Forage fish c0 nsum ption by m arine m am m als and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
33
CHAPTER 3
FORAGE FISH CONSUMPTION BY MARINE MAMMALS AND SEABIRDS3
Kristin Kaschner, Vasiliki Karpouzi, Reg Watson, and Daniel Pauly
Fisheries Centre, Aquatic Ecosy stem s Research Laboratory (AERL), University of British Colum bia.
220 2 Main Mall, Vancouver, BC., V6T 1Z4, Canada
k.kaschner@fisheries.ubc.ca; v.karpouzi@fisheries.ubc.ca; r.w atson@fisheries.ubc.ca;
d.pauly @fisheries.ubc.ca
ABSTRACT
This contribution presents estimates of the amounts and distributions of small pelagic fishes (i.e., ‘forage
fish’) consumed by the 115 species of marine mammals and the 351 species of seabirds known to feed in
the world’s marine waters. The methods used for mapping the distribution of these predators and of their
prey, detailed elsewhere, are briefly recalled. Marine mammals, in the 1990s, annually consumed about
20.2 million t of small pelagics, or roughly 12 % of their food consumption; for seabirds, the corresponding
figures, also applying to the 1990s, are 12.1 million t of small pelagics and 12.5 % of their food
consumption. Overall, we find that marine mammals and seabirds do not compromise human
exploitation of small pelagics. On the other hand, reduced biomasses of small pelagics are a challenge for
numerous species of marine mammals and seabirds.
INTRODUCTION
The marine mammals of the world, belonging to 115 species, jointly consume a large amount of food, about
four times as much as humans catch (above 100 million t if illegal and misreported catches are included),
while the 351 species of seabirds consume about as much as we catch (Kaschner and Pauly, 2005; Brooke,
2004; Karpouzi, 2005).
This study is devoted to investigating how much of this consumption (which, due to the nature of our data,
represents an average year of the 1990s) consist(ed) of small pelagic fishes (i.e. ‘forage fish’), and thus to
what extent humans may compete with marine mammals and seabirds for small pelagic fishes.
METHODS
Marine m am m als
Our model encompassed 115 species of marine mammals that live predominantly in the marine
environment (Kaschner, 2004), but did not include sirenians, sea otters, the polar bear nor any of the
exclusively freshwater cetacean or pinniped species. We used a relatively simple generic model (Trites et
al., 1997) to generate estimates of forage fish consumption of marine mammal species:
(1)
Q i = 365 *
∑N
i,s Wi,s R i,s
s
where the annual food consumption Q of forage fish of species i was estimated from the pelagic prey
consumed daily by each individual of species i and sex s is calculated based on the number of individuals N
of the sex s of a species i, and a weight- and sex-specific daily ration R.
Cite as: Kaschner, K., Karpouzi, V., Watson, R., Pauly, D. 2006. Forage fish consumption by marine mammals and seabirds, p. 3346. In: Alder, J., Pauly, D., (eds). On the multiple uses of forage fish: from ecosystems to markets. Fisheries Centre Research Reports
14(3). Fisheries Centre, University of British Columbia [ISSN 1198-6727].
3
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
34
We obtained global abundance of marine mammal species during the 1990s by extracting and combining
available regional abundance estimates and information about associated uncertainties from more than
1,000 published primary (e.g., Branch and Butterworth, 2001, Whitehead, 2002, Mullin and Fulling,
2003) and secondary sources (e.g., Reijnders et al., 1993, Ridgeway and Harrison, 1999, Perrin et al.,
2002) Mean abundance estimates that were used in this study are available in Appendix 3 (Kaschner,
2004). We assumed sex ratios were balanced for most species, except for those for which available
published information explicitly indicated otherwise (e.g., Wickens and York, 1997) or if unequal sex ratios
seemed highly likely based on information about closely-related species with similar life history traits. We
used the sex-specific mean body mass estimates for each species generated by Trites and Pauly (1998),
who estimated female and male body weights averaged across all age classes for marine mammal species,
based on the strong relationship between more readily-available maximum length information and
species-specific growth rates, survival and longevity.
