufficient
to promote persistence. In contrast under apparent
competitive interactions, it is only the host density
dependent responses that generate sufficient positive covariances in attack or transmission rates
between alternative prey that are sufficient to promote coexistence. Under host density independent
responses the multiplicative variation in density of
the two hosts between patches is insufficient to
overcome the interspecific apparent competitive
effects generated by the natural enemy, and
coexistence is not promoted (Bonsall 2003). Such
mathematical models of apparent competition
predict a number of different outcomes that reflect
the nature of the diversity of shared enemy interactions. It is important to emphasize that changes in
prey abundance through the actions of a nonspecific parasite can lead to a range of indirect
effects that are predicted to enhance or destroy host
species diversity. Understanding these effects is the
challenge of empirical parasite community ecology.
8.2.3 Parasites and apparent competition:
empirical evidence
As mentioned, Park (1948) was the first to show
experimentally that parasites could maintain biodiversity through the effects of shared enemies and
apparent competition. Park examined the competitive interaction competition between two flour beetles (Tribolium castaneum and T. confusum). When the
two beetle species were kept together in the same
containers, T. castaneum usually drove T. confusum to
extinction, suggesting that T. castaneum was the
superior competitor. However, when the sporozoan
parasite Adelina tribolii was also present in the mixed
cultures, the reverse tendency was observed. In fact,
the parasite A. tribolii was simply more deleterious to
T. castaneum than T. confusum and its presence shifted
the outcome of competitive interactions between the
two beetle species. Fifty years later, Yan et al. (1998)
showed in the same system that when another
parasite species was considered (the cestode
Hymenolepis diminuta), a new scenario occurs.
Indeed, the parasite this time benefits the superior
competitor T. castaneum so that its net effect was to
reduce the biodiversity by accelerating the extinction
127
of T. confusum. These studies by Park and Yan clearly
illustrate that, depending on which species is the
most affected by the infection, parasites can be beneficial or conversely detrimental to species diversity.
Although parasitism, by decreasing survival,
may significantly reduce the host population, its
effect on the host reproductive potential can also
affect the population dynamic interactions between
species. Not surprisingly, Jaenike (1995) showed
that apparent competition mediated by parasites is
also possible when the mechanism of differential
regulation parasite-induced affect host fecundity
rather than survival. While the castration induced
by the nematode Howardula aoronymphium is total
on Drosophila putrida, it is only partial (50%) in
D. falleni. As in Park’s experiment, the outcome of
the competition in mixed cultures is inversed in the
presence of the parasite (Jaenike 1995).
Indirect methods traditionally employed to detect
parasite-induced host mortality (Anderson and
Gordon 1982; Rousset et al. 1996) can be useful tools
to study apparent competition in the field. The two
congeneric and syntopic invertebrates Gammarus
insensibilis and G. aequicauda (Crustacea, Amphipoda)
can both be infected with metacercariae of the trematode Microphallus papillorobustus (Helluy 1981). In the
field, however, two distinct infection patterns are
observed between the two amphipod species
(Thomas et al. 1995; Fig. 8.2), suggesting that
M. papillorobustus can act as an important mechanism
regulating the density of G. insensibilis populations
and G. aequicauda. Because the higher reproductive
success of G. insensibilis (Janssen et al. 1979) is offset
by its lower tolerance to M. papillorobustus, the sympatric coexistence of the two amphipod species is
mediated by the parasite (Thomas et al. 1995). A similar scenario of parasitism affecting the competitive
interaction between species occurs with the association between the trematode M. clavifomis and its two
possible intermediate hosts Corophium volutator and
C. arenarium. By having more harmful effects on the
competitively superior species (C. volutator), this
trematode apparently permits the inferior competitor
to persist and hence, help to maintain biodiversity
(Jensen et al. 1998).
Parasitoids (insects lay their eggs and in develop
in, on or near other arthropods), like parasites have
(c)
Adult
(c)
(d)
(e)
400 µm
100 µm
Swimming cercariae
Brain encysted metacercariae
in situ
200 µm
Metacercarial cysts
(b)
60
59
40
60
60
60
60
20
3060 60 60
0
60
60
6060 60
60
60
(d)
6
5
4
87
64
3
2
1
114
30
74
122
132 47
13
31
49
88
54
40
56
42
(f)
30
Variance/mean
(b)
60
10
30
0
60
59
60
20
60
60 60
60 60 60
60
60 60
60
60
(g)
(h)
Variance/mean
100 µm
Mean abundance
(a)
Mean abundance
(a)
20
114
64
10
87
122
132
13
30
0
0
49 54
47
2
4
6
8
0
Length class
88
74 40
56
42
31
2
4
6
8
Figure 8.2 Life cycle of the trematode Microphallus papillorobustus and infection patterns (mean abundance and the variance to the mean abundance ratio) in relation to host size in its two possible
intermediate hosts Gammarus aequicauda (a, b, e, f) and G. insensibilis (c, d, g, h). Life cycle: Adults M. papillorobustus reproduce in an aquatic bird intestine (a). Once a miracidium successfully infects a snail
(b), it reproduces asexually to produce cercariae (c). Infected snails are generally castrated by the parasite. Cercariae, once outside the snail, swim, and crawl on the surface of the mud; Then cercariae infect
a gammarid by penetrating its branchial cuticle. Once inside G. insensibilis, the cercaria drops its tail, crawls toward the amphipod’s brain and encysts in cerebroid ganglions to form a metacercarial cyst (d).
Notes: Inside this cyst is a miniature adult worm that will be released when the enzymes in a bird’s gut digest away the cyst wall. Things are similar when cercariae enter a young G. aequicauda. However,
for unclear reasons, cercariae infecting an older individual of G. aequicauda, encyst in the abdomen instead of the brain. Adult M. papillorobustus, like many adult helminths, live only a few days in the bird
intestine, where they seem not to be associated with any particular disease.
Source: From Thomas et al. (1995). Drawing from Armelle Dragesco.
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
been shown to intervene in apparent competition
processes. For instance, Boulétreau et al. (1991)
showed that the coexistence between Drosophila
melanogaster and D. simulans, normally impossible
(D. melanogaster eliminates D. simulans) become
possible and stable when the parasitoid Leptopilina
boulardi (Cynipide) is present. A slight preference of
the parasitoid for D. melanogaster is apparently
responsible for this phenomenon.
Although there is considerable anecdotal evidence on the role of shared parasites, very few
manipulative experiments have evaluated the population dynamic impact of apparent competition in
structuring ecological assemblages. Using a simple
laboratory system involving the stored product
moth hosts, Plodia interpunctella and Ephestia
kuehniella and their shared parasitoid, Venturia
canescens, Bonsall and Hassell (1997, 1998) showed
how one of the host species is rapidly eliminated by
the action of the parasitoid. In the pairwise host–
parasitoid interactions, the interaction between each
of the moths and the parasitoid (P. interpunctella–
V. canescens, E. kuehniella–V. canescens) were persistence with the populations showing dynamics to a
stable equilibrium. However, in the three species
interaction (P. interpunctella–E. kuehniella–V.
canescens) when the only feasible interaction
between the two moths was via the numerical
response in the parasitoid, one of the hosts
(E. kuehniella) was rapidly eliminated. The parasitoid
is classed as a dynamic monophage (Holt and
Lawton 1993). Through its population dynamic
interactions with alternative hosts, the parasitoid is
monophagous as it drives all but one of its hosts to
extinction. More recently it has been shown, theoretically, that the spatial scale and the foraging decisions by V. canescens were too marginal to allow the
parasitoid to discriminate differences in the heterogeneity of host distributions and promote persistence
of the three species interaction (Bonsall 2003).
8.2.4 Parasites, apparent competition, and
migration
Given the dynamical consequences of shared parasites, it is entirely feasible that parasites could
constitute a major obstacle to migrations and hence
129
affect the success of biological invasions (Freeland
1983). Ecological theory predicts that a new species
will be able to invade an ecosystem only if its susceptibility to local parasites is lower than that of the
related resident species. Because in the novel habitat, parasite species (at least some of them) are
likely to be new for immigrant individuals, the
behavioural and/or immune defences are also
likely to be non efficient for avoiding infection
and/or limiting its detrimental fitness consequences. Selection for resistance in the invading
species may be not possible if the constant arrival of
new individuals dilute the gene pool (Combes
1996). Through these processes, parasites undoubtedly protect many ecosystems from alien invasions.
Although it seems impossible to know exactly how
many invasions failed because of parasites, the protective role of parasites is clearly established. For
instance, areas of North America occupied by
white-tailed deer Odacoileus virginiatus cannot be
colonised by other ungulates largely because of the
presence of the meningeal nematode Parelophostrongulus tenuis. While O. viginiatus, the usual
host of the parasite, is tolerant to the infection,
other ungulate species developed severe neurological disorders when infected (Anderson 1972). As
a consequence, repeated attempts to colonize cervids
(e.g. caribou, elk, red deer, reindeer) systematically
failed in the presence of meningeal worms
(Anderson 1972).
The protective role of parasites against invasions
can also be manifest through the ethology of resident species. Natural selection has indeed favoured
various behaviours aimed at limiting or reducing
the risks of infection (Hart 1994). Loehle (1995)
suggested that infection risks could explain certain
aggressive behaviours expressed by resident
species toward migrants. Because such aggression
increases the level of environmental adversity for
migrants, it increases their probability that
colonizations will fail.
Parasites, however, do not always systematically
protect ecosystems from alien invasions. Instead,
these natural enemies can, under certain circumstances, have dramatic consequences for biodiversity. If infected hosts invade a new area and their
parasites become established, these invasive
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parasites may impact native species if they can
recruit to novel hosts (see also Chapter 7). The
introduction of avian malaria to the Hawaiian
islands remains one of the most famous disaster of
this kind. The mosquito Culex pipiens fatigans was
accidentally introduced into Hawaii in 1826 and
transmitted bird malaria from migrating shore
birds to indigenous birds. Because indigenous birds
were highly susceptible to this new disease, numerous land species which were directly in contact
with the mosquito were also driven to extinction
(Warner 1968). Another dramatic example of these
effects that parasites can have on biodiversity is the
introduction of the Caspian sturgeon Acipenser stellatus and its gill monogean Nitzchia sturionis into
the Aral sea during the 1930s. The populations of
the local sturgeon Acipenser nudiventris were almost
decimated by this parasite (Zholdasova 1997).
Parasites can also indirectly influence the impact
of an introduced species in a novel environment.
Settle and Wilson (1990) reported an interesting
case of invasion facilitated by a parasitoid. In 1980,
the variegated leafhopper Erythroneura variabilis
invaded California’s San Joaquin Valley. Correlated
with this invasion, are the declining populations of
the endemic grape leafhopper E. elegantula. The
parasitoid Anagrus epos (Mymaridae) was known to
be the principal mortality agent in the endemic
species and was also known to parasitize the invading species but at a lower rate. Reasons of this
differential susceptibility relies on the way host
eggs are laid: while the eggs of the endemic species
are inserted just under the epidermal layer of the
leaf, those of the invading species are injected deep
within the leaf and are consequently less accessible
to the parasitoid. During the initial phase of the
invasion, the parasitoid reduced populations of the
endemic host to low levels, allowing invading populations to advance and increase unencumbered by
interspecific competition with the endemic host
species. As the invading species became dominant,
it also contributed to an increasing proportion of
the overall parasitoid population, which in turn
accelerated the decline of the endemic species. In
this case, the parasitoid did not drive the initial
invasion but it did contributed to the final outcome
and the relative abundances of the two host species.
8.3 Parasites, ecosystem stability, and
cascade effect
When a parasite is responsible for the local decline
of one or several species (either through reducing
their survival or their fecundity), we expect some
consequences not only for competitors, but also for
its prey and its predators. If the species affected by
parasitism is a predator, we may for instance expect
the population density of its prey to suddenly
increase at the expense of others with the outcome
being a reduction in local diversity. A spectacular
example is that of an epizootic of sarcoptic mange
(Lindstöm et al. 1994) that decimated the populations of red foxes in Scandinavia and strongly
altered the demography of the small mammals that
are their usual prey. Alternatively, if the species
whose survival (or activity) is impaired by parasitism is a prey species, predators may be expected
to switch to other prey species that would otherwise
not be selected.
More generally, the more a species is functionally
important in an ecosystem, the more likely it is that
a parasite that impairs this species is responsible for
major changes in the ecosystem through cascade
effects. For instance, following the introduction of
the myxoma virus into England, there was a rapid
decline in the rabbit (Oryctologus cuniculus) population, which in turn changed the vegetation patterns
and both invertebrate and vertebrate populations
(Minchella and Scott 1991). Similarly the arrival of
Dutch Elm disease in England had a variety of
consequences for plant and animals communities.
As numerous trees died, the availability of habitats
for number of bird species was also decreased.
However, at the same time, the increase in the
number of beetle larvae in the dead trees resulted in
an increase availability of food for other bird
species (Osborne 1985). Similarly, when a parasite
normally present disappears, the regulatory roles it
had on one or several species also disappear (see
Section 8.6.4 of this chapter for a detailed example).
All these examples illustrate how the interactions
between dominant species in a community may be
largely mediated by parasites and pathogens.
However, Torchin et al. (2002) suggested other subtle ways through which parasites could indirectly
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
influence the impact of an introduced species on
the function and persistence of an ecosystem. When
exotic species exclude particular native species, the
parasitic community linked to that native species
may also be excluded (see also Bartoli and
Boudouresque 1997). Cascading effects resulting
from this phenomenon could in theory be important for a number of ecosystem processes. For
instance in several marshes of the West Coast of
North America, the introduced Japanese snail
Batillaria attramentaria competitively excludes the
native snail Cerithidia californica. Knowing that
C. californica serves as first intermediate host for at
least 18 native trematode species, the local extinction of C. californica means the concomitant extinction of all of these trematodes. As trematodes
frequently have major effects (fecundity, behaviour,
demography, etc.) on the population biology of
their second intermediate hosts (numerous molluscs, crustaceans, fishes), their sudden disappearance might have important repercussions on the
entire ecosystem functioning and stability. The
ecosystem consequences of the loss of a single
species (i.e. one snail species excludes another snail
species) can potentially be strongly amplified by
the interactions of shared parasites.
Parasites, through their debilitating effects on
host species, could in theory influence the foraging
strategy and local abundance of predators (Lafferty
1992; Thomas and Renaud 2001). Indeed, although
predators risk infection when feeding on infected
prey, they also often benefit from enhanced prey
capture (Lafferty 1992; Norris 1999; Hutchings et al.
2000). Parasitized hosts are usually in poorer conditions compared to uninfected conspecifics and are
consequently easier to capture. In addition, many
trophically transmitted parasites adaptively change
the phenotype of their hosts in a way that increases
their probability of being captured by predators
(definitive hosts), making them for instance more conspicuous or less able to escape (Combes 1991; Lafferty
1999, see also Chapter 9). As such these parasites usually cause little harm to definitive hosts (Lafferty
1992, 1999), predators should show a preference for
foraging on such prey (see Lafferty 1992). For
example, Aeby (2002) has demonstrated that the
coral-feeding butterflyfish Chaetodon multicinctus
131
in Hawaii reefs prefer foraging of polyps (Porites sp)
that are infected by the trematode Podocotyloides
stenometra. Infected polyps are easier to capture as
they are no longer able to retract into their
protective coral skeletons. In addition, because
costs of infection are low for C. multicinctus, the
benefits of feeding on infected coral outweigh the
costs associated with parasitic infection. By increasing the accessibility to prey species that are normally difficult to capture, the net effect of
manipulative parasites may be to enhance the
strength of trophic interactions in ecosystems.
Whether there is a positive relationship between
the local abundance of manipulative parasites, and
the richness/diversity of predators frequenting
these habitats is poorly documented but is
undoubtedly an interesting question (Hechinger
and Lafferty, in press).
8.4 Parasites, host life history traits,
and species coexistence
Parasites could in theory play an important ecological and evolutionary role in community ecology
beyond the effects of shared parasitism and ‘apparent competition’ through their influence on host life
history traits and evolutionary trait tradeoffs
(Thomas et al. 2000a). Ecologists readily acknowledge that not only ecosystem traits (e.g. complexity,
stability, productivity) are relevant to understand
species coexistence but that organismal traits (e.g.
body size, dispersal ability, fecundity, timing of
reproduction, etc.) are also highly important (Tokeshi
1999). For instance coexistence based on resource
partitioning is more likely to occur when species
display different life history traits allowing resource
specialization. Temporal segregation of reproductive
periods within a group of species has often been
favoured by selection as it reduces the possibility and
the magnitude of resource competition. Different
sizes or morphologies allowing the use of different
types of resources between closely related species is
often a necessary condition for their coexistence.
Because parasites frequently alter life-history traits
in their hosts, they can, in theory, also have
the potential to play an important ecological and
evolutionary role in community ecology.
PA R A S I T I S M A N D E C O S YS T E M
Parasites are responsible for changes in their host
life history traits by directly exploiting them
and/or by inducing adaptive response from their
host. Parasitic exploitation is per se an important
cause of between-individual or between-population variation in the life history traits such as
fecundity, growth, or survival. Changes in host life
history traits can also be an adaptive response to
parasitism in order to compensate for the negative
effects of parasitism on fitness (Minchella 1985;
Michalakis and Hochberg 1994). For instance, there
are several examples that illustrate that by reproducing earlier when infected by a harmful parasite
(e.g. killer or castrator), hosts may partly compensate for the losses due to the parasite (see, for
instance, Minchella and Loverde 1981; Hochberg
et al. 1992; Forbes 1993; Sorci et al. 1996; Polak and
Starmer 1998; Adamo 1999). Parasites also have the
potential to impose selective pressure on other life
history traits such as reproductive effort (e.g.
Richner and Triplet 1999), dispersal (e.g. Sorci et al.
1994; Heeb et al. 1999), or growth (e.g. Agnew et al.
1999). Under particular circumstances the parental
parasite load can even influence the life history
traits of offspring (i.e. intergenerational effects)
(Sorci et al. 1994).
When traits altered by parasites correspond
directly, or are related, to traits involved in the
coexistence of species, parasites are likely to
interfere with community processes. In fact, several
situations previously assigned to ‘apparent competition’ fall within the scope of this idea (e.g. when
the traits altered in hosts are fecundity or survival).
However, other relevant examples do not correspond to what is classically considered as ‘apparent
competition’. For instance, when a parasite selects
for early investment in reproduction in a given host
species (e.g. Lafferty 1993a), this parasite also has
the potential to alter positively or negatively the
magnitude of the temporal segregation during a
breeding season. Depending on which species is
predominantly affected by the parasite, the resulting competitive interactions may contribute positively or negatively to species coexistence (Thomas
et al. 2000a; Fig. 8.3). Similarly, when temporal segregation between species in a community is maintained by a parasite, the disappearance of such
Parasite absent
A
Offspring production
132
B
Parasite present
A
B
A
B
Timing of reproduction
Figure 8.3 Effect of parasites selecting for early reproductive
investment in their hosts and consequences for species (A and B)
coexistence.
Notes: Top-most graph: parasite absent, coexistence between the two
species; Middle graph: parasite present, selective pressure on species A,
coexistence is favoured; bottom graph: selective pressure on species B,
coexistence is compromised.
Source: From Thomas et al. (2000a).
parasites from the ecosystem could result in an
increase of the magnitude of the competition
between coexisting species.
Dispersal has often been identified as an important
factor that influences the genetic diversity and structure of populations, as well as the probabilities of
regional extinction/colonization. Parasites can influence dispersal in their hosts in different ways. First,
given that a classical consequence of infection is a
reduced activity, parasites probably often impair the
dispersal potential of their host (see, for instance,
McNeil et al. 1994; Thomas et al. 1999b). At a metapopulation level, gene flow is likely to be influenced by
the mean infection rate of the different populations.
Parasites that influence dispersal ability and behaviour undoubtedly control, at least partially, the
level of geographical isolation of populations, and
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
over evolutionary time, could potentially influence
taxonomic diversification. In particular situations,
parasites have been conversely shown to favour
dispersal in host species. A high risk of infection in
a given habitat may indeed select for increased dispersal to avoid future infection (Sorci et al. 1994). In
such a case, parasites would favour gene flow
between host populations.
The net effect for diversity of the selective pressures exerted by parasites on host life history traits
is far from fully understood at the moment. The
examples and ideas presented here however suggest that this area deserves to be examined more
carefully in the future, from both ecological and
evolutionary perspectives.
8.5 Parasites and ecosystem engineering
Ecosystem engineers are organisms, plants, or animals that directly or indirectly modulate the availability of resources to other species, by causing
physical state changes in biotic or abiotic materials
(Jones et al. 1994, 1997). Certain species change the
environment via their own physical structures (autogenic engineers, for example, trees), while other
transform living or non-living materials from one
physical state to another (allogenic engineers, for
example, beavers). Both kinds of engineers modify,
maintain or create habitats within ecosystems (Jones
et al. 1994). Acts of engineering from free-living
species result from traits associated with their phenotype (e.g. morphology, behaviour). Parasites can
interfere with these processes as they alter the phenotype of their host. In fact, parasites can either impact
on existing ecosystem engineers, or act as engineers
themselves (Thomas et al. 1999a). These different
cases of interactions between host traits that are
altered by parasites and those that are involved in
engineering acts are illustrated in Fig. 8.4.
8.5.1 Infection of ecosystem engineers
Infection of ecosystem engineers does not necessarily have community consequences because host
traits modified by parasites may have no link with
engineering functions (Fig. 8.4(a)). In other situations, parasites alter host traits that are directly
(a)
Infection
H
(b)
H
(c)
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H+P
Infection
H+P
Infection
H
H+P
: Phenotypic trait having no engineering function;
: Phenotypic trait having an engineering function;
: Trait altered by parasites.
Figure 8.4 Interactions between traits altered by parasites and traits
involved in engineering processes.