We calculated daily food ration of small pelagic fish consumed by each species based on the weightspecific energy requirements and information about diet composition. Food intake of specific species was
calculated using an empirical model developed by Innes et al. (1987) and later modified by Trites et al.
(1997):
(2)
R i,s = 0.1 * Wi0.s.8 * pSPi,s
where R is the daily food intake of forage fish of an individual of sex s belonging to species i, W is the
mean body weight of that individual in kilograms, and pSP is the proportion of small pelagic fishes in the
species diet as determined by Pauly et al. (1998). Annual spatially-explicit food-consumption densities
were generated by linking food intake to global distributions of species predicted using a large-scale
Relative Environmental Suitability (RES) model (Kaschner et al., 2006). Within a global grid of 0.5 degree
latitude x 0.5 degree longitude cells, we then compared predicted marine mammal food-consumption
densities with average fisheries catch densities during the 1990s as generated by the Sea Around Us
Project (Watson et al., 2004) using a modified version of an ecological niche overlap index. This index is
derived from or related to the ‘competition coefficients’ of the Lotka-Volterra equations by Morisita (1959;
see also Horn, 1966) and originally only considered the qualitative overlap of resource utilization of two
players exploiting the same resources (i.e., the similarity of marine mammal diet and fisheries catch
composition), but ignored the absolute amounts of the resource that is being used or consumed. We
therefore further modified this index by introducing a weighting factor to provide a measure of the
importance of each cell for either fisheries or marine mammals based on overall quantity of catch or food
taken by either consumer in this cell, leading to:
(3)
' j,l
(
(
& 2
p l,k p j,k
$
$
k
=
$
p l,2k + p 2j,k
$
% k
#
!
! * pQ * pC
l
j
!
!
"
(
)
where αj,l describes the quantitative overlap between a fishery j and marine mammals l in each cell, and
the first term expresses the qualitative similarity in diet/catch composition between marine mammals and
fisheries sharing the resource or food type k (in this case: small pelagics) as the ratio of ‘niche proximity’ to
‘niche breadth’ (MacArthur and Levins, 1967), with pl,k and pj,k representing the proportions of forage fish
in the diet or catch. This term is multiplied by the product of the proportion of global food consumption of
small pelagic prey taken by marine mammals (Q) and the total fisheries (C) within this cell. The
continuous resource overlap values thus generated were subsequently sub-divided to create a categorical
index ranging from low to high.
Seabirds
We compiled information for 351 marine bird species (belonging to four orders and 14 families) in a
Microsoft Access database. Of these species, 334 are traditionally considered to be seabirds. The
remaining 17 were species of sea ducks, which consist of birds that breed inland but which winter at sea
close to shore, and prey upon small fish and invertebrates that occur along the coast. Information was
gathered using the following databases: (a) Aquatic Sciences and Fisheries Abstracts (ASFA); (b) Web of
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
35
Science, Institute for Scientific Information (ISI); and (c) BioSciences Information Service (BIOSIS) of
Biological Abstracts. These cover peer-reviewed journals and grey literature sources. The following online
databases were also consulted: (a) Avibase – the world bird database (Anon 2006); (b) The World
Conservation Monitoring Centre Species Database (WCMC, 2006); (c) BirdLife International
(www.birdlife.net); (d) the National Audubon Society (www.audubon.org) Christmas Bird Count
(http://www.audubon.org/bird/cbc/index.html); (e) the Birds of North America Online
(http://bna.birds.cornell.edu/BNA/); and (f) Wetlands International (www.wetlands.org).
Information required to estimate the seabirds’ daily food intake (DFI), and hence their annual food
consumption, included: (a) body mass (m; in g) of seabird species taken from Dunning (1993) and
Schreiber and Burger (2002); (b) Basal and Field Metabolic Rates [BMR and FMR respectively, estimated
using order-specific allometric equations from Ellis & Gabrielsen (2002); in kJ/day]. BMR and FMR were
used to estimate energy requirements (ER) of seabirds in the non-breeding and breeding season
respectively; (c) A matrix of standardized diet composition and; (d) population sizes of breeding seabirds.
Daily food intake (DFI) was estimated using a bioenergetic model created by the ICES Working Group on
Seabird Ecology (ICES, 2000):
(4)
DFI i =
ER i
G
! DC
ij
* ED j
*
1
AE i
j=1
where DFIi denotes daily food intake for each seabird species i, ERi is the energy requirements for each i,
DCij is the fraction of food item j in the diet of each i, and EDj is the mean energy density of each prey j. EDj
values were available either at the species or the genus level for prey items. AEi is the mean food
assimilation efficiency for each i, and G the total number of food groups encountered in the diet of each i.
AEi was assumed equal to 75% (Gabrielsen, 1994; ICES, 2000; Barrett et al., 2002), unless species-specific
information was found in the literature (see Karpouzi, 2005).
In order to estimate seabird species’ annual food consumption, DFIi was estimated separately for the
breeding and non-breeding season, by considering ERi for the breeding season equal to FMR (ICES,
2000), and for the non-breeding season equal to 2.5 · BMR (ICES,2000). The length of the breeding
season was assumed equal to incubation period + time from hatching to leaving the nest or burrow + 20
days (Cramp 1985).
Consumption by seabirds was specified using 25 food groups. Six out of 25 food groups represented the
forage fish groups considered here (i.e., Capelin, Mallotus villosus; Exocoetidae; Engraulidae; Clupeidae;
Osmeridae; Sandlance, Ammodytes spp.). Food groups were compiled based on the taxonomic groups
represented in the Sea Around Us Project database. In order to map total food consumption by seabirds,
we used a GIS-based modeling approach and the same spatial grid of 30-min cells developed by the Sea
Around Us Project (Watson et al., 2004; www.seaaroundus.org). Total food consumption by seabirds was
estimated per spatial cell, based on the seabird density of each cell (see details in Karpouzi, 2005).
RESULTS
Spatially explicit consumption of forage fish by marine mammals
We estimated that food intake of forage fish by all marine mammal species combined was about twothirds of the amount of small pelagics taken by fisheries in the 1990s (Figure 1). While small pelagics
represent the single most important prey type targeted by fisheries, contributing over 50 % of the total
catch, this food type makes up – at the most – 20% of the diet of any marine mammal species group.
Baleen whales and pinnipeds consume the bulk of small pelagics consumed by marine mammals, although
which of the two species groups takes the majority of this prey type may vary depending on the type of
feeding rate model used to estimate food intake. Toothed whales, in contrast, are much less dependent on
forage fish, and this prey type makes up less than 10% of the total amount consumed by both small and
large odontocetes (Figure 2).
36
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
Spatial disaggregation of fisheries catches in the 1990s showed that the vast majority of reported catches
was taken on the continental shelves of Europe, North America, Southeast Asia and the west coast of
South America (Figure 3). Fisheries were concentrated in relatively small areas and fishing rates can be
extremely high, amounting to more than 1,000 t per km2 per year in some of the dark red areas shown in
Figure 3. Highest catches occurred in areas where continental shelves are wide, such as the East China or
North Seas, or in productive upwelling systems, such as those that can be found along the west coasts of
South America and South Africa. However, despite the many distant water fleets and the development of
deep-sea fisheries operating far offshore, major fishing grounds generally lay in close proximity to areas
with high human populations along the coasts of major industrial fishing nations.
We predicted most of the forage fish that marine mammals consume to be taken in polar waters, with
particularly high concentrations along the continental shelves in the North Atlantic (Figure 4). Due to the
sheer size of the distributional ranges of many of the baleen and larger toothed whale species,
consumption densities (annual food intake per km2) are comparatively low and homogenous across large
areas (Figure 4). Areas of highest forage fish consumption are closely linked with pinniped occurrence,
since the generally more restricted, coastal ranges of this species group – combined with high abundances
and a preference for small pelagic prey types – resulted in locally concentrated feeding densities. However,
predicted maximum food consumption densities did not exceed 0.75 t per km2 per year anywhere in the
world, i.e., maximum food intake of small pelagic prey by marine mammals is several orders of magnitude
lower than the highest fisheries catch rates.