Source: From Thomas et al. (1999a).
related to engineering functions present in the host
(Fig. 8.4(b)). By altering key phenotypes in ecosystem engineers, parasites interfere with their
engineering function and hence on community
processes. There are numerous examples of parasites
interfering with engineering function. For instance,
numerous free-living species are autogenic engineers because they directly provide through their
growth space for other organisms. Any parasites
that reduce or enhance the growth of these hosts
will affect the trait (host size) involved in the engineering process. For instance, gammarids G. insensibilis, infected with the trematode M. papillorobustus
(Fig. 8.2) have a longer intermoult duration than
uninfected ones, and usually harbour higher numbers of epibionts on their cuticle (F. Thomas, unpublished data). Furthermore, numerous acts of
engineering from free-living species result from
their activity level (e.g. woodpeckers and beavers,
Jones et al. 1997). As activity is often reduced in parasitized hosts, parasites are likely through this simple effect to interfere with engineering processes.
We could for instance imagine that gastrointestinal
nematodes which frequently alter the appetite of
herbivores (e.g. Arneberg et al. 1996) will have an
(indirect) impact on plant communities.
The idea that by shifting the phenotype of their
hosts from one state to another, parasites could create
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new resources for other species is well illustrated by
the association between the cockle Austrovenus
stutchburyi, the trematode Curtuteria australis
and various epibiotic invertebrates (Thomas et al.
1998a). In the sheltered shores of New Zealand,
A. stutchburyi lives just under the surface of the mud
and can be considered as an autogenic engineer as
its shell is the only hard substrate where invertebrates like limpets (Notoacmae helmsi) and sea
anemones (Anthopleura aureoradiata) can attach
(Fig. 8.5(a)). The trematode C. australis favours its
transmission to oystercatchers by altering the
behaviour of cockles, making it unable to burrow
under the surface of the mud like unparasitized conspecifics. Given the important ecological differences
(e.g. humidity, temperature, light, etc.) between living under or above the surface of the mud, it is realistic to consider that manipulated cockles could
correspond to a new kind of substrate for invertebrates. Limpets which are normally outcompeted
(a)
for space on burrowed cockles by sea anemones,
significantly prefer surface cockles (Thomas et al.
1998a) (Fig. 8.5(b)). Infected cockles not only provide an exposed surface suitable for grazing, they
are also less occupied by anemones because of their
lower resistance to desiccation at low tide. Using the
terminology of Jones et al. (1994), the trematode
C. australis is an allogenic engineer as it turns living
material (the cockle) from one physical state
(buried) into a second physical state (surface). This
act of engineering alters both the availability and
the quality of habitats for invertebrates. The net
effect here is to reduce competition for space
between invertebrates and because of this, the parasite probably facilitates the local coexistence of
limpets and anemones. Many trematodes have been
shown to impair the burrowing ability of their molluscan hosts (see Lauckner 1987). It is not known,
however, whether similar behavioural changes
induced by parasites in comparable ecological contexts yield the same ecological consequences.
Beyond this specific study, such questions remain
essential before generalizations can be made.
8.5.2 Parasites as ecosystem engineers
(b)
Infected cockle
Uninfected cockle
Figure 8.5 The cockle Austrovenus stutchburyi with the two most
common invertebrate species living on its shell, the limpet Notoacmea
helmsi and the anemone Anthopleura aureoradiata (a)—illustration of
the effect of trematode infection on the fouling community (b).
By altering particular traits of their hosts, parasites
can be responsible for habitat creation (i.e. they give
rise to an engineering function that did not previously exist) (Fig. 8.4 (c)). For instance, in the association between the crab Carcinus maenas and its
crustacean parasite Sacculina carcini (Rhizocephala),
the parasite usually stops the moulting process of
its host. Because of this important physiological
change, the carapace of crabs becomes a more permanent substrate for fouling organisms (serpulid
polychaetes, barnacles, etc.) compared to that of
non-infected crabs that moult regularly. More generally, because free-living organisms constitute
themselves as an ecosystem for numerous parasite
species, any parasite modifying the host is potentially an ecosystem engineer with a functionally
important role in the parasite community.
Engineering processes can typically have both positive and negative effects on species richness (Jones
et al. 1997). This is nicely illustrated in the association
between the crustacean gammarid G. insensibilis, the
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
trematodes M. papillorobustus, Maritrema subdolum,
and the nematode Gammarinema gammari. As seen
before, the trematode M. papillorobustus increases the
vulnerability of gammarids to predation by aquatic
birds (definitive hosts of the parasite) by strongly
altering their behaviour (positive phototactism,
negative geotactism, and an aberrant escape behaviour, Fig. 8.2). As this change is major, it is realistic
to consider that this parasite turns gammarids from
a phenotype A (normal behaviour) to a phenotype
B (altered behaviour). As these new properties of
manipulated gammarids affect infection risk, other
parasites can have common or conversely conflicting interests in exploiting phenotype A or phenotype B gammarids. The second trematode species
M. subdolum which also finishes its life cycle in
aquatic birds prefers to infect phenotype B gammarids (Thomas et al. 1997). The cercariae (infective
stage) of M. subdolum actively swim in the water
column where they are more likely to encounter
phenotype B gammarids (Thomas et al. 1997).
If shared interests exist between the manipulator
(M. papillorobustus) and this ‘hitch-hiker’ parasite
(M. subdolum), there is conversely a clear conflict of
interest between the manipulator M. papillorobustus
and the nematode G. gammari. Indeed, the nematode uses amphipods as a habitat and source of
nutrition, not as a ‘vehicle’ to be transmitted to
birds. As expected, there is evidence that the nematode prefers phenotype A gammarids (Thomas et al.
2002). There is also the suggestion that the nematode ‘sabotages’ the manipulation exerted by
M. papillorobustus, turning back gammarids from a
phenotype B to a phenotype A (Thomas et al. 2002).
A final example serves to illustrate that, in natural conditions, the effects of parasites as ecological
engineers leads to a complex set of effects as several
processes can occur simultaneously. Mouritsen and
Poulin (2002) reported an example of dramatic
change in an intertidal community resulting from
the effects of shared parasitism and host mortality,
ecosystem engineering and cascade effects. Due to
trematode infections, the amphipod Corophium
volutator disappeared from Danish mud flats. This
crustacean, because of its tube-building activity,
played a major role in stabilizing the substrate. The
local extinction of this allogenic engineers allowed
135
rapid sediment erosion and important changes in the
particle size composition of the mud flat, which in
turn induced major changes in the diversity of infaunal invertebrates and finally the macrofaunal species.
Although there are a range of systems in which
either common interests or conflicting interests exist
between parasite species sharing the same invertebrate host population, studies on the community
ecology consequences of this phenomenon remain
relatively rare (see also Poulin et al. 1998, Lafferty
et al. 2000, Outreman et al. 2002). Parasites can
clearly have important effects on communities
through their roles in engineering process. Knowing
that most, if not all, free-living species organisms
harbour parasites and knowing that a variety of
host traits are altered by parasites, this new area of
research at the junction of ecology and parasitology
appears promising. Clearly, further empirical and
theoretical studies on this subject are needed.
8.6 Parasite diversity and conservation
biology
8.6.1 The abundance of parasites
The diversity and abundance of parasites is
remarkable: for example, at least 2000 species of
nematodes have been named but there may well
exist 10 or 100 times this many species of nematodes, most of which still have yet to be classified
(Poulin 1996b). Evidence from the phylogeny of
nematodes illustrates that parasitism is something
that has evolved many times even within this large
order of organisms (Anderson 1988; Adamson and
Caira 1995). Even within the major families of
nematodes, we find that parasitism has evolved
multiple times. Parasitism is a common way of life
among other phyla of worms: all species in the
trematodes, monogeneans, cestodes, and acanthocephala are parasitic. With the exception of the
monogeneans, all species in these taxa have complex life cycles in which two different hosts species
are parasitized sequentially. Parasitism is also a
very common life form in many of the protozoans,
the viruses, bacteria, and fungi. Peter Price was one
of the first people to make a conservative estimate
of the proportion of all known species that are
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parasitic; by including sucking arthropods (an
important analogy which we will return to later),
he concluded that around 50% of species are parasitic (Price 1980). This work was more vigorously
formalized by Cathy Toft, who formally counted
numbers of parasitic and non-parasitic species in all
known phyla (Toft 1986). This estimate also suggests that as many as 50% of species are parasitic.
Some of the major advantages of a parasitic mode
of life are emerging from life history studies of parasites (Calow 1979; Skorping et al. 1991).
Comparative studies of nematodes illustrate that
the normal rules of allometric scaling and assimilation efficiency have to be reconsidered when we consider parasites (Skorping et al. 1991; Arneberg et al.
1998b; Morand and Sorci 1998). In contrast to most
free-living animals, selection for increased body size
in parasitic nematodes leads to both increased
longevity and fecundity. This creates the potential
for parasites to become ‘Darwinian demons’.
We can obtain some estimate of the ubiquity of
parasites by trying to estimate the number of parasitic worms associated with any population of freeliving vertebrates. If we briefly survey published
data for 50 different species of North American
mammals we find that on average a mammal will
contain 400 worms from four different taxa, trematodes, cestodes, nematodes, and acanthocephalans.
At the population level there are on average
10 species of parasitic worms associated with any
one population of vertebrates (Dobson et al. 1992b).
This parasitic diversity is roughly evenly distributed among the trematodes, cestodes, and nematodes, with about 100–150 individuals of each,
divided between two species of trematodes and cestodes, and often five species of nematodes.
Acanthocephalans are less ubiquitous, but at least
one species is associated with every other host population. This suggests that most free-living vertebrates will be parasitized by at least one parasitic
worm species during the course of their life, many
will harbour a community of parasitic organisms.
More detail can be added to this picture by looking at some data put together by Clive Kennedy, Al
Bush, and John Aho (Kennedy et al. 1986b), who compared the species richness of helminth communities
in fish, birds, and mammals. Their work suggests that
fish have on average one or two species of parasitic
helminth in them, birds may have somewhere from 2
to 10 species of parasitic helminths, and mammals
may have somewhere between 8 and 19 species of
parasitic helminth. If we look at the actual numbers,
then fish will contain anywhere between 2 and 100
worms per host, birds may contain anywhere
between 20 and 1000 worms per host, and mammals
may have anywhere between 10 and 50,000 worms
per host. This implies that most populations of vertebrates, are effectively operating as a metapopulation
of patches that serve as resources for parasitic
helminths, a theme we will explore further below.
8.6.2 Host–parasite models as metapopulation
models
Models for parasite–host communities are related to
those for metapopulations of organisms in patchy
environments. Indeed the simplest host–parasite
model we could write would have a host population of constant size divided into susceptible and
infected hosts. This model is identical to the classic
Levin’s population model (Levins and Culver 1971).
The classic (SIR susceptible, infected, and recovered) epidemiological models (Kermack and
McKendrick 1927) are a simple extension of this that
include an extra category of patch, those that were
previously occupied, but are now resistant to further occupation. The other major modification of
host–parasite models is that they consider the vital
dynamics of the hosts that are patches of habitat for
the parasites and the impact that the presence of the
pathogen has on these birth and death rates. The
models used to describe parasitic helminthes add
considerably more detail in that they consider, not
whether a patch is occupied, but the numbers of
individuals of each species occupying each patch,
these are usually described by a series of frequency
distributions. It is possible to compare the structure
of a range of different host–pathogen models with
those for metapopulation models. This suggests that
all these models describe a spectrum of complexity
and detail that starts out with the basic models first
described by Levins and Culver (1971), and then
passing through different types of models for
host–parasite systems (Dobson 2003).
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
It is important to notice here that a large number
of ‘free-living’ organisms will have population
structure and dynamics that correspond to one of
the frameworks previously described. For example
the fish and invertebrates that occupy different
parts of a coral can be considered as organisms that
use patches of coral as habitat. Like parasitic
helminths they may reduce the fitness of the coral,
but their fitness will in turn also be dependent
upon the dynamics of the coral and the ability of
their offspring to locate a new patch of coral to colonize. Many insects that feed on plants, or even carrion, will also have a similar population dynamic
structure (Ives and May 1985; Anderson 1989). The
factors that determine community composition and
relative abundance in these communities will be
similar to those in the host–pathogen models: the
vital dynamics of the plant hosts, the statistical distribution of each insect species across the plant population, and the birth, death, and dispersal rates of
the different insect species.
8.6.3 Fungal pathogens and forest diversity
If parasitism is so ubiquitous in the natural world,
and parasites have the potential to regulate or alter
the dynamics of their hosts, then this implies they
may play subtle and important roles in food webs
(see also Chapter 4) and may even make significant
contributions to indirect competitive interactions
between species (see Section 8.2 of this chapter).
Work by Augspurger’s on the role of fungal
pathogens in tropical forests illustrated that fungal
pathogens have the potential to create spatially
local patterns of frequency dependent recruitment
(Augspurger 1983, 1984a). Janzen and Connell had
posited that a mechanism of this form might be
important in mediating the coexistence of different
tree species in tropical forests (Janzen 1970; Connell
1978). Augsburger’s work showed that rates of
seedling death were significantly higher in the
vicinity of the parent tree than they were at a distance removed from the tree (Augspurger 1984b).
The majority of the deaths occurred in shaded
regions where ‘damping-off’ diseases caused by
fungal pathogens were the main source of mortality. Recent work on black cherry has illustrated that
137
similar effects may be occurring in temperate
forests (Packer and Clay 2000).
The spatial dynamics of these systems can readily be modelled in one dimension. First assume that
the seeds produced from a tree decline exponentially in abundance with increasing distance from
the tree. When these tree seeds germinate their
mortality is determined by whether they are
infected with a fungal pathogen. Their probability
of acquiring the pathogen is a simple function of
the density of infected individuals in their immediate vicinity. If we assume that we can divide the
area around the parent tree into an array of
‘patches’ within which pathogen transmission
occurs, then we can describe the dynamics of the
fungal pathogen in each patch by the magnitude of
its basic reproductive number, R0.
S
R0 ⫽ ᎏᎏ.
( ⫹ ␣)
Here S is the density of seeds in a patch,  is the
transmission rate of the pathogen, is the intrinsic
rate of seedling mortality, and ␣ is the additional
mortality due to infection with the fungal
pathogen. Within any patch the proportion of seeds
that survive infection (SS) is approximately given
by the following expression
SS ⫽ e⫺R0.
It is then relatively trivial to determine the pattern of recruitment of surviving seedlings at different distances from the parent. This mechanism
produces a classic ‘Janzen–Connell’ recruitment
curve. The high abundance of seedlings close to the
tree produces high levels of disease that minimize
their chances of recruiting. Seedlings are only able
to survive at distances where seed abundance has
fallen to sufficiently low levels that the pathogen
dies out. Providing the fungal pathogen is specific
to one host species then individuals of other species
can recruit into these areas. It is important to notice
that we are again dealing with a threshold phenomena, recruitment of seedlings can only occur at
densities where the basic reproduction rate of the
pathogen is less than unity. If seed production
varies from year to year, then seedlings will tend to
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PA R A S I T I S M A N D E C O S YS T E M
recruit closer to the parent tree in years of low seed
abundance, and further from the tree in years when
seed crop is high. Here, it is interesting to speculate
about how the recruitment patterns of tropical trees
might be affected by changes in the abundance of
species that feed on seeds. In areas where these
species have been lost due to hunting, then seed
abundance on the ground will increase leading to
recruitment at greater distances from the parent
tree. Alternatively, if humans harvest seeds at high
levels, then seedling recruitment will occur closer
to each tree and the potential for other trees species
to establish will decline.
One further speculative idea concerns the role
that mycorrhizal fungi may play in controlling
plant pathogens. Although most studies emphasize
the role that mycorrhizae play in helping plants to
assimilate nitrogen, there is also some evidence that
they may also help suppress pathogens (Marx 1972;
Allen 1991). If mycorrhizae evolved this ability in
situations where pathogens caused a Janzen–Connel
effect, then it should be possible for a single species
of tree to dominate a community. As this would also
lead to a tree’s fitness being more directly associated
with its net rate of seed production, then it may also
allow large-scale mass seeding events such as masting to evolve. Plainly there is much still to be
explored in this area.
There is also increasing evidence that parasitic
nematodes play an important role in plant communities. Recent work by Van der Putten’s succession in
dune grass systems has shown that plant specific
nematodes play an important role in reducing the fitness of different successional species (Van der Putten
et al. 1993; Van der Putten and Van der Stoel 1998). A
particularly nice twist to this tale is that species that
enter the succession at a later stage are resistant to
the nematode pathogens of species that have become
more abundant at earlier stages of the succession.
The models described above could be readily
modified to examine this effect in more detail.
8.6.4 Rinderpest in East Africa
There have been relatively few studies of the
impact that pathogens have at the ecosystem level.
One enticing example comes from studies of
rinderpest virus in East Africa (Sinclair 1979b;
Plowright 1982; Dobson 1995a,b). Rinderpest is a
morbillivirus that is closely related to canine distemper and human measles (Plowright 1968). The
evolutionary split between the three pathogens
occurred between 3000 and 5000 years ago, most
likely as a consequence of the domestication of cattle and dogs (Norrby et al. 1985). Rinderpest has
caused cattle plagues in India and Europe since at
least the dark ages, there are no records of its presence in sub-Saharan Africa until the great pandemic
of 1890–98. This was initiated when infected cattle
were accidentally shipped into Africa during the
Italian Mesopotanian military campaign (Plowright
1982). The virus quickly established in the local cattle population and spread from here into the wild
artiodactyls. Historic records suggest that 80% of
the populations of some wild ungulates perished in
the pandemic that took 10 years to spread from the
Horn to the Cape of Africa. Throughout the first
half of the last century the presence of rinderpest
prevented the development of a viable cattle industry in Africa and continued to cause epidemics in
both wild species and domestic herds (Simon 1962;
Branagan and Hammond 1965). The pioneering
Serengeti wildebeest studies of Lee and Martha
Talbot found that more than 40% of wildebeest
calves died of rinderpest during their first months
of life (Talbot and Talbot 1963), those calves that
survived were then immune from further infection.
This situation is directly analogous to measles in
malnourished human populations.
A viable rinderpest vaccine was developed in the
late 1950s and it was hoped that this would at least
allow the cattle population to be protected from
outbreaks that were maintained in the wildlife
reservoir. Wide-scale vaccination of cattle produced
a remarkable response in the wildlife populations
of East Africa (Plowright and McCullough 1967;
Plowright and Taylor 1967). Although only cattle
were vaccinated the disease disappeared from the
wild species, implying that cattle were in fact the
main reservoir! The removal of rinderpest led to a
massive eruption of both wildebeest and Cape buffalo populations, the two wild species that were
most susceptible to the virus. In the Serengeti,
wildebeest numbers increased from around
PA R A S I T I S M , B I O D I V E R S I T Y, A N D C O N S E R VAT I O N
200,000 to 1.5 million (Sinclair 1979b). Buffalo
populations increased by a factor of four to five and
their range expanded into areas such as Ngorongoro
crater, where no previous knowledge of their
presence existed (Fosbrooke 1972).
Increases in the abundance of ungulate species led
to an increase in the density of carnivores, particularly lions and hyenas. These increases in abundance were matched by decreases in the abundance
of gazelles, most likely due to increased predation
pressure (Dublin et al. 1990; McNaughton 1992).
The most dramatic declines occurred in the wild
dog population whose numbers declined from
around 500 to eventual local extinction (Burrows
et al. 1994). While competition with hyenas is the
most likely mechanism producing this effect (Creel
and Creel 1996), it is interesting to speculate upon
the role that disease may have played. A significant
crash in the wild dogs population was caused by a
distemper outbreak. Plowright recorded that when
he developed the rinderpest vaccine in Nairobi
they disposed of dead cattle by supplying them to
the local dog owners (Plowright 1968). Distemper
effectively disappeared from the domestic dog population at this time! This implies that exposure to
rinderpest in infected carcasses may cause crossimmunity to rinderpest in canids. It may be that
loss of rinderpest from wildebeest increased the
susceptibility of wild dogs to distemper (Dobson
and Hudson 1986). Further evidence in support of
this comes from the recent outbreak of distemper in
the Serengeti lion population (Roelke-Parker et al.
1996). The outbreak was initiated by an epidemic in
the domestic dog population in the lands that surrounds the Serengeti, it caused the lion population
to decline by almost a third before the virus died
out. It has led to a large-scale programme to vaccinate the domestic dogs around the park in order to
prevent a future outbreak.
All of this suggests that rinderpest can act as a
keystone virus in the Serengeti ecosystem. Although
there was never more than a kilogram of rinderpest
in the entire ecosystem, it had a major direct, or
indirect impact on most of the large vertebrates
(McNaughton 1992; Dobson and Crawley 1994).
Furthermore, the changes in the numbers of
139
artiodactyls would certainly have had an impact on
grass that is the primary food of these species. There
is even evidence to suggest that the decline in
browsers, particularly impala during the first pandemic, may have allowed a large recruitment pulse in
many tree species (Prins and Weyerhaeuser 1987;
Prins and van der Jeugd 1993); the acacia stands in
many parts of the ecosystem are remarkably even in
their age and size distribution.
8.7 Concluding remarks
In conclusion, it is hard to imagine what natural
communities and ecosystems would be like without shared parasites. Even if diseases and parasites
have been undoubtedly responsible for a number of
extinction (especially on islands), they also play in
other situations a crucial role in maintaining biodiversity. How should conservationists manage parasites and pathogens? Although wildlife managers
are increasingly aware of the roles played by parasites in ecosystems, at the moment we are far from
an answer to this question. In particular situations,
concrete actions have been attempted for instance
in order to minimize disease risks in endangered
species through reducing the population size of a
reservoir population or through vaccination programmes (see Cleaveland et al. 2002 for a review).
Some attention has also been devoted to the problem of disease risks associated to wildlife translocations (Cunningham 1996). These examples
provided useful information but they remain
sparse. In addition, generalizations are difficult to
make at the moment because despite broad similarities, a close look at each situation often shows that
the ecological or political context differ substantially. Finally, the problem of protecting endangered
species from infection is only a specific and an
extreme case of conservation problem. The challenge for parasitologists and conservationists is
also to understand the ecological roles played by
parasites, so as to understand which ecosystem
functions would be lost if certain parasites would
disappear. Sooner or later, such kind of research
should logically yield to the conclusion that some
parasites might need conserving!
CHAPTER 9
Subverting hosts and diverting
ecosystems: an evolutionary
modelling perspective
Sam P. Brown,1 Jean-Baptiste André,2 Jean-Baptiste Ferdy,2 and
Bernard Godelle2
Through a focus on the behavioural and physiological interactions among
parasites and their hosts, we consider how within-host and among-host
ecosystems are shaped by parasite strategies. Furthermore, we consider how
these resultant ecosystem structures can feed back on parasite strategies via
natural selection. We link our discussion to a diverse range of empirical
systems and theoretical approaches.
9.1 Introduction
Most organisms are parasites. If an organism is not
a parasite, then it harbours parasites, as do many
parasites themselves. To make such broad claims, it is
necessary to take an inclusive view of the concept of
parasitism. In a hangover from the taxonomic focus of
much nineteenth-century zoology, the term ‘parasite’
has come to be associated with the protozoan and
metazoan occupants of free-living animal hosts, with
a particular focus on helminth worms (e.g. Cox 1993;
Wakelin 1996; Poulin 1998a). In the light of this continued taxonomic bias, it is of interest to note that the
word parasite stems from the Greek parasitos, literally
‘to eat at another’s table’ (Oxford English Dictionary,
2nd edition). This definition has several important
merits: first, it views parasitism as a relationship,
rather than as a taxonomic category. Second, it
illustrates that this relationship takes place in a social
context. Furthermore, it suggests that parasitism can
occur within—as well as between—species.
1
Department of Zoology, University of Cambridge, Downing
Street, Cambridge CB2 3EJ.
2
Laboratoire Génome, Populations, Interactions, Adaptation,
UMR 5171, USTL-CC 105, Bât. 24, Place Eugène Bataillon, 34095
Montpellier Cedex 5, France.
The significance of the social context of parasitism
is easily overlooked, yet is central to its origins
and continued existence. Cooperative synergies
among distinct biological individuals underlie all
the major increases in complexity in evolution
(e.g. genes to cells, protozoans to metazoans,
individuals to societies; Maynard-Smith and
Szathmáry 1995; Keller 1999). Yet simultaneously
these cooperatively driven increases in complexity
create increased opportunities for parasites, or
cheats. The image of ‘cheats’ provides an interesting working definition of parasites—organisms
that give less than they take in interactions with
other organisms.
These social interactions with other organisms—
both hosts and other parasites—can have great
impacts on the ecosystems that these organisms
comprise. Parasites divert some of the energy that
flows through ecosystems. We shall consider in this
chapter that the body of an individual host is the
first ecosystem parasites live in, and that this host is
itself part of a larger ecosystem. At the first level,
parasites will distort or even completely hijack the
body of their host (by manipulating host physiology, behaviour, life-history traits, etc. see OdlingSmee et al. 2003 ‘niche construction’) in order to
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S U B V E RT I N G H O S T S A N D D I V E RT I N G E C O S YS T E M S
fulfil their own ends. At the second level, parasite
manipulation of the host physiology can have profound consequences on ecosystem structure at
large. We shall then survey the conditions promoting adaptive manipulations of this global ecosystem. Finally, at this larger scale, the community of
parasites constitute an ecosystem, composed of distinct ecological niches, and within which competition occurs. We shall then survey how the existence
of distinct niches for parasites at this scale might
alter the evolution of transmission modes and
virulence in parasites.
Studies at these three scales are mostly theoretical.
Giving an exhaustive review of the mathematical
techniques these surveys require is beyond the scope
of this chapter. The interested reader should find
useful references within the text; boxes should
provide some clues to understand important ways
of approaching parasitism with an evolutionary–
ecological approach.
9.2 Parasite manipulation of host
phenotype
The first ecosystem that is transformed by parasites
is the body of their host. The most illustrative
examples of such effects are the so-called ‘manipulators’, exemplified by dramatic modifications of host
behaviour (see below). However, in this chapter we
wish to give a wider definition of the manipulation
concept to include all host–parasite systems where
the parasite adaptively brings about physiological,
morphological, or behavioural changes in the host to
promote its own fitness, either through an increase
in transmission rate and/or persistence time (Brown
1999). Table 9.1 summarizes with examples the scope
of our manipulation concept; the various effects are
classified according to two poles. The first corresponds to the cases where the parasites control the
overall properties of their infection (the infection
being the product of the interaction host ⫻ parasite):
the parasites manage the infection’s physiology in
order to turn the host’s body into the best parasite
transmitter. The second pole corresponds to the
more spectacular cases where the parasites affect
some traits specific to the host (behaviour, life
history traits), these last cases being traditionally
141
Table 9.1 A broad classification of host manipulation: from
management of infection physiology toward manipulation of host
phenotype
Management of infection physiology
1. Resource intake from host tissues and dispersal (e.g. via tissue lesions
caused by microparasite secretions; Robson et al. 1997; Williams et al.
2000).
2. Immune escape by antigenic variation (genetic or plastic; Moxon et al.
1994).
3. Immune escape by suppression of host immunity (e.g. virus involved
in chemokine mimicry; Murphy 2001).
4. Resource defence against competitors by concomitant immunity;
Brown and Grenfell 2001; Brown et al. in prep.)
5. Manipulation of host life history traits (size, reproduction; references
in Kuris 1997).
6. Manipulation of the host’s relationship with other organisms (e.g.
increased susceptibility to predation through behavioural alterations
caused by macroparasites in intermediate hosts; references in Poulin
1994a, 2000; Thomas et al. 1998a)
Manipulation of host phenotype
referred to as ‘host manipulation’. Of course there is
no clear-cut separation between these two poles but
only a continuum of manipulations; for convenience
we however separate their descriptions below into
two subsections.
9.2.1 Parasite administration of infection
physiology
In simple epidemiological terms, the adaptive
rationale for manipulation is to increase either the
transmissibility or the expected length of infection:
the aim of parasites being to transform the body
of their host into the best parasite transmitter (see
Box 9.1). In microparasites (parasites that replicate
for several generations inside their hosts and attain
large population sizes, that is, bacteria, viruses, and
protozoa, see Anderson and May 1979), the mechanism of this ‘transformation’ implies the replication, mutation, and death of a large number of
microscopic entities: the individual microparasites
and immune cells. The management of host physiology is therefore a matter of rates and numbers,
which is widely open to mathematical modelling.
In macroparasites, this transformation implies
different mechanisms, but the same questions are
nevertheless raised.
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PA R A S I T I S M A N D E C O S YS T E M S
Box 9.1 Management of infection physiology for maximal overall transmission
1. A parameter of infection maximized by evolution
Parasite renewal rate per generation (Anderson and May 1979; van Baalen and Sabelis1995):
= Paraste transmissibility
= Natural death rate of the host
where = Virulence of infection
= Immune clearance rate
B=
,
++
2. Optimisation of infectious process
Host
Infectious process
Parasite
Parasite traits :
Replication rate, tissue
preferences, immune interference,
mutation rate, dispersal rate,
Host traits :
Immune properties, molecular
receptors, behaviour…
Example:
Parasite
replication rate
Host immune
properties
Infectious dynamics
Transmissibility
Virulence
Clearance
Space of reachable phenotypes for (, , )
Graphical presentation:
Reachable
phenotypes
Optimal strategy:
Maximal B
++
S U B V E RT I N G H O S T S A N D D I V E RT I N G E C O S YS T E M S
In a first approach, the infectious process can be
extremely simplified; one simply considers that the
host ⫻ parasite interaction is characterized by an
‘intensity of infection’, which is optimized by the
parasite (within the limit imposed by the host) in
order to maximize its transmission rate without
harming too much the host. This problem, known as
the ‘evolution of virulence’, has led to a large number of theoretical developments (e.g. Anderson and
May 1979; May and Anderson 1979; Levin and
Pimentel 1981; Bremermann and Pickering 1983;
Frank 1992, 1996; Bull 1994; van Baalen and Sabelis
1995; Gandon et al. 2001). However, it may be often
useful to describe more accurately the within-host
infectious process, and to understand how such
processes are shaped by natural selection exerted on
parasites. In a simple situation, parasites replicate
inside a host considered as a uniform environment,
and are killed by replicating immune cells; the
course of their infection is characterized by a peak
dynamic. Natural selection exerted on the parasite
optimizes the infection dynamic through the parasite’s replication rate (several works have explored
this case; Antia et al. 1994; Ganusov et al. 2002;
Gilchrist and Sasaki 2002; André et al. 2003). In
more realistic situations, parasites express habitat
preferences within the heterogeneous within-host
environment, that is, their affinity with various host
tissues is under the pressure of natural selection.
The course of infection is characterized by the
dynamics of the parasite’s density in each host
tissue. Particular tissues may serve as entries inside
the host’s body; others as reservoirs of parasites,
protected from the action of immunity (the cerebrospinal fluid for instance); some others may be the
richest location of nutrients necessary for parasite
growth and replication (for instance the digestive
tube or the blood); and others may be best suited for
dispersal from the host (for instance, the respiratory
tract or the seminal fluid). The evolution of a
parasite’s strategy of host exploitation when several
ecological niches are present inside the host (e.g.
several tissues) has rarely been considered explicitly
in models (but see Koella and Antia 1995). This
question becomes even more intricate if several
parasite strains can infect the host independently or
if mutants appear during the infection and invade
143
new host tissues. This phenomenon could be for
instance involved in the rare appearance of very
virulent meningitis owing to the invasion of the
cerebrospinal fluid by Neisseria meningitidis usually
carried asymptomatically in the nasopharynx
(Levin and Bull 1994; Richardson et al. 2002), or in
the development of AIDS owing to HIV (Tersmette
et al. 1989; Schuitemaker et al. 1992). In all these
cases, the infection must be considered as a whole
ecosystem undergoing development through reproduction, mutation, migration inside the host, and
niche specialization.
Parasite behaviour can also vary during the
course of infection. The evolution of parasite strategies in this case can be investigated with ‘optimal
control theory’. Sasaki and Iwasa (1991) use this
technique to model a situation where the parasite
can modify its replication rate during the course of
infection, while Koella and Antia (1995) consider
also the evolution of the parasite’s investment in
dispersal. In both cases, it is shown that under a
large number of circumstances the parasite could
be selected to change its behaviour in the course of
infection, switching from slow-replicating to fasterreplicating phases. Besides, in biological terms, it
is well known that the expression of bacterial
virulence factors (permitting resource intake from
the host and in turn replication) is often plastic and
controlled by a system of communication among
bacteria called quorum sensing (Williams et al.
2000). The ‘assault’ of bacteria on its host can
hence be synchronized and conditional on a high
density. Brown and Johnstone (2001) have built
a kin selection model to study the evolution of
such a conditional strategy (see discussion below
concerning the kin selection aspect of this question,
and Box 9.2).
Parasites also control the course of their infection
through their rate of antigenic variation, permitting
an escape from the adaptive immune system of
their host. The mutation rate of parasites evolves to
maximize the length of infection (targeted mutation
can be on the whole genome in the case of viruses,
and at particular antigenic loci in the case of bacteria and protozoa, see Moxon et al. 1994 for a review
and Frank 2002: chs. 5 and 7). Various models have
been built on this question in the specific case of
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PA R A S I T I S M A N D E C O S YS T E M S
Box 9.2 Kin-selection models of the evolution of virulence and host manipulation
Kin selection is a fundamental evolutionary process
(Frank 1998), and has increasingly been invoked in the
development of models of parasite evolution. The classic
tool for modelling kin selection is the technique of
inclusive fitness (Hamilton 1964). Here, we briefly
summarize the ‘direct fitness’ formulation of inclusive
fitness (Taylor and Frank 1996; Frank 1998), an important
and influential tool. First we express a general fitness
function for a social parasite, then we apply the direct
fitness technique to derive the ESS (evolutionary stable
strategy) of exploitation.
Fitness functions in locally interacting groups can be
usefully separated into two elements: within-group
(‘individual’) and between-group (‘group’) fitness (Frank
1998; e.g. host manipulation, Brown 1999; virulence,
Frank 1996; sibling competition, Godfray and Parker 1992;
vigilance, McNamara and Houston 1992). The approach
taken below is to construct a fitness function, w, consisting
of an individual (I) and a group (G) component in
a multiplicative form,
– ) ⫽ I (m)G (m
– ).
w(m, m
At an evolutionary stable equilibrium, the unbeatable
strategy m* is found by solving dw/dm冨 m ⫽ m ⫽ m* ⫽ 0. First
苶 the phenotypic
find dw/dm with the chain rule, then replace
– /⭸m with the corresponding relatedness
derivative ⭸m
coefficient (R), yielding
⭸w
m*
0.4
0.2
0
1
0.75
2
⫽ 0.
m ⫽ m– ⫽ m*
Equation 2 implies that there is no marginal gain from a
deviation from m* at equilibrium. For more details, see
Taylor and Frank (1996) and Frank (1998).
(2)
0.5
4
n
R
0.25
6
8
10 0
(b)
m*
0.4
0.3
0.2
0.1
0
1
0.75
0.5
100
(1)
– ) is the
Here m is the trait of a focal individual, and w (m, m
fitness of the focal individual (with strategy m), in an
–.
infrapopulation (group) in which the average strategy is m
I (m) equals the individual fitness function: if the trait is
costly to the individual then it is a declining function of m
(and conversely a rising function of m if the trait is directly
– ) equals the group fitness
beneficial to the individual). G (m
function, which again may be either a rising or falling
–.
function of m
⭸w
⫹Rᎏ
– 冨
冨ᎏ
⭸m
⭸m
(a)
200
n 300
R
0.25
400
500 0
(c)
–m*
1.5
1
0.5
0
1
0.75
0.5
100
200
n 300
R
0.25
400
500
0
Figure 9.1 Evolutionarily stable individual ‘collective action’
strategies (m*, Figs 9.1(a) and (b)) and ‘tragedy of the commons’
strategies (–m*, Fig 9.1(c)) as a function of relatedness (R) and
intensity of infection (n), following the model presented in
Box 9.1. Fig. 9.1(a), obligate collective action, p = 0 (e.g. RNA
replicase, Brown 2001). Fig. 9.1(b), threshold collective action,
p = 100 (e.g. quorum-sensing traits, Brown and Johnstone
2001). Fig 9.1(c), tragedy of the commons, p = 100. In all
figures, c = 1.
Source: Reworked from Brown et al. (2002).
Continued
S U B V E RT I N G H O S T S A N D D I V E RT I N G E C O S YS T E M S
By way of a simple example, consider a simple case of
linear G and I functions, wherein the exploitation trait is
costly to the individual, but beneficial to its group. This
‘altruistic trait’ framework has been used to consider the
evolution of host manipulative traits that are costly to
individuals to engineer (eg Immuno-manipulation,
Brown 1999, Brown and Grenfell 2001; RNA replicase
production, Brown 2001; siderophore production,
West and Buckling 2003).
– ) ⫽ (1 ⫺ cm)(p+ nm
– ),
w(m, m
So long as m is limited to positive values, we have a model of
cooperative host-manipulation (cost to the individual, benefit
to the group—i.e. ‘collective action’). However, by considering
the negative space of m, we recover a classic ‘tragedy of the
commons’ model of virulence, where increasing the virulence
trait (increasing the negative magnitude of m) has a positive
impact on the within-host fitness, and a negative impact on
the among-host fitness (Brown et al. 2002).
(3)
where c represents the cost of cooperation, p represents
passive fitness (the fitness of a non-contributing individual
in an infrapopulation of non-contributors) and n represents
infrapopulation size or density. Substituting eq (3) into
eq (2), we can solve to obtain the stable level of
collective effort:
nR ⫺ c p
m*⫽ ᎏ ᎏ.
c n (1 ⫹R )
145
(4)
parasites (Nowak 1990; Kamp et al. 2002), but also
more generally on the evolution of mutation rate in
a changing environment (Leigh 1970; Taddei et al.
1997; Johnson 1999). Antigenic variation (through
mutation) is a way to manipulate the host’s immune
system by sending it in the wrong direction. The
parasite may also manipulate directly the immune
system of its host by interfering specifically with
some of its communication molecules. Numerous
examples of such immune subversion are coming
from the viral world (see reviews by Alcami and
Koszinowski 2000; Tortorella et al. 2000; Murphy
2001), but some bacteria also interfere with immune
regulation (Rottem and Naot 1998). Finally, the parasite may also manipulate its local environment with
regard to competition with other parasites.
Protecting its host against further parasite arrival,
or eradicating all competitor parasites already present, may be a good strategy. This can be attained via
an effect on the host’s immune system. Brown and
Grenfell (2001) modelled the potential for adaptive
immune-manipulation by established macroparasite worms against larval challengers, illustrating
The positive (host-manipulation/collective action) and
negative (classic virulence/tragedy of the commons) regions
of m* are plotted separately in Figure 9.1, as a function of
infrapopulation size (n) and relatedness (R).
The model we present here is a very simple caricature, to
which many refinements can be made. West and Buckling
(2003) analyse a suite of related models (focusing on the
‘collective action’ dilemma of individual cost versus group
benefit) using the more general tactic of non-specified
individual and group functions. Furthermore, they consider
the effect of additive versus multiplicative fitness functions,
host mortality and the scale of competition on the trait ESS.
that this ‘host vaccination’ could be selected for
under reasonable conditions of density-dependent
fecundity, given an adequate dissociation between
the antigenic profile of adult and larval stages.
To conclude this section, besides the traditional
models on the evolution of virulence, we emphasize that the complexities of how parasites ‘administrate’ the body of their hosts, akin to ‘military’
strategies of invasion and occupation, should be
more often considered explicitly in models.
9.2.2 Parasite manipulation of traits specific
to the host
When the host is transformed into an efficient and
durable parasite syringe, it is important for the parasite to control the behaviour and energy allocation
of this syringe in order to maximize transmission
events. To this end, the parasites engage in numerous tricks to distort or hijack dramatically their
host’s body, providing the most potent examples of
Dawkins’ notion of an extended phenotype
(Dawkins 1982, 1990).
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Over the past 30 years, a significant body of empirical work has focused on the changes in host behaviour following parasitism, and whether or not these
changes represent parasite adaptations, host counteradaptations, or non-adaptive side-effects (e.g.
Rothschild 1962; Holmes and Bethel 1972; Dawkins
1990; Thomas et al. 2004). These changes in host phenotype vary greatly, from statistically discernable
changes in size or habitat, to the emergence of completely novel behaviours (Poulin 1994a, 1995b;
Thomas et al. 2004). If these effects are really parasite
adaptations then they constitute the most striking
examples of manipulation, as the parasites manage to
unexpectedly influence traits that belong ‘intimately’
to their host, and not only some properties of the
infectious process. Given the often-antagonistic
interests of host and parasite, the host body can be
viewed as an ecological and evolutionary battleground between host and parasite genotypes.
Nonetheless, the simplest explanation for parasiteinduced changes to the host phenotype is that they
are simply non-adaptive side-effects of infection
(Dawkins 1990; Poulin 1995b; but see Thomas et al.
2004). At this point it is worth considering a few case
studies, to understand the attraction of the hostmanipulation hypothesis. The great majority of
empirical studies on host-manipulation have centred
on the problem of jumping from one host to another,
in species of parasites employing complex, multiplehost life cycles (see references in Poulin 1994a, 1995b,
2000; Thomas et al. 2004). The digenean Dicrocoelium
dendriticum presents a well-known yet representative case (Carney 1969; Wickler 1976; Dawkins 1990).
In order to complete its complex life cycle, this fluke
faces the challenge of jumping from an ant to a sheep
host. The behaviour of healthy, uninfected ants presents a formidable barrier to this transition, as having
no selective interest in being consumed by grazing
sheep, they are appropriately evasive. Dicrocoelium
dendriticum apparently overcomes this barrier by
lodging in the sub-oesophageal ganglion of the ant,
leading to a significant behavioural alteration in its
host. Infected ants climb to the top of grass blades,
and lock their jaws to the very tip, in readiness for
the next grazing sheep. Numerous other examples
reveal a similar pattern of influence, with parasites
creating impressive modifications in one host, to
promote their ingestion by another. In some cases,
the mechanistic complexity of the modification is
most impressive, as for instance when parasites
secrete analogues of host hormones (e.g. production
of a growth hormone analogue by the protozoan
Nosema sp., leading to a doubling in size of their
insect host (Fisher 1963). For other hormonal examples, see Beckage (1991, 1997), the apparent purposefulness of the modification lends the manipulation
hypothesis its greatest support, as for instance when
the onset of behavioural changes following infection
coincides with the arrival of the parasite at a developmental stage suited for transmission. For example,
the suppression of anti-predator responses in stickleback fish is only a property of infective plerocercoids
(Tierney et al. 1993; see also Poulin et al. 1992).
As a result of these and many similar examples,
changes in the behaviour of parasitized animals are
commonly viewed as parasite adaptations to
enhance transmission (see reviews by Dobson 1988b;
Dawkins 1990; Moore and Gotelli 1990; Keymer and
Read 1991; Poulin 1994 a,b, 1995b, 2000; Thomas et al.
2004). However, considerable confusion remains
over how cases of adaptive host manipulation can be
reliably recognized, given the contrasting possibility
of host counter-adaptation, and the often more parsimonious explanation of non-adaptive side-effect
(see Poulin 1995b; but see also Thomas et al. 2004). To
date, models have only played a minor role in aiding
the dissection of the adaptiveness of complex host ⫻
parasite interactions. Poulin (1994b) presented a
graphical analysis of a number of key issues in host
manipulation. More recently, interest has grown in
understanding the social selective forces underpinning potentially manipulative behaviours (Brown
1999; Brown et al. 2001, 2002; West and Buckling
2003). In our view, there is still much potential for
dynamically explicit models of parasite evolution in
the setting of complex life cycles (see Choisy et al.
2003 for a starting point).