Overall, the model predicted low overlap in resource exploitation between all marine mammals and
fisheries in the 1990s (Figure 5). High overlap appeared to be restricted to small geographical regions and
was mostly concentrated in temperate continental shelf areas of the northern hemisphere and the highly
productive upwelling systems in the southern hemisphere. Highest overlap was predicted in areas where
high fishing effort coincided with high densities of seals such as the North Atlantic shelves (harp, hooded,
harbour and grey seals) or the Benguela system (South African fur seals) or along the coast of western
South America where productive upwelling systems support a wide range of marine mammal species and
fisheries. Although only a few pinniped species occur in the waters around Japan, high overlap in this
region can be attributed to the large number of dolphins and some baleen whale species feeding on small
pelagics, combined with very high fishing rates in these waters.
Figure 1. Mean estimated annual consumption of small pelagics by marine mammals in comparison to fisheries
catches in the 1990s.
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
37
Figure 2. Mean estimated annual proportion of small pelagics in the diet of marine mammals and in fisheries catches
during the 1990s.
Figure 3. Distribution of fisheries catches of small pelagics for an average year in the 1990s. Note open-ended scale of
legend, which indicates that fisheries catch rates can reach up to 150 000 t·km-2·year-1 in some areas.
38
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
Figure 4. Distribution of estimated marine mammal food consumption rates (t·km-2·year-1) of small pelagics for an
average year in the 1990s.
Figure 5: Map of estimated overlap in resource exploitation of small pelagics by marine mammals and fisheries for an
average year in the 1990s.
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
39
Spatially explicit consumption of forage fish by seabirds
We estimated that food intake of forage fish by all seabird species combined was at least eight times lower
than what is taken by fisheries in the 1990s (Table 1). Small pelagics comprised about 12.5% of the overall
food consumed annually by the world’s seabirds. Alcids (puffins and murres) and larids (gulls) are
responsible for about 75% of small pelagic fish consumption by all seabird species combined.
Table 1. Small pelagic fish (in t) taken annually by seabirds from different FAO statistical areas.
FAO
Area
18
21
27
31
34
37
41
47
48
51
57
58
61
67
71
77
81
87
88
Total
Capelin
31,289
207,258
2,556,958
3,457
5,854
111,008
2,915,824
Exocoetidae
Engraulidae
Clupeidae
Osmeridae
Ammodytes
1
13,828
4,569
410,265
2,310,191
40,054
56,489
2,835,396
144
42
5,282
2,241
234
20,888
7,018
15,322
11,288
43,726
12,044
26,193
174,629
809,532
249,765
1,378,348
1,716
22,722
657,668
2,439
812
24,843
17
5,927
4,431
650
34,554
48,321
3,252
27,784
207,668
13,059
1,055,864
86
22
31
2,278
28,785
31,202
62,621
119,055
3,071,392
5,809
172,607
405,430
2,337
7,328
174
3,846,752
All
95,625
349,265
6,286,082
17,018
3,053
25,077
20,905
12,946
33,582
16,506
259,019
605,588
442,048
2,519,931
1,057,427
319,312
12,063,385
We predicted that more than 52% of the forage fish that seabirds consume is extracted over the
continental shelves of the Northeast Atlantic Ocean (Figure 6; Table 1). In this area, sandlance and capelin
accounted for >54% of the food taken annually by seabirds. The Eastern Central Pacific Ocean (Figure 6;
Table 1) was the second most important area, where small pelagics taken by seabirds comprised 21% of the
overall forage fish consumption. In this area, forage fish groups in the diet of seabirds were dominated (up
to 92%) by fish species of the family Exocoetidae. Areas of highest forage fish consumption were closely
linked with the distribution of those seabird species that are limited to waters above continental shelves
when foraging (Karpouzi, 2005).
Furthermore, predicted maximum food consumption rates exceeded 10 t · kmֿ2 · yearֿ¹ along the
continental shelves of the Northeast Atlantic Ocean and around islands of the Western Central Pacific
Ocean. This figure is more than ten times larger than what marine mammals were predicted to consume.
However, it still remains several orders of magnitude lower than the highest fisheries catch rates.
40
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
Figure 6. Map of predicted global small pelagic fish consumption rate by all seabirds combined for an average year in
the 1990s.