Note that most of the manipulative traits outlined above (in Sections 9.2.1 and 9.2.2) benefit not
only the individual parasites that manipulate but
also all their co-infecting neighbourhood, including
potential ‘cheats’; free-rider parasites that take the
advantages of manipulation, but do not pay the
costs. In the preceding discussions, the infection
is considered as a unique individual in conflict
with another (the host). However, the existence of
S U B V E RT I N G H O S T S A N D D I V E RT I N G E C O S YS T E M S
competition between parasites within the host is
also an important aspect of parasites’ life which
may have important consequences for manipulative traits (Box 9.2). Let us take the example of
immune manipulation. Some viruses secrete proteins that alter the regulation of host defence; this
time and energy consuming behaviour affects the
entire host physiology and benefits all the viruses
of the infection, whether or not they secrete the
immune modulator. If the mutation rate (or immigration rate) within the virus population is too
high, then the secretion behaviour may be lost
because ‘cheats’, not secreting the immune modulators, are favoured by local competition (see
Bonhoeffer and Nowak 1994). This question of
multilevel selection is present concerning numerous traits of host exploitation and manipulation:
virulence and within-host replication rate (e.g.
Frank 1992; Nowak and May 1994), expression of
virulence factors (Brown and Johnstone 2001; West
and Buckling 2003), dispersal from the host, tissue
preference within the host (see Levin and Bull
1994), host behavioural manipulation (Brown
1999). For instance Brown (1999) develops a simple
evolutionary analysis of ‘unbeatable strategies’ of
host manipulation, focusing in particular on the
cooperative dilemmas of manipulating a single
host as part of a potentially large group of parasite
individuals. The relationship between the evolution of host manipulation and the evolution of virulence is discussed in Brown et al. (2002) and Box 9.2.
9.3 Parasite manipulation of global
ecosystems
In the Section 9.2 we have explored how the host
(seen as an ecosystem by itself) can be manipulated
by the parasite in its own interest via several traits
(replication rate, tissue affinity, mutation rate, secretion of virulence factors, interference with immunity,
etc.). On a higher level (population of hosts in their
external environment), the parasite also influences
the ecosystem through an action on host behaviour,
mortality, and reproduction. A major difference
between these two levels of action is that, in the case
of the within-host environment, the ensemble of the
host’s cells (the organism) is a tightly integrated unit
of selection, whereas this is less likely to be the
147
case in aggregates of independently reproducing
organisms. This difference has consequences both
for the host and the parasite. First, regarding the
host, immune cells work for the entire organism and
not for themselves; as a consequence they do not
function like independent predators: their replication
rate is controlled by an upper level of integration
(the organism); it does not simply rely on the quantity of parasites (‘prey’) they ‘eat’. This decoupling
permits the immune system to eradicate parasites
entirely even when they get very rare, which is
rarely possible in the case of predators with their
prey. This major demographic difference between
immune cells and predators has been studied and
reviewed by Antia et al. (2003). Second, and more
importantly in this chapter, regarding the parasites,
the strong genetic relatedness between co-infecting
parasites (and the emergence of the whole infection
as a unit of selection), permits the evolution of
cooperative strategies of host manipulation (as
discussed in Section 9.2 and Box 9.2).
Regarding the ecosystem at the higher level,
parasites can affect both the demography and
evolution (genetic composition) of the population
of hosts (see Chapter 3). In most cases this effect
is a simple coincidental product of parasitism.
However, if the population of hosts is structured
(by distance isolation or environmental heterogeneity) then external environmental changes brought
by a within-host community of parasites may in
turn differentially affect genetically related parasites in other hosts. In such case, an adaptive
manipulation of the upper-level ecosystem (i.e. of
the hosts demography and evolution) may evolve.
In a first simple analysis, this manipulation may
affect the evolution of the parasite’s strategy of host
exploitation. Spatially explicit models show that
parasites tend to be less virulent when the population of hosts is structured in space, the parasites
being selected to maintain a high local density of
available hosts that benefits their genetically
related neighbours (Claessen and de Roos 1995;
Rand et al. 1995; van Baalen 2002). This phenomenon might also be involved in the evolution of parasite strategies of host ‘domestication’, that is,
parasite traits that influence the evolution of the
local host population in a direction that benefits the
local population of parasites. For instance, certain
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parasites may tend to be more virulent against
hosts that resist their attack (the so-called mafia
behaviour; Soler et al. 1998). Such behaviour is
costly for a given parasite as it increases the host
death rate; however it may be favourable for the
local parasite population as it reduces the density of
resistant hosts and therefore increases the density
of sensible ones. This question requires a formal
mathematical analysis (previous models, for example, Soler et al. 1998, only analyse the evolution of
mafia behaviour in the case where the host has
already evolved a plastic strategy of immune
response). More generally, domestication in a structured environment might often be involved in the
long-term coevolution of host/parasite systems,
and especially in the emergence of symbiotic
systems from initially parasitic ones.
In order to consider how parasite-induced
changes in host phenotype can have wide-ranging
impacts on host population and community structure, we will move to mobile genetic elements
(MGEs) in bacteria, as bacterial systems permit
rapid experimental investigation on a large populational scale. MGEs (eg bacteriophage, plasmids,
transposons) can be propagated via a variety of
mechanisms leading to both horizontal and vertical
transmission (see Lawrence 1999). Host manipulation by MGEs is rife, as they can carry genes altering
many aspects of the host phenotype. In contrast
to the helminth-biased examples discussed in Section
9.2.2, many of these changes in host phenotype
are unambiguously adaptations, displaying complex
specialization and beneficial effects, at least to the
MGE. The MGE genes underlying host-manipulative
traits are referred to as ‘conversion genes’.
Consider the case of colicinogenic plasmids, not
least because of a rich and accelerating dialogue
between theory and experiments. These are extrachromosomal DNA parasites of Escherichia coli that
cause (at a low frequency) the explosive suicide of
the host, and the release of antimicrobial toxins
termed colicins (Riley and Wertz 2002; Riley et al.
2003). On an individual host level, this is a dangerous pathogen. What is more, on an individual
plasmid level this behaviour is also extremely
costly as the plasmid genes are exploded
along with the host. To understand this system, a
population-based perspective is essential. For a
given lineage of colicinogenic plasmid carriers (carriers for short), only a small fraction release colicins
via cell lysis. Furthermore, non-lysed carriers are
immune to the colicin released by their lysed kin,
thanks to the specific antidote coding genes carried
by the plasmid. In a pure culture, this lysis represents a straightforward cost of parasitism to the
host, and a more puzzling cost to the parasite itself.
However, if the carrier lineage is in contact with a
line of E. coli that is susceptible to the toxin (i.e. not
carrying the same specific plasmid), then the
release of colicin may act to reduce the density of
susceptibles, and hence act as a spur to carrier
growth, benefiting both the carrier bacteria and
carried plasmid. The conditions determining the
outcome of competition between carrier and susceptible lineages of E. coli where first sketched in a
pioneering paper by Chao and Levin (1981). They
illustrated that in a well-mixed environment (e.g.
shaken liquid culture), carriers cannot invade a
susceptible lineage if their initial density is below a
critical threshold. However, they went on to show
that the introduction of spatial structure can overcome this barrier to invasion. Carriers could invade
a numerically dominant susceptible population if
the bacteria were grown on static agar plates, even
for ratios where invasion failed in the well-mixed
environment.
Subsequent theoretical work illustrated that the
localization of killing brought about by spatial
structure ensured that the local density of toxin
could be sufficiently high, even when carriers where
extremely rare (Frank 1994; Durrett and Levin 1997).
In contrast, in the well-mixed environment the density of toxin produced by rare carriers is rapidly
diluted to ineffective levels. In sum, models of wellmixed competition illustrate that ‘susceptible’ is
always a locally stable strategy (always resistant
against vanishingly small invasions by carriers), but
carriers can also be a locally stable strategy for certain parameters (Frank 1994; Durrett and Levin
1997, Brown, Le Chat, and Taddei submitted). Thus
when both carriers and susceptibles are stable to
invasion, the ecological end-point depends on the
initial frequency of carriers to susceptibles in the
local well-mixed environment. More recent work
S U B V E RT I N G H O S T S A N D D I V E RT I N G E C O S YS T E M S
has focussed attention on how spatial structure can
support diversity, once multiple competing strains
of carriers are taken into account (Czárán et al. 2002;
Kerr et al. 2002; Czárán and Hoekstra 2003). Thus we
see that simple parasite-induced niche construction
(e.g. production of colicins) can have wide-reaching
impacts on the invasiveness of the host, and host
community diversity (similar arguments can be
advanced for phage-mediated competition; Brown,
Le Chat, and Taddei submitted).
9.4 Transmission modes as ecological
niches in the ecosystem of parasites
We shall now consider evolution in a community of
parasites that compete for transmission among a
population of hosts, as in the previous section.
Within a host individual, parasitic strains compete
to gain access to resources. This competition could
yield a diversification of pathogenicity strategies
(type of tissues preferentially attacked, etc.). The
same sort of competition, and possibly the same sort
of specialization, could in fact occur at the level of
the population of hosts. At this level, parasites
indeed compete to gain access to susceptible hosts.
At the lower level of selection, life history traits that
determine replication rate or resistance to the host’s
immune system will be selected. At the upper level,
traits that determine what host or what trait of the
host they use for their transmission could be under
selection. Of course some parasite traits might be
selected at both levels, and it is anyway generally
assumed that tradeoffs exist between these two
suites of traits. As a result, pathogens should evolve
toward intermediate strategies where costs and benefits of virulence are balanced. In the following
paragraphs we will see that under some form of
competition evolution does not follow this simple
evolutionary path. The average strategy might
indeed deviate strongly from what would be
expected if R0 was maximized when selection yields
extreme specialization on transmission modes.
As we have seen previously, pathogens can
attack specifically some part, tissue, or organ of
their host. Each host is, from the pathogens’ point
of view, a collection of resources that can be
149
exploited, a set of different ecological niches that
can be occupied. Not surprisingly, pathogenic
strains that do not compete, because they do not
exploit the same resource, can coexist within a
single infected host. This is yet another manifestation of Gause’s competitive exclusion principle.
The same sort of specialization can occur among
parasites that infect a population or a community of
hosts. This point is clearly demonstrated by
Lipsitch et al. (1996). These authors considered a
mixed mode of transmission: vertically each time
their host reproduces and horizontally by contact
between infected and susceptible hosts. Lipsitch
et al. (1996) found that two strains of pathogens cannot coexist within the same population of hosts,
unless they have contrasted modes of transmission:
parasites that are transmitted mostly vertically can
coexist with others that transmit mostly horizontally (see Box 9.3). Again, as the authors point out in
their paper, this result is a manifestation of the competitive exclusion principle: vertically transmitted
pathogens exploit the capacity of their host to
reproduce; horizontally transmitted pathogens
exploit the capacity of their host to contact susceptible conspecifics. The competition between these
two kinds of pathogens is therefore reduced and
their coexistence is possible.
As the same reasoning applies at both levels of
selection, we can generalize and propose that different modes of virulence and of transmission characterize distinct ecological niches. At this point the
reader might wonder how the existence of several
ecological niches might affect the evolutionary
dynamics in pathogens. If pathogens all converge
toward the niche where resources are the most
abundant and where transmission is the most efficient, R0 will be maximized as classically predicted.
In some situations however, pathogens might not
converge towards this ‘ideal’ niche, simply because
it is overcrowded. Specialization might then
appear, pathogens being selected to occupy niches
where resources are maybe less abundant but
where competition with other strains is reduced.
We shall see in the following that selective pressures might be different among the niches
pathogens can colonize. Evolution of pathogens
will therefore depend first on what niche is
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Box 9.3 The principle of adaptive dynamics—finding conditions necessary for diversification
We shall illustrate the principles of the adaptive dynamics
technique using the example of a pathogen with a
mixed mode of transmission, exerted from
Lipsitch et al. (1996).
Defining the invasion function
Let u and v be the densities of infected and uninfected
hosts respectively. Each pathogenic strain is characterized
by a rate of horizontal transmission  and a virulence ␣:
infected pathogens die at a rate (1 ⫹ ␣) ⬎ . When
infected hosts reproduce, pathogens are transmitted
vertically in a proportion 1 ⫺ ␦ of the offspring.
This yields the following set of differential
equations:
dv
ᎏ ᎏ⫽ f (v ⫹ ␦u) (1 ⫺ u⫺ v ) ⫺ v ⫺ uv,
dt
du
ᎏ ᎏ⫽ f (1⫺ ␦) u (1 ⫺ u⫺ v) ⫺ (1 ⫹ ␣) u⫹ uv.
dt
We can use these equations to derive the equilibrium
epidemiological state (ur, v r) of the host-pathogen
community. We shall now consider a mutant pathogenic
strain that appears in this equilibrium community. Assuming
that mutants are initially rare (um⯝0), we can write
d um
ᎏ ᎏ ⫽ um {f(1⫺ ␦)(1 ⫺ ur⫺ v r) ⫺ (1 ⫹ ␣m ) ⫹ m v r}.
dt
opportunities of transmission, decreases when  increases.
Under such a trade-off model, there should be a value of ,
a singular strategy, at which the benefits and the cost of
virulence are balanced.
The signification of singular strategies is exemplified on
Fig. 9.2. On this figure, each pathogenic strain is
characterized by its . Gray areas define the set of mutants
(m on the y-axis) that can invade in a given resident
population (r on the x-axis). The edge of this set is a
curve on which the invasion function is zero (mutations
are neutral). The singular strategy corresponds to the
point where that edge crosses the line m⫺ r. Note
that in Figs. 9.2(a) and 9.2(b) the pathogen population
always evolves toward the singular strategy. This
convergence is not always guaranteed in adaptive
dynamics models.
Branching points and the diversification of
pathogens
Most generally, ␣ is supposed to increase at an accelerating
rate with . Under this assumption, once the community of
(a)
(b)
m
m
From this equation, we can define an invasion criterion.
A mutant pathogen will invade in an equilibrium
community if and only if
r
w⫽ f(1⫺ ␦)(1 ⫺ ur⫺ v r) ⫺ (1 ⫹ ␣m) ⫹ mv r ⬎ 0.
The possibility for a mutant to invade a resident population
depends, of course, on its characteristics ␣m and m. It also
depends on that of the resident pathogen because ur and v r
are functions of ␣r and r.
Convergence toward singular points
In most epidemiological models, transmission comes at the
cost of additional virulence. We will now assume that a
increasing function relates ␣ to  (e.g. ␣ ⫽ ab). As a
result, the rate of pathogen transmission increases with 
while the number of susceptible hosts, and therefore the
r
Figure 9.2 Two Pairwise invasibility plots.
Notes: The gray areas indicate set of mutant strategies (m) that can
invade the resident strategy r, that is, those for which the invasion
criterion w is positive. The circle and the dashed vertical line indicate
the singular strategy, i.e. the level of transmissibility where costs and
benefits of virulence compensate. Arrows indicate that in both cases A
and B selection will bring pathogens at this point. In case A, once this
point is reached, the resident population of pathogens is immune from
invasion (all values of m ≠ r yield w < 0). The singular point is
therefore an Evolutionary Stable Strategy (ESS). In case B, the resident
population of pathogen corresponding to the singular point can be
invaded by any mutant (all values of m ≠ r yield w < 0). In this later
case the population of pathogen will become polymorphic for this
level of transmissibility (see text and Fig. 9.3)
Continued
S U B V E RT I N G H O S T S A N D D I V E RT I N G E C O S YS T E M S
151
pathogen has reached the singular point, no mutant
can invade: the pathogens have evolved toward a
strategy that makes them immune from invasion.
The singular point is then evolutionary stable
(Fig. 9.2(a)).
We shall now assume that ␣ increases at a decelerating
rate with  : ␣⫽ ab with b⬍ 1. We will not
discuss here what circumstances might justify
this particular assumption. Our purpose is to show
that, if valid, this particular form of trade-off
produces a situation where the singular point,
instead of being evolutionary stable, can be
invaded by any mutant strategy (see Fig. 9.2(b)).
Once the pathogen population has reached
this point, it starts developing a polymorphism
for transmissibility (and hence virulence).
Eventually two strains with very contrasted
transmission and virulence status differentiate
and coexist within the same host population. This
type of dynamics is illustrated in Fig. 9.3.
available and second on the selective pressures that
are characteristic of this niche.
We shall now go back to the example exerted
from Lipsitch et al. (1996): pathogens can specialize
on contrasted modes of transmission. This verbal
prediction seems to match some experimental cases,
for example, endophytes. Endophytes are pathogenic fungi of grass species. In some species one
form of the fungus is vertically transmitted to
offspring, colonizing seed tissues. A different form
of the same species produces spores that are dispersed and can contaminate neighbouring plants. In
this system horizontal transmission mechanically
suppresses vertical transmission. Spores are indeed
produced in the grass inflorescence, which effectively precludes production of seeds, and therefore
vertical transmission of the fungus (Schardp 2001).
Clearly, the two forms of the fungus do not exploit
the same resource on the host. As we would predict,
they are found to coexist in some populations of
grass. Once specialization has occurred on transmission modes, traits that are not directly involved in
transmission should experience different selective
pressures in the two pathogenic strains. A clear
Time
Figure 9.3 A situation of evolutionary branching.
Notes: Each horizontal gray bar represents a pathogenic strain: its position
along the y-axis gives its characteristic ; its thickness is proporptional to
the frequency of the strain in the pathogen population. Vertical lines
indicate mutation events that give rise to a new pathogenic strain from a
pre-existing one. The community of pathogens first evolves toward the
singular strategy (central horizontal line). Once it has reached this point,
a polymorphism develops and two strains emerge with low and high
virulence level respectively.
expectation in this situation is that, because vertical
transmission aligns the pathogen’s interest with that
of its host, virulence should be counterselected in
the vertically transmitted strain. This prediction is
again supported by detailed studies of endophyte
species. While the horizontally transmitted strains
impose heavy costs on their hosts, the first of which
being that they suppress their sexual reproduction,
the vertically transmitted strain resemble mutualists. It has even been demonstrated that some of
these strains induce greater host resistance to
draught and herbivores. We have here a clear illustration of the evolutionary scenario we proposed
earlier: the first traits to be selected are those that
determine which niche a pathogen occupies; which
traits are then selected, and in what direction,
entirely depends on this niche.
The case of endophytes illustrates very clearly
our point because the trait on which specialization
occurs directly determines the selective pressures
that act on virulence. The same situation probably
arises in many other systems (e.g. bacterial plasmids). However, this correlation between selection
on traits involved in specialization and traits
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involved in virulence might not always be as
straightforward. Selection on traits involved in virulence might in particular depend on some characteristics of the host species, as emphasized in the
first section of this chapter. We recently developed
a model of this sort to explain the coexistence of
several species of pollinators with contrasted
strategies of oviposition in natural populations of
globeflowers (Trollius europaeus, Ranunculacea)
(Ferdy et al. 2002). Globeflower pollinators are flies
which lay eggs in the flowers they visit. The larvae
hatching from these eggs eat part of the plant’s seeds.
From these simple facts, we could consider flies as
parasites as their reproduction is detrimental to
their host. But among the species that can be found
in natural populations of globeflowers, some visit
young flowers and lay one egg at each visit while
others visit wilted flowers in which they lay all
their 15 eggs at once. The first species is often considered as a mutualist, as it contributes to pollination while imposing a minimum cost on its host.
The second species, for symmetrical reasons, is considered as a cheater or a parasite. The trait that
seems to be involved in specialization in this system is the age of flowers in which females lay their
eggs. It has been shown that larvae that hatch from
eggs laid at different times in a flower do not feed
on the same part of the fruit. Therefore these larvae
do not compete and the existence of flies that lay
their eggs in flowers of different age can be interpreted as resulting from selection for competition
avoidance. But then, how should we interpret the
fact that the first of these flies lays one egg per
flower while the second lays all their eggs in a
single visit? We proposed that this results from
a correlation between the age of the flower in
which eggs are laid and their survival chances.
Preliminary data indicate that eggs survive better
in the first species that in the second, probably
because the closed corolla of the globeflower
protects them from parasitism and other external
aggressions. Eggs that are laid in wilted flowers do
not benefit from such protection. The result of this
difference in survival probability is that, for a given
number of eggs, the number of hatching larvae, and
therefore the competition between them, is much
higher when eggs are laid in young flowers than
when they are laid in old ones. Flies that lay their
eggs in young flowers should therefore be selected
to reduce competition among their offspring, which
can be achieved by spreading eggs among many
flowers. In this scenario flies first specialize on
flowers of different age to escape from competition
with other species. Flies visiting young flowers are
then selected to spread their eggs among many
flowers. This second step in the evolutionary
dynamics of the system is mediated by the host
whose corolla shape induces stronger competition
among larvae in one of the two niches. It has
recently been proposed that a similar scenario
could apply to the much better known case of
Yucca–Yucca moth interaction (Pellmyr and Huth
1994; Ferrière et al. 2002).
A further issue in this story concerns the evolution of corolla shape in globeflowers, which we propose to be a trait allowing the plant to manipulate
competition among fly larvae. Of course, this trait
cannot be selected because it induces the evolution
of mutualism in flies. Rather, in our model, this trait
is favoured simply as an anti-parasite strategy that
allows the plant to kill fly larvae before they cause
too much damage to its developing seeds. The fact
that these traits select for mutualism in some fly
species is fortunate to the host, but it is only accidental. Whatever traits are selected in the host, we
see here that this selection will determine the
ecosystem structure of pathogenic species.
The importance of the existence of distinct niches
in host populations has recently been demonstrated
in a model where specialization occurs on a trait
that directly determines the degree of mutualism of
one partner of an interacting pair of species (Ferrière
et al. 2002). Clearly mutualism can here be interpreted as ‘negative virulence’ and all the arguments
we developed earlier apply to both mutualists and
pathogens. The work of Ferrière et al. (2002) shows
that once pathogens split into several populations
occupying distinct niches, the evolution of their virulence becomes in part determined by the structure
of the community of mutualists/pathogens—
namely the symmetry of competition. Mutualism
here is not really stable because of some intrinsic
characteristic. It is stable only when all other niches
are occupied by pathogens. We could rephrase this
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by saying that in such systems, the question of the
evolution of mutualism/benevolence becomes
distinct from that of its stability.
virulence are not simple functions of the interacting
genotypes: they also depend on the ecological
community these genotypes live and reproduce in.
9.5 Discussion and concluding remarks
9.5.2 Host manipulation and community
ecology
9.5.1 Mutualism as negative virulence:
host–parasite co-evolution
Relative to within-species interactions, asymmetries
move centre-stage in the interspecific context of
host–parasite interactions. The classical definition of
a parasite as a symbiont that does harm (e.g. Poulin
1998a) freezes this asymmetry as a net flow of value
from host to parasite. However, this simple categorization can hide a more interesting mix of antagonistic and overlapping interests (Dawkins 1990;
Michalakis et al. 1992; Herre 1999; van Baalen and
Jansen 2001). For instance, concomitant immunity to
infection carries important benefits to both established parasites and their hosts (Brown and Grenfell
2001). Likewise, the production of antibacterial
agents by E. coli may aid a vertebrate host. From a
coevolutionary perspective, prudent exploitation
offers benefits to both the host and to parasites, suggesting room for cooperation between host and parasite in fighting subsequent infections (van Baalen and
Sabelis 1995). These examples highlight that parasiteinduced host manipulation does not necessarily
cause harm to the host (Brown et al. 2002).Viewing
the host–parasite interaction as a complex mix of
interests, or desiderata (Dawkins 1990) is an important
step away from the medically influenced view of parasites being always virulent to some degree.
Not only is there a phenotypic continuum ranging from mutualism to parasitism, with commensalism as an intermediate stage, but also all these
states are not just characteristics of host–parasite
interactions. They characterize an interaction in a
particular ecosystem. If ever some force was changing the composition of the community or the functioning of the ecosystem, a mutualistic association
could start functioning as a parasitic one. In the
example above, an E. coli strain that produces antibacterial agents is a mutualist if the host is infected
by pathogenic bacteria; it becomes a parasite if
these pathogens disappear. Fitness, parasitism, and
A final aim of this study is to provide a basis for
future research investigating the community-level
consequences of parasitism. Most of the existing
evidence for parasitic impacts on community
structure concern ‘parasite arbitration’, where a
single parasite mediates apparent competition
among multiple host species through differential
host-susceptibility (Hudson and Greenman 1998;
Tompkins et al. 2001; see Chapter 8). Thomas et al.
(2000a) identify the potential for more indirect chains
of influence between parasites and community
structure, mediated by the host-phenotype. Life history traits of free-living species can be an important
determinant of community structure, for instance
changes in development time or dispersal can
impact on competitive interactions and food web
structure (Chase 1999; Tokeshi 1999). Thus via their
effects on host phenotype (whether through parasite
adaptations, host counter-adaptations, both, or neither), parasites have the capacity to indirectly influence the structure of both host and parasite
communities. Some of the systems described in this
chapter provide potential examples of such indirect
effects on community structure. Bacterial collective
action can lead to innumerable changes in their
hosts, of significance to third-party species. For
instance, human dental plaque is a product of complex interactions between the host and multiple bacterial species. A subset of these bacterial species
actively creates a fibrous biofilm matrix, providing a
modified environment within the host, enabling the
establishment of a broad bacterial community
(Costerton et al. 1995; Wood et al. 2000). As we have
seen above, once the composition of the ecological
community is modified, who is a parasite and who is
not might also change. From an evolutionary point
of view, once a complex community has established,
many new ecological niches are open and selection
can take many different directions. A simplistic view
of the situation would be that each virulent strain
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opens a niche for a protective bacteria. The number
of niches could in fact be much higher and the traits
submitted to selection much more complex, because
each member of the community can manipulate for
its own interest a complex network of interactions
between other members. Some experimental studies
in macroparasites gives a flavour of this complexity:
the host-manipulating trematode Microphallus papillorobustus offers increased transmission success to
non-manipulative trematodes sharing the same
intermediate and definitive hosts (Thomas et al. 1997,
1998b; see Chapter 8). Models of the evolution of virulence started with pairs of interacting species. They
then considered heterogeneity or polymorphism in
these species. We are now at the point where we
need to consider the community to understand the
selective forces that act on parasites. The answer to
many current questions on the evolution of parasites
might come from this dawning convergence
between evolutionary and community ecology.
CHAPTER 10
Parasitism in man-made ecosystems
François Renaud,1 Thierry De Meeüs,1 and Andrew F. Read2
Technological and cultural change in human populations is opening up new
ecological niches for pathogens and parasites. The organisms that cause
many of these ‘‘diseases of progress’’ have opportunities for global spread and
access to host population densities unprecedented in human history.
Understanding the natural history and evolutionary ecology of these
pathogens needs to become a key part of public health planning.
10.1 Introduction
Like free-living organisms, parasites and pathogens
can colonize and evolve in new environments. In this
way, travel and technical developments (e.g. air conditioning, plane, boats, new economic links, etc.),
medical and surgical developments (e.g. catheters,
fibroscopy, prosthesis, organ transplants associated
with anti-rejection medicine, immunosuppressive
drugs, etc.) are generating new environments in
hospital ecosystems which are colonized now by new
parasite and pathogen flocks. Elsewhere, agricultural
processes have widely disturbed ecological parameters in natural ecosystems for food development;
they are responsible for the emergence and development of new parasite and pathogen species, and also
for changes in host–parasite interactions. Through
different examples, the aim of this chapter is to present and to discuss some phenomena and processes
involved in the conquest by parasites and pathogens
of man-made ecosystems. We could name diseases
which are the result of pathogens colonizing manmade ecosystems as ‘progress infectious diseases’.
To pass from 6 billion to 10 or 12 billion human
inhabitants by the end of the twenty-first century
1
Génétique et Evolution de Maladies Infectieuses GEMI/UMR
CNRS-IRD 2724, Equipe: ‘Evolution des Systèmes Symbiotiques’,
IRD, 911 Avenue Agropolis, B.P. 5045, 34032 Montpellier Cedex 1,
France.
2
Institutes of Evolution, Immunology and Infection Research,
School of Biological Sciences, University of Edinburgh, EH9 3JT,
Scotland.
represents one main subject of anxiety for scientists.
Ten billion humans could not live on the earth with
the lifestyle enjoyed by the 750 million people
presently living in developed countries, because of
lack of water, energy, quality, and quantity of space.
Developed countries must contribute to the development of all countries to balance economy and life
conditions. However (indeed, if ever) this is
achieved, substantial environmental modification
seems likely. Throughout history, mankind has
severely modified the biosphere. Human impacts on
ecosystems are as old as the human species.
However, following industrialisation, the consequent increase in numbers of people and their ability
to modify the biosphere, the extent and consequences of human impacts on ecosystems have
accelerated. Impacts resulting from human activities
occur in all parts of the biosphere, and at all kinds of
temporal and spatial scales. (Dickinson and Murphy
1998). The ecological consequences of the unavoidable modifications of the future are hard to predict:
we simply do not have a thorough understanding of
the impact of global change on local environmental
conditions and the evolution of biodiversity.
10.1.1 But what is an ecosystem?
Let us imagine a pond, for example. What animals
might live here? Insects, worms, birds, fish, mice,
muskrats, ducks, deer, wolves. What do these
animals need to eat? Insects eat plants, fish eat
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worms and insects, birds eat fish, worms, and
insects. Mice eat grain. Muskrats eat ducks, eggs,
and chicks. Ducks eat insects and worms. Deer eat
grass. Wolves eat mice, muskrats, and deer. All
these animals rely on the pond for the water they
need. The deer cut the grass, wolves remove the
sick and weak deer from the herd. Muskrats regulate the duck population. All these animals rely on
each other. Just like people in a human community.
An ecosystem is a community too. Consider a pond
community, with all its variety of plants, insects,
birds, and other living things. What would happen
to the community if the water vanished? What if
the ducks all disappeared?
Other examples of ecosystems include forests,
rivers, oceans, deserts, cold arctic tundra, high
mountains, and rain forests. Different plants and
animals grow in different ecosystems. Normally,
the living things in the ecosystem balance in such
a way that no living things take over the whole
ecosystem and destroy it, at least not for a while.
For example, the production of O2 by the first photosynthetic algae had dramatic consequences on
the anaerobic life that predominated at that time.
10.1.2 But why some deer are sick and weak
within the herd?
May be they could be parasitized? We just want to
underline here that the above description of an
ecosystem, as we can read it in numerous books or
websites, disregards systematically the fundamental
role that parasites play in ecosystem functioning!
Indeed, it is less poetic to speak about a tapeworm or
a virus than a duck or a deer! Nevertheless, parasites
are present in a large part of ecosystems, and the liver,
kidneys, lungs, gills, gut, and pharyngeal sphere of a
host constitute as many ecosystems for parasites
and pathogens as do rivers, oceans, desert, high
mountains, and jungles for free-living organisms.
10.1.3 But what is a parasite and/or a
pathogen?
‘An organism in or on another living organism
obtaining from it part or all of its organic nutriments,
commonly exhibiting some degree of adaptive
structural modifications, and causing some degree of
real damage to its host’ (Price 1980). So, the parasite/
pathogen lives at the expense of the host, and this
host’s exploitation has automatic consequences on
host biology and physiology, on host evolutionary
biology and on evolutionary relationships between
hosts and parasites (Renaud and De Meeüs 1991).
Because the host represents the ‘habitat/resource’
system of the parasite, each modification on host
ecosystem will have consequences on the parasite
ecosystem, and because parasites affect host fitness,
they act on host ecosystem too. Because living organisms are parasitized, we cannot consider ecosystem
evolution without parasites (see Chapter 9).
It is undeniable that humans greatly disturb
ecosystem equilibrium (deforestation, eutrophication, overgrazing, etc.), but the aim of this chapter
is not to consider anthropogenic ecosystem disturbances and subsequent evolution of parasites and
diseases which are presented in other chapters of
this book (see Chapter 7). Instead, we will illustrate
and discuss, through different examples, the impact
of technical progress by humans on the evolutionary ecology of parasites and pathogens. How have
parasites exploited new ‘human-made’ ecosystems,
especially those concerning public health?
10.1.4 What is a ‘human made’ ecosystem?
It is an ecosystem artificially elaborated by humans
in order to enhance their quality of life.
For example, let us imagine that the wheel was
never invented! The wheel is everywhere on our
cars, trains, planes, machines, wagons, and most factory and farm equipment. What could we do without wheels? But as important the wheel is, we do not
know who exactly invented it. The oldest wheel
found in archaeological excavations was discovered
in Mesopotamia, and is believed to be more than
5500 years old. Eventually, wheels became covered
with tyre in order to make the trip more easy and
pleasant. But, it is almost impossible remove all the
water a worn-out tyre contains. Consequently, old
tyres become excellent habitat for the larvae of different mosquito species, especially Aedes spp. which
are the vectors of the Dengue virus. Worn and waste
tyres are being traded throughout the world, and are
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3
1
2
Figure 10.1 Example of hypothetical main routes of Aedes albopictus- infested tires.
Notes: 1: Japanese origin; 2: first colonization wave: US and South America in 1985/1986; 3: second colonization wave: Mexico, Africa, and Europe in
1990/1991.
Source: Data from Reiter (1998: 93, table 10).
responsible for the introduction of mosquitoes in
different countries (Fig. 10.1). ‘In short, it seems we
must accept the establishment of exotic species as an
inevitable consequence of modern transportation
technology’ (Reiter 1998). For example, inspections
of containers arriving in US ports showed the presence of living Aedes albopictus and four other mosquito species in worn tyres from Japan (Craven et al.
1988). Japan is the biggest exporter of worn tyres in
the world. Ae. albopictus is capable of vertical and
horizontal transmission of the Dengue virus, and
other important human arboviruses (Shroyer 1986).
Thus pathogenic agents can take advantage of tyre
trade. We can imagine that such trades could have
also consequences on other vectors, such as the
Anopheles mosquitoes which transmit malaria.
10.2 Economic and touristic human
travels: enhancement of human contacts!
Boats not only carry the worn tyres which constitute
new ecosystems for mosquito larvae, but they also
have bilge. The classic bacterial disease, cholera,
entered both North and South America during the
last century from the bilge-water of an Asian
freighter. Indeed, molecular typing showed that the
South American isolates were pandemic genotypes
previously observed in Asia. Water bilge seems to
constitute a very good ecosystem for the transported pathogens such as bacteria (Anderson 1991;
Morse 1995). Cholera is not the only opportunistic
pathogen which use such kinds of transport: an epidemic strain of Neisseria meningitidis seems to have
disseminated rapidly along routes by travelling in
ballast waters (Moore and Broome 1994).
Malaria parasites use mosquitoes to transmit
between vertebrate hosts. For example, different
mosquito species belonging to the genus Anopheles
are the definitive hosts of the malaria agent
Plasmodium vivax , one of the four species of human
malaria. Human malaria is currently absent in
western Europe, but an autochthonous case of P.
vivax malaria occurred in Tuscany (Italy) in August
1997, decades after malaria eradication (Baldari et al.
1998)! The disease was diagnosed in a woman with
no travel history who lived in a rural area where
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indigenous Anopheles labranchiae, the former main
malaria vector in Italy, was abundant (Romi et al.
1997). A molecular epidemiological investigation
concluded that this was an introduced malaria case,
and indicated a girl recently immigrated from
Punjab (India) and living about 500 m away from
the patient, as the source of P. vivax infection
(Severini et al. 2002). The parasite was able to pass
from Asia to Europe because an infected host took
a plane to visit a family member. Planes and boats
constitute new opportunities for vector and
pathogen dispersion, in the same way as when
a pathogen is using different hosts for its dispersal.
Parasites and pathogens are able to colonise new
environments and to adapt locally to new hosts and
vectors through human-made transportation.
Similarly, epidemics of malaria in NE Brazil in the
1930s occurred because of the introduction of
Anopheles gambiae , one of the most efficient malaria
vectors, which probably arrived from a boat bringing mail from Africa (Killeen et al. 2002).
But what could be the consequences ever more
frequent travel? What would be the possible
(a)
consequences on pathogens evolution as regards to
resistance and virulence? Vector-borne diseases
such as malaria and water-borne diseases such as
cholera are generally more virulent than diseases
spread by direct infection (Ewald 1994). One reason
for this may be that vector or water-borne diseases
to spread over long distances, and causing infection
of susceptible individuals distant from the infected
individual. In a spatially structured host population, the ability of the pathogen to infect distant
individuals leads to the evolution of a more virulent pathogen (Boots and Sasaki 1999). Developing
travel alters the connections between different
towns or areas (Fig. 10.2). We could have passed
from a regular lattice between the different points
to random net-connections which are permitted by
long and frequent travels. From their analyses on
the consequences of the modification and the evolution of connections, Watts and Strogatz (1998)
suggested that infectious diseases spread more easily in small-word networks than in ‘regular’ lattices. We can predict that the increase in world
travel would have strong consequences on
(b)
(c)
Increasing randomness
Figure 10.2 Connection topology from (a) regular ring lattice, to (b) small-world, to (c) a random network.
Notes: The intermediate connection is called ‘small world’ network, and infectious diseases spread more easily in small-world networks that in regular
lattices. The different means of transport are presented in order to try to illustrate the development of ‘travel man-made ecosystems’ which permit to
link different geographical points and modify the connections within and between populations. No company or factory could be incriminated here for
disseminating pathogens.
Source: Modified from Watts, D. J. and Strogatz, S. H. (1998).
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pathogens dispersal and consequently on the evolution of infectious diseases virulence and resistance, but this could be also applied for all
categories of vectors which are responsible of
pathogen carriages. It seems reasonable to assume
that human societies in the past lived in larger with
more isolated communities. But, modern social networks (Wasserman and Faust 1994) are known to
be small words (Watts and Strogatz 1998), and it
follows that infection networks may also show
‘small world’ connections in modern societies.
When infections occur predominantly locally we
predict a lower virulence than when transmissions
occur predominantly randomly throughout within
and between populations (Boots and Sasaki 1999).
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10.3 Human comfort and
industrialization
Throughout human evolution, people have always
tried to enhance their comfort. Temperature and
humidity have a significant effect on human comfort and health. The most comfortable humidity
range is 40–60%, but air temperature and humidity
are related in respect to comfort or perceived temperature. The combination of temperature and
humidity where people report comfort is termed
the ‘comfort zone’. At the time we are writing this
chapter, an epidemic legionnaire’s disease occurs in
North of France (Pas de Calais). Indeed, 85 persons
where infected during January and February 2004,
and among them 13 died (Fig. 10.3).
1
a
5
2
3
4
Figure 10.3 Legionella disease: infection routes.
Notes: 1: The pathogen responsible for the disease is a bacteria living in fresh water. The optimal growth temperature is between 35 and 40 °C. This
pathogen is present in sanitary facilities (showers, taps, etc.), air conditioning, fountains, greenhouse, cooling towers, etc. For example, bacteria are
presents in droplets coming from factory steam; 2: Bacteria contained in ‘contaminated droplets’ are inhaled by humans, and clinical symptoms arise
after 2–10 days of incubation; 3: The serious form of the disease named ‘Legionnaire’s disease’ generally arise in weakened patients (elderly,
immunocompromised, etc.) which can evolve to a lethal pulmonary infection in about 15% of cases; 4: The treatment is based on antibiotics;
5: While writing this chapter, a Legionella epidemic was raging within the north of France (Department: Pas de Calais). More than 80 cases were
registered during January 2004.
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Legionnaires’ disease is a lung infection
pneumonia) caused by a Legionella pneumophila.
The name of this bacterium was derived from the
original outbreak at the 1976 American Legion
Convention in Philadelphia (Hlady et al. 1993).
These bacteria are readily found in natural aquatic
environments and some species have been recovered from soil. Legionella parasitize Amoeba, and
spread through cysts of these protozoans
(Fliermans 1996). The pathogen can survive in a
wide range of conditions, including temperatures
of 0–63 °C, pH of 5.0–8.5, and dissolved oxygen
concentrations of 0.2–15 ppm in water. Temperature
is a critical determinant for Legionella proliferation.
Legionella and other micro-organisms become
attached to surfaces in an aquatic environment
forming a biofilm. Legionella has been shown to
attach to and to colonize various materials found in
water systems including plastics, rubber, and
wood. But, crucially from the public health perspective, Legionnella are not only found in natural
habitats. These bacteria develop particularly well in
human infrastructures where water is present as
saunas, for example (Den Boer et al. 1998). But the
main human-made ecosystem they colonize seems
to be the cooling systems found, for example, in factories, hotels, and hospitals (Alary and Joly 1992;
Pedro-Botet et al. 2002; Sabria and Yu 2002). For
instance, in January 2000, WorkSafe Western
Australia reported a case of Legionnaires’ disease
from a teacher who had worked in a room supplied
with cooled air from an evaporative air-conditioning
unit, and had also used potting mix while gardening at home. Both potting mix and warm water
allow multiplication of these bacteria.
Figure 10.3 describes the different steps of human
infection by Legionella. But, not only workers who
live in the contaminated building are concerned,
indeed people working or living around the
Legionella source can be infected (Fig. 10.4). For
example, during the 2004 French epidemic discussed
above, the infected patients were people living near
a factory where the bacteria were identified in the
cooling systems. Even though the link between the
presence of the bacteria and human infections was
not clearly established, the French government
decided to stop immediately the factory activity.
Other microbes can contaminate air-conditioning
units and cooling towers which can result in other
health problems for workers and visitors such as
respiratory sensitization and building related
illness, or ‘sick building syndrome’. It is thus
essential to maintain a good indoor air quality at
all times.
Water is essential for life! But drinking water
networks are heterogeneous and constitute real biological reactors, that is to say an ecosystem between
a mobile phase (i.e. water) and an appointed phase
(i.e. biofilm). These networks are continually contaminated by microorganisms (i.e. bacteria, algae,
protozoans, fungi, yeast, metazoans) and nutrients
(i.e. organic dissolved matter) that passed through
the treatment systems or gather from accidental
procedures (i.e. breaks and repairs). Drinking water
networks thus bring together all the favourable
conditions for the maintenance and the spread of
microbial systems diversified and organized in
different trophic levels, and thus constitute real
food webs.
Another example which could well illustrate the
phenomenon of disease induced by the human
desire for comfort is wastewater such as those
encountered near houses in septic tanks. Septic
tanks were designed to improve sanitation.
Bacteria, viruses, protozoans, and worms are
the types of pathogens in wastewater that are
hazardous to human. Bacteria are responsible for
several wastewater related diseases, including
typhoid, bacillary dysentery, gastroenteritis, and
cholera. Depending on the bacteria involved,
symptoms can begin hours to several days after
ingestion. Viruses cannot multiply outside their
hosts, and wastewater is a hostile environment for
them. But enough viruses survive in water to make
people sick. Hepatitis A, polio, and viral gastroenteritis are a few of the diseases that can be
contracted from viruses in wastewater. A protozoan
is the cause of amoebiosis, also known as amoebic
dysentery. Parasitic worms also dwell in untreated
sewage. Tapeworms and pinworms are the most
common parasites found in these wastewaters,
from where their eggs can be ingested. Children and
the elderly are the groups the most significantly
affected by wastewater related diseases.
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1
2
3
Figure 10.4 Persons exposed to Legionnaires’ disease the case of factory cooling towers which could constitute a potential reproductive ground for
Legionella bacteria, Pas de Calais—France 2004: >80 cases of Legionella disease.
Notes: 1: Technical personal intervening near the cooling towers; 2: persons working near the smoke; 3: persons living in buildings and houses near
the factory: the contaminated air penetrating through windows and new air intakes.
10.4 Humans get sick, age, and die!
Modern humans try to live better and longer. These
days, this desire has culminated in massive pharmaceutical and medical industries and associated
science base, as well as on going interest in alternative medicine. Unsurprisingly, some pathogens take
advantage of human illness and death, and of the
new openings provided by medical science.
10.4.1 Sickness
‘Despite a century of often successful prevention and
control efforts, infectious diseases remain an important global problem in public health, causing over
13 million deaths each year. Changes in society,
technology and the microorganisms themselves are
contributing to the emergence of new disease’ Cohen
(2000). During the twentieth century, many medical
and public health officials were optimistic that most
of infectious diseases could be eradicated. This has
patently not occurred, and indeed that the ongoing
emergence of new pathogens is a reality (Liautard
1997). Pathogens have plunged into the new ecological niches provided by new human behaviours and
customs. It would be impossible and tedious to
make an exhaustive review of these diseases,
because they are so numerous. The development of
medical technology in hospital ecosystems lead to
the development of cohorts of opportunistic
pathogens which exploit these new ecosystems.
Diseases emerging in hospital ecosystems are known
under the terminology ‘Nosocomial infections’
(hospital-acquired infections), derived from the
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Greek ‘nosokomeion’, which means hospital.
Hospitals are the source of many diseases because
patients are often immunocompromised, and
because infected people come to hospitals. The
majority of nosocomial infections have an endemic
origin (i.e. inside the hospital), where infection
comes from a microorganism present in the ecosystem, and the surgical intervention renders it infectious. In an important article, Cohen (2000) reviewed
the causes of nosocomial infections in modern medical environments. The classical case is represented
by an inoffensive bacterium that is brought by
the surgeon’s lancet into the body of a patient
and evolves to a septicaemia. Figure 10.5 illustrates
different origins of nosocomial infections where
medical tools can be incriminated. These infections
can be due to microbes that have lived on or in
(i.e. colonized) the patient for many years without
harm before healthcare procedure provides a means
of bypassing the patient’s host defences (Farr 2003).
Nosocomial infections have been known for a
long time in hospital ecosystems: Oliver Wendell
Catheter
Endoscope
2
1
Biopsy catheter
Contaminated hospital environment
Endogenous
Nosocomial infections
Exogenous
Infected patient
3
(a)
Needle (venipuncture)
(b)
4
Prosthesis: new ecosystem
Figure 10.5 Nosocomial infections.
Notes: Following an invasive surgery (i.e. through the skin as illustrated in 1, 2, 3, for example), a patient can be infected by germs coming from an:
Endogenous origin: patient is infected by its own germs following a surgical act and/or because he displays a particular weakness. For example, a patient
under artificial breathing can develop pneumonia from a germ of its own digestive tract, which can go up to the respiratory ways. The same phenomenon
can be observed for an urinary infection from an urinary probe carrier.
Exogenous infection: Cross infections transmitted from a patient to another through hand contacts or medical tools. These infections can be originated
from the germs inhabiting hospital workers, or linked to the contamination of the hospital environment (water, air, material, foods, etc.).
Prosthesis constitutes new ecosystems for pathogens. The figure shows a knee prosthesis (4): (a) before; and (b) after.
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Holmes published a paper on this topic as early as
1843. Nosocomial infections can be directly linked
to medical treatment, or can simply occur during
hospitalization, independently of any medical act.
They concern patients, but also workers present
in this ecosystem. They can occur because the
immune system is busy fighting some other chronic
illness, or for people who are immunocompromised. People can be immunocompromised from
certain diseases (e.g. AIDS), certain medications
(e.g. immunosuppressants or chemotherapy), surgical recovery, or other serious medical complaints
that limit the person’s ability to fight against these
infections (Berche et al. 2000).
These infections can spread by endogenous
or exogenous ways (Fig. 10.5). Many types of
pathogens are involved, including fungal infections
(e.g. Candida, Aspergillus, Fusarium), bacterial and
viral pneumonia (e.g. influenza, Staphylococci,
Pseudomonas) which can be found in different
organs, giving rise to urinary tract infections, surgical site infections, respiratory tract infections, blood
stream infections, skin infections, gastrointestinal
tract infections, central nervous system infections,
and so on. Numerous surgical acts can initiate
nosocomial infections, these fall into three main
types: (i) urogenital probes lead to urinary infections, (ii) catheters are sources of systemic and local
bacterial and viral infections, and (iii) artificial
breathing systems are responsible of pulmonary
infections. For a lead into the extensive literature
on nosocomial infections see Arnow et al. (1993),
Scheckler et al. (1998), Lucet (2000), Lemaitre
and Jarlier (2000), Korinek (2000), and Joly and
Astagneau (2000).
The frequency of nosocomial infections in France
is typical of industrialized countries, with about 7%
of hospitalized patients developing a nosocomial
infection. In other countries it ranges from from 5%
to 12%. In the United States, more than 2 million
cases of nosocomial infections have been reported,
leading to about 80,000 deaths and to 8000 additional days in hospital for 1000 infected patients, all
at a cost of $US5 billion dollars in 1985 (Wenzel
1985; Haley 1991).
In this section on human sickness, we can illustrate the Machiavellianism of pathogens exploiting
163
a human health problem: drug addiction. Many
pathogens from viruses to worms use insect as
vectors in order to infect new hosts. In the same way,
we could do a comparison with medical tools that
pathogens use as vectors. The best and saddest
example could be the syringe which represents
a wonderful vector for pathogens to pass from host
to host. A non sterilized syringe represents a very
efficient ecosystem exploited by many pathogens.
One terrible recent example was provided by HIV
and drug addiction. The HIV virus can be passed
through different venous injections from different
individuals sharing the same syringe. Unfortunately,
this problem does not only occur within drug
addicts; nurses in hospital have been contaminated
by this parasite when taking a blood sample from
infected patients. AIDS is one of the major diseass
at the beginning of the twenty-first century, and we
have to keep in mind the public scandal which
occurred in France at the end of the twentieth
century with contaminated HIV blood. Indeed,
haemophiliacs need recurrent blood transfusions,
and before the use of warmed blood elements, many
of them were infected by HIV through the needle
which served to transfuse them (Fig. 10.5). Most of
them died, and this scourge continues to kill a lot of
people in the world.
10.4.2 Ageing
Modern humans live longer, at least in industrialized countries, where the number of the elderly is
rapidly increasing (Morris and Potter 1997). This
leads to an increasingly large group of hosts ripe for
exploitation. For example, ageing results in senescence of the gut-associated lymphoid tissue, and
decreasing in gastric acid secretion (Feldman et al.
1996). The consequences of these physiological
disturbances lead to an increase of susceptibility to
pathogens. Indeed, as a low pH of the stomach
represents an important barrier to entry of enteric
pathogens, reduction in gastric acidity can increase
the susceptibility to infection by these pathogens
(Morris and Potter 1997). The communal living
environment of some elderly, exacerbated by problems such as incontinence, further creates an
habitat in which enteric and food-borne pathogens
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can spread rapidly (Benett 1993). In a study
between 1968 and 1979 in the United States, Blaser
and Feldman (1981) showed that the frequency of
Salmonella bacteremia increased dramatically in the
elderly compared with other age groups. Salmonella
infections increase the risk of death, and elderly are
often immunocompromised and they are assisted
by a large cohort of medications. This treatment
undeniably leads to the selection of drug resistance
in many categories of pathogens. The grouping of
patients in ‘elderly care homes’ may constitute production units of ‘pathogen resistant ecosystems’,
which will represent a new and complex public
health problem as the population ages. We expect
that pathogens produced in these ecosystems,
many of which may be drug resistant, will spill out
to attack other age groups of the population
(i.e. babies, toddlers, and children)? To our knowledge, policies have not yet considered this ecological problem. It is well known in evolutionary
parasitology that an increase in the number of
susceptible hosts can have dramatic consequences
for the spread of pathogens in the whole population
(Bird Influenza Virus below).
10.4.3 Death
Even if human have largely improved health care
and have lengthened life expectancy, particularly in
industrialized countries, death always occurs.
Humans worship death and we can observe a lot of
flower vases in some cemeteries. These vases can
constitute ideal ecosystems for the development of
different mosquito species larvae. In a very interesting paper, Lancaster et al. (1999) related the invasion of Ae. albopictus into an urban encephalitis
focus, where flower vases ecosystems found in
cemeteries could play an important role.
Elsewhere, O’Meara et al. (1995) investigated the
competition between Aedes aegypti and Ae. albopictus in a US cemetery named Rose Hill, and showed
that until the summer of 1990, only Ae. aegypti
inhabited vases at Rose Hill. Ae. albopictus was first
collected that summer and by 1994, had become the
most prevalent species (i.e. greatest percentage of
vases occupied). Juliano (1998) sampled three
cemeteries in Southern Florida where Aedes inhabit
water-filled stone cemetery vases. From manipulative field experiments, he analysed the mechanisms
involved in the competition between Ae. aegypti
and Ae. albopictus. He showed that, at least at the
three sites tested, Ae. albopictus was more competitive than Ae. aegypti. This invader superiority was
attributed to better resource acquisition in these
ecosystems. Knowing that these mosquito species
are vectors of different pathogenic viruses, these
cemetery ecosystems can play an undeniable role in
mosquito transmitted diseases, at least in the area
concerned.
10.4.4 Surgical progress
Like different mechanical parts of our car, many
organs of our body can be replaced by better functioning parts. Xenotransplantation is the graft
(i.e. skin, tissue) or the transplant (i.e. organ) into
humans of tissue or organs from animals (Wadman
1996). Xenotransplantation seems a very real possibility now that the generation of transgenic
pigs as potential organ donors for humans has
been achieved. Baboons are also likely to be used,
especially so for bone marrow grafting. But, both
baboons and pigs may silently harbour a great variety of viruses belonging mostly but nor exclusively
to the Herpesviridae, Retroviridae, and Papoviridae
families. All these viruses are potentially able to
infect deeply immunocompromised patients. This
may lead to the emergence of deadly viral infections, the so-called ‘xenozoonosis’, among the
recipients and/or the general population (Chastel
1996). Indeed, the majority of viruses that emerged
during these last 30 years displayed a zoonotic
(mainly simians) origin (Morse and Schluederberg
1990). For example, the Herpesvirus simiae , specific
to asian cerpothitecicidae of the genus Macaca and
where it seems to be a largely benign virus,
becomes very dangerous for human when injected
by biting or by accidental injection by infected
syringe or needle (Artensein et al. 1991). DNAs
represent a well-established molecular species
ecosystem where a large number of selfish DNAs
(including number of viruses) are evolving and
pass through generations. Each species harbours its
own selfish DNAs, and they constitute, for
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165
example, a large part of the human genome (De
Meeûs et al. 2003). Therefore, transmission of virus
through grafts is confirmed, and allografts were
reported to be at the origin of primary infections by,
at least, the cytomegalovirus, Epstein–Barr virus,
VIH, and hepatitis C (Chastel 1998). We could be
thus confronted to a new virulent variant of these
viruses or to a genetic matching between close
human and simians viruses (i.e. Herpesvirus,
Retrovirus). We cannot exclude the possibility of an
outbreak of a genetic chimera between human and
animal viruses, or of the ‘complementation’ of a
defective virus. Xenotransplants can come from
transgenic animal in order to avoid graft rejection
by human recipient. ‘I view xenograft tissues as
essentially very complex vectors for shuttling new
viruses in humans’ (Allan 1995).
Prostheses are another example of surgical
progress. The addition of exogenous material leads
to the establishment of new ecosystems inside
the body (Fig. 10.5). These new niches can be
colonized by pathogens. For example, prosthetic
joints, prosthetic implants, and vascular prosthetic
materials are a ‘nest’ for many pathogens such
as group C Streptococcus, Staphylococcus epidermidis,
Staphylococcus aureus, Mycobacterium tuberculosis,
Histoplasma capsulatum (Gillespie 1997; Kleshinski
et al. 2000).
use) and contraceptive methods (i.e. Intra-Uterine
contraceptive Devices—IUDs or coil). The insertion
of tampons or coils in female genital systems represents a new opportunity for pathogens. Urinary
tract infections of women are common, and a
source of considerable expense. The possibility that
tampon usage is a risk factor for recurrent urinary
tract infection has not been studied in detail, but it
has been associated with bacterial vaginosis. The
tampon may facilitate the spread of bacteria from
the vagina to the urethra and bladder (Doran 1998).
Elsewhere, it was thought that IUD infections
spread through lymphatic canals to produce a
perisalpingitis similar to that of postabortal or
postpartum infections. Even if it was not demonstrated that IUDs are directly responsible of these
infections, their role remains to be determined
(Schwarz 1999).
10.4.5 Hygienic progress
10.5.1 Tinned food
Polio was almost unknown until the dramatic
epidemics that terrorised the developed countries
in the twentieth century. This terror led to irrational
responses, such as aggression to immigrants of
shantytowns. Before hygiene was common, infants
were safely immunized against polio by maternal
milk. However, once hygiene standards were high
in developed countries, individuals were first
exposure to polio occured at older ages, when the
clinical complications are likely. Thus, changing
hygiene habits has allowed the poliovirus to
the exploitation of new habitats, with dramatic
consequences for the host (Schlein 1998; Seytre and
Schaffer 2004).
Medical progress has led to women being
attacked by pathogens due to menses (i.e. tampon
A major problem to which human populations
were and are still confronted is to food preservation. Different methods of food conservation were
developed in human societies, but two of them are
the more used, at least in industrialized countries:
tinned and cooled food.
Listeriosis, a serious infection caused by food
contaminated by the bacterium Listeria monocytes,
has recently been recognized as an important
health problem in the United States and European
countries (Lorber 1997; Silver 1998). Listeriosis is a
disease that is enhanced by alimentary progress.
This bacterium is frequently found in soil and
water, and becomes pathogenic for human when
ingested at high densities. Naturally contaminated
food never presents dangerous densities of this
10.5 Human need to eat!
Life, reduced to its simplest expression, could be
caricatured through two main functions for each
individual in each plant and animal species: survival and reproduction. Food is the fuel for this, but
eating is not without risk. Our new food habitats
have opened up new niches for many pathogens.
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bacterium, but this pathogen experiences an
increase of its population demography at low temperatures. Refrigerators constitute a favourable
ecosystem for these bacterial populations where
they can reach the infectious quantity dose for
human.
Human brucellosis or ‘Bang’s disease’ which was
discovered a century ago remains poorly known
and difficult to treat. Pathogens responsible for the
disease are bacteria belonging to the genus Brucella,
a strictly aerobic coccobacillus. Brucella can enter
the body via the skin, respiratory tract, or digestive
tract. Once there, this intracellular organism can
enter the blood and the lymphatic canals where it
multiplies inside the phagocytes. The disease
spreads through animal contacts or contaminated
food, especially cheese! Cheese permits milk to be
preserved, and several hundred of people are
infected each year in France. The disease causes
nausea, meningitis, hepatitis, and miscarriages
(Straight and Martin 2002).
Botulism is a food-borne disease; the agent of the
disease is an anaerobic bacteria Clostridium botulinium with a spore-forming rod that produces a
neurotoxin. The spores are heat-resistant and can
survive in foods that are incorrectly or minimally
processed. The disease is caused by the neurotoxin
produced by C. botulinium that is present in the
food (Smith and Sugiyama 1988). The organism
and its spores are widely distributed in nature
(e.g. cultivated and forest soils, coastal waters, gut
of fish and mammals, gills and viscera of crabs and
other shellfishes), but the types of foods involved in
botulism vary according to regional food preservation and eating habits. Almost any type of food that
is not too acidic (pH above 4.6) can support the
growth and toxin production of C. botulinium.
Botulinal toxin has been evidenced in a considerable variety of foods, such as canned corn, soups,
ham, sausage, smoked, and salted fish. The incidence of the disease is low, but the mortality is high
if not immediately and properly treated.
10.5.2 Intensive farming
High intensity farming has been very good at producing large amounts of cheap food, but has also
opened up new parts of the human–pathogen
ecosystem. Salmonellosis is one of the most common food-borne illness causing enteric infections in
developed countries. The pathogens are bacteria
(Salmonella) which consist of a range of very related
bacteria, many of which are pathogenic to humans
and animals (Thorns 2000). The strains which are
implicated in the diseases are generally different
serovars of Salmonella enterica that caused diseases
of the intestine, as suggested by their name. For
example, S. enterica serovar typhi is the causative
agent of typhoid fever. It is very common in developing countries, where it causes a serious and often
fatal disease. Salmonella bacteria primarily invade
the wall of the intestines causing inflammation and
damage. Infection can spread in the body through
the bloodstream to other organs such as liver,
spleen, lung, joints, placenta, or foetus, and the
membrane surrounding the brain. Toxic substances
produced by bacteria can be released and affect the
rest of the body. Salmonella has evolved mechanisms to escape our immune system (Olsen et al.
2001). In the liver, bacteria can grow again, and be
released back into the intestine. S. enterica serovar
enteritidis has become the single most common
cause of poisoning in the United States in the last
20 years. Salmonella are found in contaminated
food, with recent increases in the number S. enteritidis
a consequence of mass production chicken farms.
When tens or hundreds of thousands of chickens
live together, die together and are processed
together, a Salmonella infection can rapidly spread
throughout the whole food chain, and hence
Salmonella can be rapidly dispersed among million
of people.
Changed farming practices have also led to
new opportunities for non-food-borne human
pathogens. In the Asillo zone, located at a very high
altitude of 3910 m in the Peruvian Altiplano, high
levels of human infection by Fasciola hepatica
(i.e. the liver fluke) were linked to man-made irrigation zones. Man-made irrigation areas are built
only recently to which both liver fluke and lymnaeid snails (i.e. the first intermediate host of the
liver fluke) have quickly adapted. Such man-made
water resources in high altitude of Andean countries dangerously inflate the parasitic risk, because
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the lack of drinking water and running water inside
dwellings forces inhabitants to obtain water from
irrigation canals and drainage channels (Esteban
et al. 2002). Elsewhere, it is largely recognized that
a significant amount of malaria transmission in
Africa and Madagascar is due to human activities.
Modifications of the environment resulting from
land use often create or alter habitats for mosquito
vectors, and may indirectly affect parasite development rates, and the lifespan of mosquito (Service
1991; Ault 1994; Coluzzi 1994).
Marine ecosystems are also on the danger list due
to pollution and aquaculture which modify all
parameters of natural equilibrium. The organic pollution exerts both oppressing and stimulating influences, with industrial waste depressing the
formation and function of parasite systems. Some
current aquaculture practices are environmentally
benign, others, especially those in some of the
fastest growing portions of the industry, can
degrade water quality, transmit diseases to wild
populations, disrupt marine ecosystems, and
spread invasive parasites and pathogens species
(Maender 2002; Young 2003, see also Chapter 7).
We think that it is now important to present a
current very deep problem which links public and
veterinary health. At the time we are writing this
chapter at the beginning of 2004, public opinion
and World Health Organization is strongly focused
on two animal zoonotic diseases which have arisen
recently, particularly in Asia. ‘The terror of the
unknown is seldom better displayed than by the
response of a population to the appearance of an
epidemic, particularly when the epidemic strikes
without apparent cause’. This quote from Kass
(1977) concerned the emergence of legionnaires’
disease, and it well describes public response to
the recent emergence of an atypical pneumonia
named as Severe Acute Respiratory Syndrome
(SARS). SARS was first recognized in the
Guangdong Province of China, in November 2002.
Subsequent to its introduction in Hong Kong in
mid-February 2003, the virus spread to more than
thirteen countries and caused disease across five
continents. According to the World Health
Organisation (WHO) in January 2004, a cumulative
total of eight thousand SARS cases with more than
167
800 deaths had been reported. A novel coronavirus
was identified as the human etiological agent of
SARS, causing a similar disease in cynomolgous
macaques (Peiris et al. 2003). Because cases where
SARS was first diagnosed occurred in restaurant
workers handling wild mammals and exotic food,
scientists focused on wild animals recently captured and marketed for consumption. Their work
provides evidence that SARS shifts from animals to
humans, possibly frequently (Guan et al. 2003).
Elsewhere, Stanhope et al. (in press) have confirmed this host shift, because they could identified
that SARS-CoV has a recombinant history with
lineages of types I and III virus, concomitant
with the reassortment of bird and mammalian
coronaviruses. Food marketing trades could thus
provide the opportunity animal ScoV-like viruses
to amplify and to be transmitted to new hosts,
including humans. Even if the natural reservoir is
not clearly identified, market animals (civets, raccoon dog, and ferret badgers for example) might
be compatible hosts that increase the opportunity
for transmission of the virus to humans. Markets
constitute thus man-made ecosystems favourable
to a new set of pathogenic agents. Thousand of
these aforesaid animal species have been slaughtered as a preventive measure. But, is it the most
efficient solution?
The Avian Influenza outbreak which is currently
raging in south east Asia is related to SARS only in
demonstrating how the so-called zoonotic diseases
in animals can become a threat to human health. It
clearly illustrates how man-made intensive farming
ecosystems can represent spring boards for new
pathogens. Highly pathogenic avian influenza
A viruses of subtypes H5 and H7 belong to the
Orthomyxoviridae family, and are the causative
agent of fowl plague in poultry. Type A influenza
viruses are those which affect humans, but also
pigs, horses, and some marine mammals (whales
and seals). There are three types (A, B, and C) of
influenza viruses, depending on the antigens
detected in the virus capsid. The antigens that are
used to recognize the different viruses belong to
two kinds of glycoproteins, hemagglutinin (HA),
and neuramidase (NA). There are fifteen different
HA antigens (H1 to H15) and nine different NA
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antigens (N1 to N9) for influenza A. Human
disease historically has been caused by three
subtypes of HA (H1, H2, and H3) and two subtypes
of NA (N1 and N2), which were responsible for
million of deaths around the world, through different pandemics. All known subtypes of influenza A
can be found in birds, but only subtypes H5 and H7
have caused severe disease outbreaks in bird populations (Fouchier et al. 2004). Figure 10.6 illustrates
the life cycle and possible routes taken by these
pathogens; migratory birds and waterfowl are
thought to serve as reservoir hosts for influenza A
virus in nature (Murphy and Webster 1996), but
waterfowls generally do not suffer from the disease
when infected with avian influenza.
The viruses easily circulate among birds worldwide as they are very contagious for birds, and can
be deadly, particularly for domesticated birds like
chickens and turkeys. The disease spreads
rapidly within poultry flocks and between farms.
Direct contact of domestic flocks with wild migratory waterfowls has been implicated as a frequent
cause of epidemics, and live bird markets are implicated in the spread of the disease. Avian influenza
A virus may initiate new pandemics in humans
because the human population is serologically
naive toward most HA and NA subtypes (Fouchier
et al. 2004). Until recently, it was considered that
pigs were the obligate intermediate host for transmission of these virus types to humans (Yasuda et
al. 1991; Webster 1997, Fig. 10.6). Past influenza
pandemics have led to high levels of illness, death,
social disruption and economic loss (Fig. 10.6), but
in general, avian influenza viruses do not replicate
efficiently or cause disease in humans (Bear and
Webster 1991). However, the highly pathogenic
influenza virus subtype H5N1, first documented
in Hong Kong in 1997, was transmitted in 2003
from bird to humans, and was responsible for
a very serious outbreak, the seriousness of which is
still unclear at time of writing. Nevertheless, this
epidemic is an illustration of how intensive poultry
farming ecosystems (i.e. increasing host density
to increase food productivity) are responsible for
these new outbreaks, at least in the countries
where this influenza H5N1 virus finds its origin
(Fig. 10.6).
10.5.3 But how can viruses of high and low
virulence coexist?
This is a case of a classical question in evolutionary
biology: what conditions are required to maintain
polymorphism (genetic and/or phenotypic variability), in space and time, within and among
populations of all kind of species? Literature on the
topic is rich (e.g. De Meeüs et al. 1993 and 1995;
De Meeüs and Renaud 1996 for examples). We will
not attempt here to make a review on this topic, but
in their paper published in 2004, Boots, Hudson,
and Sasaki developed a theoretical model to envisage the conditions for maintenance and spreading
of low versus high virulent type of pathogens
(e.g. viruses). The model clearly shows that large
shifts in pathogen virulence are related to host
population structure (i.e. demography and genetic).
Poultry flock structures managed by humans
represent new ecological and demographic configurations for the evolution and emergence of new
virulent pathogen strains, which enter more and
more in contact with human populations.
Given the increasing long-distance movement of people
and domestic animals around the modern world, our
results have important implications for emerging diseases
in general. Recombination among avirulent (and therefore
possibly previously undetected) strains of viruses and
other pathogens may produce new virulent strains that
may spread through vertebrate host populations because
they have shifted to a new evolutionary stable state.
(Boots et al. 2004)
What is happening with the current influenza
outbreak has been clearly predicted by theoretical
population biology models. This stresses the need
there is that such approaches should be taken now
into account in future public and veterinary health
control.
Pathogens and parasites can use different manmade ecosystems to spread and threaten human’s
health. Indeed, as illustrated in the case of influenza
virus, the pathogen can first exploit the intensive
farming processes (i.e. food production) in order
to emerge and rapidly infect humans (Fig. 10.6),
and second, hitch-hike the man-made ‘travel ecosystems’ (i.e. plane, boat, or train) to spread among
populations and become pandemic (Fig. 10.2).
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169
1
2
N1
H5
4
3
A
B
Figure 10.6 Avian influenza: (a) infecting routes and (b) geographical outbreaks in 2004 and the Avian influenza virus.
Notes: (a) Waterfowl are thought to be the natural reservoir of Avian influenza A viruses (1). Viruses replicate in the intestines as well as the respiratory
tract of birds.
During migratory processes of birds, poultry flocks become infected when contacts between them and naturally infected birds are established. In the 2004
outbreak, very large quantities of virus were excreted in the faeces of infected farming birds, resulting in widespread contamination of the environment
(2). This presence of numerous H5N1 subtype created one of the most important risks for human exposure and subsequent infection.
Some findings support the hypothesis that the pig was a ‘mixing vessel’, able to produce new virus subtypes by genetic reassortment that can infect
humans. Until recently, it was supposed that pigs were obligatory intermediate hosts for human infections (3). Nevertheless, epizoonose of Avian Influenza
in different Asian countries in 2004 confirmed the possibility of direct human infection from birds, via the H5N1 Influenza virus subtype (4). Indeed, if Avian
Influenza viruses lack the receptors needed to infect mammals efficiently, the infection of humans observed during the 2004 and two previous H5N1
outbreaks demonstrates that transmission from birds to mammals, including humans, can occur despite the lack of receptors. (b) The influenza
outbreak in 2004 affected more than ten Asian countries.
From the 20 February 2004, Thai authorities reported that 147 patients were admitted in the hospital since the beginning of the zoonotic outbreak, and
eight died. The main problem for all countries around the world is that this Asian influenza outbreak became pandemic. There were three pandemics in the
twentieth century. All of them spread worldwide within one year:
– 1918–19: ‘Spanish flu’ [H1N1]: 20–50 million people died worldwide. Nearly half of those who died were young, and healthy adults.
– 1957–58: ‘Asian flu’ [H2N2]: First identified in China, the Asian flu spread in the United States and caused about 70,000 deaths.
– 1968–69: ‘Hong Kong flu’ [H3N2]: First identified in Hong Kong, the virus spread in the United States and caused about 35,000 deaths.
More than seven billion poultry were slaughtered in infected Asian countries which suggest the farming of billions of bird in this geographic area. This
demographic situation is favourable for (i) the emergence and the spread of highly virulent strains of pathogens within and between stock breeding,
and (ii) the transfer between host species, including humans.
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In front of such processes, we do not know which
zoonoses will become important in public health in
the future, and we must be vigilant over the
emergence of new pathogens.
10.6 Concluding remarks
It was not our intention to produce an exhaustive
review of all situations where pathogens and parasites found new infectious routes associated with
human customs, development, and technology, and
we are conscious of many gaps (for instance,
Western beds provide an excellent ecosystem for
ectoparasites such as lice, fleas, ticks, sarcoptes, bed
bugs, etc.). But our goal was to present some
aspects which we believe will become more and
more topical given current trends. We believe
future key questions will be how societies could
and should manage (i) population ageing,
(ii) need of food access, (iii) earth demographic
growth, (iv) people density and urbanization,
(v) new technical and medical tools. This is a challenge for which we must get prepared. Pathogens
are everywhere and can adapt to a wide panel of
environments (even computers). Indeed, we may
be just at the beginning of the evolution of
pathogens and parasites evolution in our biosphere
ecosystem.
CONCLUSION
Parasites, communities, and
ecosystems: conclusions and
perspectives
Gary G. Mittelbach
What is a parasite?
Most ecologists harbour a classic, taxonomic view
of parasites; that is, parasites are protozoans or
metazoans that occupy and harm their free-living
hosts. Visions of worms come to mind. Yet, as the
chapters in this book forcefully argue, the definition
of a parasite is much broader than this traditional
view (e.g. Guégan et al., Chapter 2). In fact, Moore
(2002) suggests that parasites are like pornography—they elude definition (but we may know
them when we see them). Clearly, many bacteria,
viruses, fungi, and other symbiotic organisms may
be viewed as parasites. If we adopt this broad perspective, then we soon realize that most of the
world’s species are probably parasitic (Price 1980;
Toft 1986). Further, as Brown et al. (Chapter 9) note,
‘If an organism is not a parasite, then it harbors parasites, as do many parasites themselves’. Thus, we
reach the inevitable conclusion that the majority of
species interactions also involve parasitism.
Community ecologists have long focused on
species interactions as major determinants of the
distribution and abundance of organisms. More
recently, ecosystem ecologists also have begun to
recognize the importance of species and species
interactions to the functioning of ecosystems
(e.g. Loreau et al. 2001; Tilman et al. 2001; Loreau
et al. Chapter 1). Yet, studies of parasites continue to
W. K. Kellogg Biological Station and Department of Zoology
Michigan State University, Hickory Corners, MI.
lie outside mainstream community and ecosystem
ecology. As Loreau et al. (Chapter 1) discovered,
‘ . . . the journal Ecosystems has not published a single
paper containing the words parasite, parasitism or
parasitoid in its title, keywords or even abstract’
since it was founded in 1998. No doubt, the journal
Ecosystems has covered topics that would be
included in our broad definition of parasites (e.g.
mycorrhizal fungal associations). But, the point
remains that parasites are not included in the everyday thinking of most community and ecosystem
ecologists. Why is this the case?
As the authors of this book point out, there are
many possible reasons. For one, parasites are hard
to see. They are often small and live inside other
organisms, and ecologists do not notice them when
we routinely sample communities and ecosystems.
Second, if we do find parasites, they can be repulsive. When our field sampling turns up a sick or
infected animal (or even plant), we often shy away.
Third (and most important, I think), is that the
effects of parasites may be subtle. For example, we
may see predation in action, but we are unlikely to
notice that the reason one prey was eaten and the
other was not was because of a difference in parasite load or disease. Or, we may discover that interspecific competition determines the distribution of
plant species along an environmental gradient, but
we do not see that it was a fungal infection that
tipped the competitive balance between the species.
One of the important messages of this book is that
parasites influence the interactions between species
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and that while the mechanisms may be subtle, the
results can be profound.
How can ecologists better incorporate the effects
of parasites into studies of communities and
ecosystems? The contributors to this book have
identified many potential avenues for progress. In
this concluding chapter, I gather together some of
the ideas developed in this book and (along with
the authors) try to highlight future directions for
study. Some of these ‘future directions’ are new,
exciting areas of active research. Others are old,
tough nuts to crack—challenging problems that
will yield only to continued hard work and careful
thought.
It was Mark Twain who quipped that America
and England are ‘Two nations separated by a common language’. Likewise, building stronger linkages between ecology and parasitology will
require, in part, better communication. Ecologists
and parasitologists/epidemiologists are traditionally trained in separate departments, with little
overlap in coursework and little overlap in vocabulary. As a consequence, ecologists are often stymied
by the wealth of specialized terms used by parasitologists to describe the complex life cycles of
their organisms. Similarly, ecologists have their
own specialized jargon to describe the myriad ways
in which species may interact with each other and
with their environment. In summarizing the
research themes below, I try to note examples of
where ecologists and parasitologists have been
studying the same processes, but describing it with
a different language.
How do parasites affect communities
and ecosystems?
Trait-mediated effects
Parasites can strongly affect the dynamics of their
host populations and a rich tradition of theory and
empirical data underlies the study of host/parasite
dynamics (Møller, Chapter 3). In the past, most
studies have considered only the direct effects of
parasites on host mortality or host fecundity.
However, there is now a growing body of work
documenting how parasites affect host behaviours
as well (e.g. Brown et al. Chapter 9; see also Poulin
1994a; Moore 2002; Thomas et al. 2004). In many
cases, parasites alter host behaviours in ways that
increase the host’s probability of being eaten,
thereby increasing the parasite’s likelihood of
transmission to the next host. Thus, parasites may
affect host densities through direct impacts on host
mortality or fecundity, or indirectly, through
changes in host behaviour, morphology, or physiology. Community ecologists have classified the analogous impacts of predators on their prey as either
density-mediated or trait-mediated effects (Abrams
et al. 1996). Interestingly, the typical trait-mediated
effects of the parasite on its host tend to increase
host mortality, while the typical trait-mediated
effects of a predator on its prey result in a decrease
in mortality. There is currently great interest in
understanding the relative importance of traitmediated and density-mediated effects of predators
on the structure of ecological communities (e.g.
Werner and Peacor 2003 and other papers in this
special feature in Ecology). Surprising, however, the
impacts of parasites on host behaviours are rarely, if
ever, mentioned as examples of trait-mediated indirect effects. This surely needs to be remedied, both
by ecologists and parasitologists.
Cascading effects and food webs
How might the effects of parasites on host densities
and host behaviours impact communities and
ecosystems? In perhaps the simplest case, if parasites affect the abundance of a keystone species
(sensu Paine 1966), the impact may cascade dramatically through the community. Loreau et al.
(Chapter 1) suggest that these effects will be most
dramatic when the affected host species occurs
high in the food web. On the other hand, we would
also expect to see strong, community-wide effects
when the affected host species is an abundant foundation species (sensu Bruno et al. 2003). For example, the near elimination of the American chestnut
(Castanea dentate) by a fungal pathogen in the early
1900s dramatically altered the structure of eastern
US deciduous forests. How this changed the functioning of the ecosystem is unknown. However,
given the ability of some pathogens to completely
CONCLUSION
decimate their hosts, the cascading effects of
parasites (defined in the broad sense) may be much
larger than those commonly attributed to textbook
examples of keystone predators.
Recent interest in the impacts of biodiversity on
ecosystem functioning suggests further mechanisms by which parasite effects on host species
abundance may impact ecosystems. As Loreau
et al. (Chapter 1) note, ‘An important limitation of
virtually all recent theoretic and experimental
studies on the effects of biodiversity on ecosystem
function and stability is that they have concerned
single trophic levels—primary producers for the
most part’. However, we know that interactions
between trophic levels may affect the biomass, productivity, and functional composition of different
trophic levels, including primary producers.
Therefore, incorporating multiple trophic levels
into theoretical and experimental studies of biodiversity and ecosystem functioning is a critical next
step (e.g. Downing and Leibold 2002; Duffy et al.
2003; Thébault and Loreau 2003; Petchey et al.
2004). However, incorporating parasites into ecology’s well-developed framework of food chains
and food webs is challenging to say the least
(Sukhdeo and Hernandez, Chapter 4). In those
cases where parasites kill their hosts, the problem
is somewhat easier. Parasitoids act much like ‘standard’ ecological predators and a substantial body
of theory and empirical studies describes this ‘consumer-resource interaction’ (Murdoch et al. 2003).
Consumer–resource interactions constitute the
building blocks of theoretical and real-world food
chains and food webs. However, as noted earlier,
the effects of many parasites are sublethal.
Incorporating these sublethal effects of parasites
may require approaches like those recently used by
ecologists to incorporate the trait-mediated effects
of ‘standard’ ecological predators into food webs
(e.g. Abrams 1995, 2004). The complex life cycles of
many parasites, with their multiple hosts and
multiple life stages, further complicates the
prospect of effectively incorporating this important class of organisms into ecological food webs.
Sukhdeo and Hernandez (Chapter 4) present some
ideas for how to attack the difficult problem of
including parasites in food webs.
173
Shared parasites, apparent competition, and
parasite-mediated coexistence
About 25 years ago, Holt (1977) first developed the
mathematical theory showing that species sharing
a predator may negatively affect each other’s abundance and thereby ‘appear’ to compete. Since that
time, the theory of ‘apparent competition’ has come
to occupy a fundamental place in community ecology and numerous studies have documented its
importance in nature. As Thomas et al. (Chapter 8)
and others note, hosts that share a parasite species
may interact via apparent competition just as prey
species that share a predator. However, the impact
of shared parasites on their host species can be
much more complex than the impact of shared
predators on their prey, due to the fact that parasites may require intermediate hosts, that hosts
may recover from infection (and become immune),
and that transmission rates may vary among host
species (Holt et al. 1994). As Thomas et al. (Chapter 8)
note, ‘It is important to emphasize that changes in
prey abundance though the actions of a non-specific parasite can lead to a range of indirect effects
that are predicted to enhance or destroy host
species diversity. Understanding these effects is the
challenge of empirical community ecology.’
Predators may enhance species diversity as well
as reduce it and ecologists have identified a number
of way in which predators may promote the coexistence of competing species. These include: (1) selective predation on the competitive dominant (Paine
1966; Lubchenco 1978); (2) frequency-dependent
predation where mortality falls selectively on the
more abundant species (Roughgarden and Feldman
1975; Vance 1978); and (3) predation that opens up
‘patches’ for species that exhibit a tradeoff between
colonizing ability and competitive ability (Slatkin
1974; Caswell 1978; Connell 1978). Each of these
classic predator-mediated coexistence mechanisms
may apply to parasites as well as predators.
While parasites are commonly viewed as harmful
to the host (e.g. as ‘shared enemies’ above), Brown
et al. (Chapter 9) note that ‘ . . . this simple categorization can hide a more interesting mix of antagonistic and overlapping interests’. For example, the
boundary between parasite and mutualist may be
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easily blurred. In the case of mycorrhizal fungi that
infect the roots of plants, the interaction between the
plant and the fungus is mutualistic in relatively lowresource environments. The fungus benefits the
plant in obtaining soil nutrients and the plant benefits the fungus by ‘leaking’ root exudates. However,
in high-resource environments, the fungus becomes
a parasite on the plant. Thus, we need to view the
interaction between host and parasite as context
dependent in the same way that ecologists see context dependency in the interactions between species
within a community (i.e. interactions are affected by
the nature of the abiotic environment, the presence/absence of other species, etc.). ‘Viewing the
host-parasite interaction as a complex mix of interests, or desiderata (Dawkins 1990) is an important
step away from the medically influenced view of
parasites being always virulent to some degree’
(Brown et al. Chapter 9).
Species invasions and parasite escape
Recent evidence suggests that parasites may play a
major role in determining the magnitude and
impact of species invasions. Species invasions,
along with habitat destruction, are perhaps the two
greatest threats to biodiversity on a global scale. In
the United States alone the economic cost of invasive species is estimated at >$100 billion dollars
annually. The enemy release hypothesis proposes
that one of the factors underlying the successful
introduction and spread of exotic species is that
they may leave many of their natural enemies
behind. The enemy release hypothesis has a long
history in ecology (Darwin 1859; Elton 1958) and
initially ecologists focused on species escapes from
herbivore and predator ‘enemies’ (Keane and
Crawley 2002). However, recent studies suggest
that the escape from parasite ‘enemies’ may be
equally or more important.
Mitchell and Power (2003), Torchin et al. (2003),
and Torchin and Mitchell (2004) show that on average, introduced plants and animals escape more
than half of their native parasites and this escape is
due to both a reduction in the number of parasite
species infecting introduced species and a reduction
in the percentage of individuals infected (parasite
prevalence). Further, while introduced species may
acquire new parasite species from the introduced
range, on average they acquire <25% of the parasite
species they escape (Mitchell and Power 2003;
Torchin et al. 2003). How important is this release
from parasites in contributing to the demographic
success and expansion of exotics in their new habitat? The answer awaits experimental tests (e.g.
Callaway et al. 2004), however, the correlative patterns are suggestive (Torchin and Mitchell 2004).
Also, because introduced species have been shown
to accumulate parasite species through time
(Cornell and Hawkins 1993; Torchin et al. 2001), it is
tempting to ascribe the commonly observed boom
and bust of many introduced species to any early
escape from natural enemies (parasites) and a subsequent increase in acquired enemies through time.
The success and failure of purposeful species introductions also provides evidence of the role of parasites in species invasions, as shown by Møller’s
(Chapter 3) work on the immune defences of bird
species introduced to New Zealand in the late 1800s.
Although it is too early to say how important parasites are in determining the successful establishment
and demographic response of introduced species,
this is clearly an area where parasites may play an
important role in communities and ecosystems.
The ecosystems of parasites
Ecosystem types
In the discussions above, I have been mostly concerned with the roles that parasites play in communities and ecosystems. However, what about the
ecosystems of parasites themselves? This is a complex and fascinating topic, driven in part by the fact
that parasites occupy two classes of ecosystems. As
Brown et al. (Chapter 9) note, we can think of the
host as the first ecosystem that the parasite occupies. Numerous interactions may occur between
parasite species within the host and parasites may
transform or ‘engineer’ their host ecosystem in
complex and interesting ways (Thomas et al.
Chapter 8; Tinsley, Chapter 6). The second ecosystem that parasites occupy is the larger ‘global’
ecosystem that contains the host population(s). This
CONCLUSION
ecosystem includes all the complex spatial and
temporal dynamics associated with each host population (Brown et al. Chapter 9, Holt and Boulinier,
Chapter 5). The field of parasitology tends to focus
on the first ‘host’ ecosystem, while studies of the
‘global’ ecosystem tend to fail within the domain of
epidemiology and more recently the rapidly developing field of the ecology of infectious diseases
(Grenfell and Dobson 1995). Understanding the
ecology of parasites and their impacts necessarily
includes studying both ecosystems.
Ecosystems and environmental change
The chapters by Lafferty and Kuris (Chapter 7),
Renaud et al. (Chapter 10), and Tinsley (Chapter 6)
highlight important ways in which environmental
change and human-made environments impact the
ecosystems in which parasites occur. In recent years,
ecologists have documented how species ranges are
shifting in response to climate change (Parmesan
and Yohe 2003; Root et al. 2003), concluding that such
shifts will have profound effects on species interactions and biodiversity (Thomas et al. 2004). The
study by Thomas et al. (2004) predicts that 18–35% of
species in their sample regions will be ‘committed to
extinction’ by 2050 due to climatic effects on species’s
ranges. Likewise, climate change may alter host and
parasite geographical ranges, with potentially dramatic consequences for disease outbreaks (Harvell
et al. 2002). Many aspects of host/parasite ecology
are climate dependent and forecasting the effects of
climate variation on infectious diseases is an area of
active research (e.g. Patz 2002; Rodo et al. 2002).
In addition to altering the natural ecosystems of
parasites, human have created entirely new and
novel ecosystems for parasites, to which they have
rapidly adapted. The chapter on ‘Parasitism in
man-made ecosystems’ by Renaud et al. (Chapter 10)
presents a series of fascinating (and frightening)
examples of new ecosystems and new ecological
niches (ranging from hospitals, to cemeteries, to air
conditioning units) that have been colonized by
opportunistic pathogens. Understanding the ecology of parasites in these new ecosystems represents
one of the many emerging links between ecology
and public health.
175
Spatial scale, meta-populations and
meta-communities, and the effects of local
and regional processes
As Guégan et al. (Chapter 2) and Holt and Boulinier
(Chapter 5) note, the fields of ecology, parasitology,
and epidemiology are each profoundly influenced
by spatially dependent processes. Both free-living
and parasitic organisms may function as metapopulations (Grenfell and Harwood 1997; Hanski
1999). Moreover, just as the dispersal of individuals
may link the dynamics of populations in a metapopulation, the dispersal of species may link
the dynamics of communities across a landscape.
The ‘meta-community’ model is an area of active
research in ecology (e.g. Mouquet and Loreau 2003;
Leibold et al. 2004), with theory predicting that the
composition of any local community is the result of
within-community interactions and the dispersal of
species between communities. In addition, the
response of communities and ecosystems to environmental change (e.g., global warming) may
depend critically on the types of species present
and their traits. When new species are introduced
from the regional species pool, communities and
ecosystems have the potential to function as complex adaptive systems responding to these environmental changes (Norberg et al. 2001; Norberg 2004).
To date, meta-community theory has only considered free-living organisms, but of course parasites
might exhibit meta-community properties as well.
The assemblage of parasite species within a host
may be viewed as a community of parasites that
interact with their environment (host) and with
each other. The outcome of these interactions
will depend on the traits of the species present
and on the potential for new species to invade the
‘community’.
Many of the spatial biodiversity patterns
observed in free-living organism (e.g. species–area
relationships, species richness–isolation relationships, local versus regional richness relationships)
are found in parasitic organisms as well (Guégan et
al. Chapter 2). The best-known biodiversity pattern,
the increase in species richness observed when
travelling from the poles to the tropics (i.e. the
latitudinal gradient), was described more than
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200 years ago (Forster 1778; von Humboldt 1808)
and has been documented in a wide variety of freeliving taxa (see Willig et al. 2003). Broad-scale studies of parasite species richness are far less common
and there is disagreement over how well parasites
fit the classic pattern of increasing diversity with
decreasing latitude (e.g. Rohde 1999; Willig et al.
2003). In Chapter 2, Guégan et al. discuss a new
data set by Guernier et al. (2004) that examines the
geographical distribution of >200 species of human
pathogens (bacteria, viruses, fungi, protozoa, and
helminthes). This extensive data set shows that
pathogen species richness is strongly correlated
with latitude in the classical pattern and that the
effect of latitude remains after correcting for
cofactors such as area and socio-demographic variables. Understanding the mechanisms driving
broad-scale diversity gradients is an area of intense
ecological research. As Guégan et al. note, parasite
diversity may simply follow host species diversity,
or instead, the same general processes may drive
broad-scale diversity gradients in both free-living
and parasitic groups. Further studies on broadscale diversity patterns of parasites and pathogens
are needed, as are theoretical and empirical
studies that examine the effects of interacting
spatial scales.
Final comments
While writing this chapter I thought many times of
Hutchinson’s little paper on ‘Copepodology for the
ornithologist’ (Hutchinson 1951). Hutchinson
wrote this paper (remembered more for its title
than its content) because he wanted to share what
he had recently learned from studying copepods
with a broader audience of evolutionary biologists.
In his introductory paragraph, Hutchinson notes
that ‘ornothologists and other students of terrestrial
ecology’ were unlikely to read an account of
copepods in his forthcoming Treatise on Limnology.
It is important that we remember Hutchinson’s
example. We all tend to become specialists in our
own fields and the daily deluge of scientific papers
overwhelms our abilities to keep up even in our
own area. But, breakthroughs often come about
when we recognize the generality of pattern or
mechanism. ‘Parasitology for the ecologist?’
‘Ecology for the parasitologist?’—readers of this
book will have discovered some of both.
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Index
abiotic substances 14
abundance–area relationship 43
abundance–occupancy
relationships 50–1
Acanthocephalan 64–5, 87, 118, 136
Acanthocephalus sp. 64–5
acaricides 6
acid precipitation 118
Acipenser sp. 130
adaptation 83, 86–7, 146
abiotic factors 86–7
arctic 91
deep sea 87
deserts 87–92
extremely varying 91–2
for transmission 146
adaptive dynamics 150
Adelina parasite 10
Adelina tribolii 127
Aedes albopictus 157
Aedes sp. 164
ageing 163–4
agents of interference
competition 125
aggregation 33, 44, 72–3
air pollution 118
Alectoris rufa 35
allopatry 80
Alopex lagopus 72
altruistic trait 145
Anderson–May model 44–5
Anguilla rostrata 118
Anguina tritici 86
anhydrobiosis 110
Anopheles sp. 157–8
anthelminthic treatment 46–7
Anthopleura aureoradiata 134
Apodemus sylvaticus 27
apparent competition 125–30, 153,
173–4
and mathematical models 126
and migration 129
apparent mutualism 126
arctic ecosystems 71, 91
arrested development 45–6
Ascaris suum 92
Aspergillus sydowii 122
assault 143
Austrovenus stutchburji 134
autotrophic organisms 14
avian influenza 167–9
Bang’s disease 166
Batillaria attramentaria 131
between-group fitness 144
between-season transfer 88
between-species transmission 126
biodiversity 7–9, 16
and ecosystem functioning 16–18
loss 114–17
and Lyme disease 8, 123
and parasitism 7
plant biodiversity 7
biomass 20
plant 20
pyramids 65–6
Borrelia burgdorferi 8
bottom-up control 19, 24–5
botulism 166
browsers 56
Brucella sp. 166
brucellosis 166
buffalo measles 3
Buteo jamaicensis 52
caecal nematode 3–4
Trichostrongylus tenius 3
Calluna vulgaris 4
carbon: nutrient ratio 20
Carcinus maenas 121, 134
cascade effect 130–1
Castanea dentata 77
cell lysis 148
cercariae 63, 119
Cerithidia californica 131
Chaetodon multicinctus 131
cheats 146–47, 152
Cheilospirura gruweli 35
chemotherapeutic drugs 96–7
resistance 97
chewing lice 48
classic virulence 145
climate change 118–20
Clinostomum marginatum 58
Clostridium botulinium 166
co-feeding transmission 6
colicins 148
collective action 144–5
colonization 48
Columba livia 52
comfort zone 159
community 22–3, 78
compound community 23
critical community size 78
ecology 23–5
infracommunity 22–53
organization 23–5
competition 51–3, 92–3, 125–30, 173
apparent 173–4
interspecific 93
intraspecific 92
competitive exclusion principle 149
composition–disease
hypothesis 41
compound community 23
consumer–resource interactions 173
consumers 14
conversion genes 148
Coregonus lavaretus 116
corolla shape and parasitism 152
Corophium sp. 127
Corophium volutator 135
corticosterone 49
Crepidostomum sp. 65
critical community size 78
cross-fertilization 93
cross-infection 93
cross-resistance 93
Cryphonetria parasitica 77
Culex pipiens fatigans 130
Cyathocephalus truncatus 119
Cynomolgus macaques 167
Darwinian demons 136
death rate 69, 75, 83, 136
decomposers 14
definitive-host density
hypothesis 35
218
INDEX
deforestation 114–15
density 115
compensation 41
dependence 43–7
desiderata 153
Dicrocoelium dendriticum 146
Dicrocoelium sp. 35
digena 71, 87, 118, 146
direct fitness 144
Discocotyle sagittata 92
disease transmission 82
dispersal 73–4, 132
and population structure 132–3
distribution 44, 70
Ditylenchus dipsaci 86
diversity loss 42
diversity–disease hypothesis 7, 41
domestication 50, 148
Drosophila melanogaster 81
Drosophila sp. 127, 129
drug addiction and parasitism 163
dualism 1
Echinococcus multilocularis 72, 91, 110
echinostome 92
ecological niche 149
ecosystems 14–5, 155, 174–6
achievements and frontiers 15–16
arctic 91
components 14
cybernetic nature 14
deep sea 87
definitions 14
deserts 87–92
ecology 13
engineering 133–5
extremely varying 91–2
stability 130–1
ectoparasites 71
ectotherms 120
effects of parasites 172
cascading effects 172–3
trait-mediated 172
Elton, Charles 55, 57
endemism 31
endogenous infection 162
endoparasites 71
endophytes 151
endothermy 112
energy and nutrient flows 69
energy hypothesis 38
environmental factors 102–103, 106,
113–122, 155
biodiversity loss 114–17
climate change 118–20
external 106
habitat alteration 114
introduced species 120–2
pollution 117–18
pollutogens 122
Ephestia kuehniella 129
epidemics 76–7
equilibrial densities 69
eruption 3
Escherichia coli 148
eutrophication 118
evolution of virulence 143
evolutionary
branching 151
lag 83
stable strategy 144, 150
exogenous infections 162
exploitation trait 145
explosive breeding 90
extinction 106–7
evidences 107–9
parasite–parasite interactions 107
risks of 106
farming and parasites 166
Fasciola hepatica 62, 91, 110–11, 166
fecundity 43–5
Felis catus 52
Fessisentis sp. 64–5
Filenchus polyhypnus 86
fitness 144
fleas 48
flu see avian influenza
flux rates 69
food chains 55
food webs 54–67, 172–3
history 55
and host specificity 61–2
pattern 59
fragmentation 28
fungal pathogens 7, 137
Gallotia gallota 83
game birds 10
Gammarinema gammari 135
Gammarus sp. 127
gastrointestinal nematodes 10
Heterakis gallinarum 10
gene flow 83
generalist pathogen 7
generalists 61–2
paratenic 62
genetic
incompatibility 93
variation 83
geographic information systems
(GIS) 73
germ warfare 125
‘global’ ecosystem 174
global warming and parasites 120
Gonocerca phycidis 87
grouse–nematode interaction 6
growth rate 75
gut parasites 10, 94, 96
Gyrodactylus bullaturdus 46
Gyrodactylus salaris 101
Gyrodactylus sp. 99–101
habitat
alteration 114
heterogeneity 75
restoration see restoration
Haemoproteus 52
Heather moor lands 6
Heligmosomoides polygyrus 46
Hemigrapsus oregonensis 121
Herpesvirus simiae 164
heterotrophic organisms 14
Hirundo pyrrhonota 74
Histoplasma capsulatum 165
HIV 163
horizontal
diversity 17
transfer 50
hormone manipulation 146
hospital ecosystems 161–2
host
gut see gut parasites
manipulation hypothesis 141–9
species abundance 41, 80
specificity see specificity
transmission 70–2, 74, 93, 100,
114–15, 120, 126, 142, 151
host finding, tail 63
hostile environments 86–100, 104, 106
competition 92
control by parasite 104–6
by hosts 94–102
man-made 96–7, 156–7
outcome 106
by parasites 92–4
hostility 104
host–parasite coevolution 74,
80–1, 108
host–parasite interactions 3–5, 13, 28,
33, 35, 42, 44–5, 49, 68–9, 70, 73–6,
79, 80–3, 93, 97, 102, 104–5, 109,
111, 136, 141–9, 153
environmental influence 102–3
spatial interactions 76
INDEX
host–parasitoid–hyperparasitoid
interaction 79
host–pathogen interactions 69,
136–7
hotspots 81–2
Howardula aoronymphium 127
human contacts 157–9
‘human made’ ecosystem 96–7,
156–7
humidity 120
Hutchinson, G.E. 176
hygiene and parasitism 165
Hymenolepis diminuta 94, 127
Hypoderma tarandi 45
hypotheses in ecology 38, 41, 69
composition–disease
hypothesis 41
definitive-host density
hypothesis 35
diversity–disease
hypothesis 41
energy hypothesis 38
host manipulations hypothesis
141–9
insurance hypothesis 69
Janzen–Connell hypothesis 69
Marilyn Scott hypothesis 46
immune response 97–102
immunocompromise 163
industrialization 155, 159–61
infection
and immunity 98
physiology 142
influenza see avian influenza
infracommunity 22–3, 32–5
within-individual 22
infrapopulations 22–3, 93, 95,
98, 110
interaction and parasitism 125
intermediate hosts 118
interspecific cross-fertilization see
cross-fertilization 93
intraspecific competition
51–2, 92
introduced species 47–50,
120–2
invasion
criteria 126
and escape 174
function 150
isolation 28–31
endemism 31
isopods 65
IUDs and diseases 165
Ixodes scapularis 8
and parasitism 9
Ixodes uriae 73
Janzen–Connell
hypothesis 69
recruitment curve 137–8
journals (ecological) 12–13, 171
Ecohealth 12
Ecosystems 13
keystone species 57
kin selection model 143–4
Lagopus lagopus scoticus 45
larva migrans 63
latitudinal gradient 35
Legionnaires’ disease 159–61
Leishmania sp. 105
Leptopilina boulardi 129
life history traits, hosts 131–3
linking parasites 39–42
Listeria monocytes 165
Listeriosis 165
Littorina sp. 71
local–regional richness 31, 34
regression plots 31–2
Lotka–Volterra predation model
76–7, 126
louping-ill 5–7, 11
lung-dwelling parasites 105
Lyme disease 8, 123
macro-consumers 14
macroinvertebrates 64–5
macroparasites 42, 44, 72, 105, 141
mafia behaviour 148
maladaptation 82–3
malaria 120, 130
transmission 114, 120, 167
manipulation 141, 144, 148
adaptations 146
manipulators 141–9
man-made ecosystem 96–7,
156–7
marine ecosystem 167
Marshallagia marshalli 91
meningitis 143
metacommunities 24, 175
metapopulation 80 see also
SI model
micro-consumers 14
microparasites 42, 72, 122, 141
Microphallus papillorobustus
127–8, 154
219
Microtus rossiaemeridionalis 72, 91
mobile genetic elements (MGEs)
148
monogenea 88, 96–100
Monte Carlo simulations 37
morbillivirus 3, 117, 138
multiple resistance 97
mutualism 64, 82, 152–3
as negative virulence 152–4
and parasitism 153
Mycobacterium tuberculosis 165
mycorrhizal fungi 15, 19, 138
natural enemy 33, 126–7
negative virulence 152–4
Neisseria meningitidis 143, 157
nematodes 86, 91, 96, 108, 110, 116,
120, 133, 135, 136, 138
Filenchus polyhypnus 86
Gammarinema gammari 135
gastrointestinal 10, 94, 133
Marshallagia marshalli 91
Parelophostrongulus tenuis 129
Pseudocapillaroides xenopodis 96
Strongyloides ratti 103
Teladorsagia circumcincta 91
Trichostrongyle 86, 87, 111
Nematodirus battus 86
nemerteans 116
nestedness 27, 37–38, 40–1
temperature calculator 37–8
Nitzchia sturionis 130
nosocomial infections 161–3
Notoacmae helmsi 134
Odacoileus virginiatus 129
oil pollution 118
oncomiracidia 89–90
Ophryocystis elektroscirrha 81
optimal control theory 143
optimization 104
Oryctolagus cuniculus 52, 130
oscillation 46
P* rule 126
paradox of enrichment 78
Paralithodes camtschatica 116
parapox virus see squirrel
invasion 10
parasite–host specificity
see specificity
parasite-induced mortality 52
parasite mediated competition
9–11, 51
parasite–parasite interactions 107
220
INDEX
parasites 1–2, 4, 10–1, 23, 25–6, 31,
37, 40, 42, 44–5, 50, 55, 60, 62, 64,
70, 72, 76, 92, 94, 96, 116–17,
119, 121, 125, 133, 135, 138,
140–1, 143, 146, 155–6, 157, 160,
171–2, 174
aggregation see aggregation
arbitration 153
burden 46, 99, 104, 109
caecal 4
and chemotherapeutic drugs 96
community organization 23–5, 39
competition 92
conservation 135–9
definition 156, 158
development 45
distribution see distribution
diversity 135–9
and ecosystem engineering 133–5
effects on communities 172–4
and environmental factors 155
and epidemics see epidemics
fecundity 43–5
and fishing practices 116–17
gastrointestinal 10, 94, 96
horizontal transfer 50
hormone 146
in food webs 55–60
interaction 125
introduced species 121
invasions and escape 174
local–regional riches 31–4
macroparasite 42
manipulation of host phenotype
141–7
microparasite 42, 72, 122, 141
mycorrhizae 138
nestedness 40–1
patterns of distribution 70–4
and pollution 117
position in the food webs 59–60
prostheses and 162, 165
recruitment 40
replication rate 143
role in ecosystems 11–12
specialists and generalists 61–2
species richness 26–36
species–area relationship 26–8
surgery and 164–5
survival 44–5
tampons and 165
temperature influence 119
and touristic travels 157–9
toxins and 117
transmission see host transmission
understanding of 171–2
and wastewater disposal 160
word origin 140
parasitic arbitration 125
parasitic worms 4
parasiticides 96
parasitism 1, 7, 50, 68, 76, 82, 88, 102,
111–13, 120, 125–30, 135, 152–3,
163–6
abundance–area relationships 50–1
biodiversity see biodiversity
breeding 88–90
competition 125–30
corolla shape 152
diseases in women 165
drug addiction 163
dualities 1, 7
ecosystem implications 68–70
endothermy 112
environment provision 111
environmental disturbances 113
environmental influence 102–3, 113
farming and 166
global warming 120
HIV 163
hygiene and 165
immunocompromise 163
interaction 125
mutualism 82, 153
predation and 51–3, 97, 173
role of hygiene 165
shared parasitism 76
in surgical progress 164–5
Parelophostrngulus tenuis 129
parthenogenesis 103
Partula turgida 9
Passer domesticus 50
patch location 86
pathogen 156–8
Pentastomida 104–5
lung-dwelling 105
Perca fluviatilis 45
Perkinsus marinus 120
pheasants and partridges 10–11
Phoca vitulina 79
Phyllodistomum sp. 65
piggyback argument 58
plant biomass see biomass
herbivore 20
Plasmodium spp. 48, 72
Plasmodium vivax 157–8
Platyhelminthes 90
plerocercoids 146
Plodia interpunctella 129
Podocotyloides stenometra 131
Poecilia reticulata 46, 99
polio 165
pollution and parasitism 117
pollutogens 122
polystomatid monogeneans 97–9
Polystomatidae 108–9
population regulation see regulation
anthelmintic treatment 46
competition and predation 51–3
death rate 75
enviromental factors 88
equilibrial density 69
growth rate 75
introduction see introduced species
limitation 68–9
Marilyn Scott hypothesis 46
oscillations see oscillation
saturation 90
T-cell response 48, 51
Porrocaecum vulgaris 45
precipitation 119–20
predation and parasitism 51–3,
97, 173
predator–prey model 76
producers 14
progress infectious diseases 155
proportional sampling 32
prostheses and parasites 162, 165
Protopolystoma sp. 93–5
Pseudocapillaroides xenopodis 96, 98
Pseudodiplorchis americanus 88–90, 93,
98, 106, 108–10
quorum sensing 143
Raffaelli’s pyramid 67
Raillietina tetragona 35
Rangifer tarandus 45
red grouse 4
regulation 44–8, 51, 68–9, 75,
88, 90
replication rate 143
reproductive number 137
resistance 97
restoration 116
Ribeiroia ondatrae 118
rinderpest 3, 138–9
Rissa tridactyla 73
Sacculina carcini 134
Salmo salar 100
Salmonella sp. 164, 166
salmonellosis 166
sanitation 160
saprobes or saprophytes 14
Sardinops sagax 76
SARS 167
Scaphiopus couchii 88–90
INDEX
Scaphiopus recruitment 106
Schistosoma spp. 93, 110
schistosomiasis 107, 114
Sciurus carolinensis 52
Sclerotina minor 76
selection pressure 97
septicaemia 162
Serengeti 3, 4, 6, 9, 11, 121, 138–9
shared parasites 173
SI
dynamics 69
model 69, 74, 76, 80
sick building syndrome 160
sickness 161–3
small-world network 158–9
soil nutrient concentration 20
space and parasitism see spatial
dynamics
spatial
aggregation 72
dynamics 70, 77–83
heterogeneity 76
variability 70
specialist and generalist parasite
2, 7, 61–2
species–area relationship 26–8
species coexistence 23–5, 33,
126, 131–3
species richness 35, 41–2
host species abundance 41
latitudinal gradient 35
local–regional richness 31–4
relationship with isolation 28
species–area relationship 26–8
species richness–isolation
relationship 28
specificity 61–4
Spiroxys japonica 45
Sporidesmium sclerotivorum 76
squirrel invasion 10
Staphylococcus sp. 165
stochasticity 79
stress and disease 114
Strongyloides ratti 103
Sturnus vulgaris 45, 50
Subulura suctoria 35
suprapopulation 23
surgery and parasites 164–5
survival 43–5
Sylvilagus floridanus 52
sympatry 80, 93, 107
T-cell response 48, 51
tail in host finding 63
Tamias striatus 52
tampons and parasites 165
Teladorsagia circumcincta 91
temperature and parasitism 119
temporal segregation 131–2
Testudo graeca 62
tick borne virus 5
ticks 6
tinned food 165–6
Toft, Cathy 136
top-down control 19, 21, 24–5
toxins and parasites 117
tragedy of the commons 144–5
transformation 141
transmissibility 150
transmission
habitat alteration and 114
per capita rates 74
modes 149
rates 126
vertical and horizontal 157
see also host transmission
trematodes 63, 114–15, 118–20, 128,
131, 133–4
Curtuteria australis 134
Podocotyloides stenometra 131
Triaenophorus crassus 116
Triaenophorus nodulosus 45
221
Tribolium sp. 127
Trichinella nativa 86, 91
Trichinella spiralis 105
Trichobilharzia ocellata 118
Trichostrongylus tenius 3, 46
tritrophic interaction 79
Trollius europaeus 152
tropical ecosystems 71
two-species interactions 93, 107
type I and II communities 33
typhoid 160, 166
Tyto alba 52
ungulates 3, 121, 129, 138
urban encephalitis 164
vaccination 12, 109, 138, 145
valley fever 122
vector borne diseases 9, 119, 158
between-species transmission 10
Venturia canescens 129
virulence 70
viruses 168–70
weapons of competition 125
Wetanema sp. 86
wildebeest 4
within-group fitness 144
within-host infection 22, 25
emergent properties 25
within-season transmission 88
within-species transmission 126
Xenopus laevis 98
Xenopus sp. 93–4
xenotransplantation 164
xenozoonosis 164
Yucca–Yucca moth interaction 152
zoonoses 72, 164