DISCUSSION
Spatially explicit food consumption and overlap with fisheries
Based on the small size of predicted ‘hotspots’ of potential conflict, in combination with highly
concentrated fishing operations and the mobility of many species of marine mammal and seabirds, we
suggest that it is unlikely for direct competition to represent a severe threat to species with large foraging
ranges. In contrast, our findings support a previously proposed hypothesis that the most common type of
harmful competitive interaction will be one in which fisheries adversely impact species with restricted
distributional ranges (DeMaster et al., 2001; Frederiksen et al., 2004), indicating that local depletions of
food resources through intensive fisheries may pose serious threats to species such as the Vaquita in the
Gulf of California, South Africa’s Heaviside’s dolphins, the North Sea populations of Black-legged
kittiwakes, and also to localized populations of other species.
Quantitative validation of our resource overlap analysis will be difficult to achieve. However, even though
resource overlap does not automatically imply competition and vice versa, it is reassuring that the
‘hotspots’ of potential conflict highlighted by our approach coincide with many areas that have been the
focal points of much previous debate about marine mammal-fisheries and seabird-fisheries interactions.
This indicates that the models capture at least some important aspects of the processes that drive these
interactions. Prominent hotspots for marine mammals in Figure 5 include the east coast of North America,
where the largest annual cull worldwide is – in part – being justified based on the perception that the
growing harp seal population impedes the recovery of the northwest Atlantic cod stocks (e.g., Yodzis,
2001). In addition, the model identifies areas of potential conflict in the Benguela system off southwest
Africa, where the potential impacts of the increasing population of South African fur seals on the hake
stocks has been an issue of much debate (Wickens et al., 1992, Punt and Butterworth, 1995), or in the
waters surrounding Japan where the perception of marine mammals as competitors appears to be
particularly prevalent (Anon., 2001b, a). Furthermore for seabirds, the model identified several areas of
potential conflict, for instance in the Norwegian and Barents Seas, where rapid decline in the numbers of
Common murres has been attributed to the development of industrial fisheries, which target mainly
Sandeel for industrial raw materials, fish oil and fishmeal (Anker-Nilssen et al., 1997). Looking at our
maps, the skewed perception of this issue by nations in close vicinity to these hotspots of interaction
becomes an understandable, if somewhat myopic, viewpoint when extrapolated to the global scale.
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
41
On the other hand, there is a growing literature on marine mammals and seabirds being starved by
depletion of small pelagics by fishing. We shall not pursue this theme here, except for mentioning the
Mediterranean, where the fattening of Bluefin tuna (Thunnus thynnus) has generated a huge demand for
small pelagics. It has been proposed that this demand, which is added to that of the seafood markets of
Mediterranean countries, has led to a radical depletion of the stocks of small pelagics in certain areas (e.g.
the Ionian Sea) and, therefore, to a depletion of previously abundant Common dolphins (Delphinus
delphi) (CIESM 2004; Bearzi et al., 2004,2005).
BIASES AND LIMITATIONS OF FOOD CONSUMPTION MODELS
All input parameters of the basic food consumption models are affected by a number of conceptual and/or
methodological biases.
Abundance
Estimating abundance of any marine mammal and seabird species is challenging due to the vast
distributional ranges of most species and, for marine mammals, the fact that they spend the majority of
their time underwater (Buckland et al., 1993). Moreover, dedicated surveys are labour- and cost-intensive,
are generally conducted at irregular intervals and cover only a small proportion of a species’ total range. A
lack of standard surveying techniques and coverages, and seasonal and inter-annual variation in species
occurrence patterns, hamper direct comparison and summation of available regional areas. For all of these
reasons, the global estimates used here should be regarded with caution. Nevertheless, we arrive at
abundance estimates that are largely comparable to those previously used in similar studies assessing food
consumption of marine mammals and seabirds on very large scales (Trites et al., 1997; Young, 2000;
Tamura, 2003; Brooke, 2004).
Feeding rates
The selection of feeding rates used in any food consumption model strongly affects estimates of total
consumption. Feeding rates have been estimated based on a variety of different methods ranging from
direct measurements of food intake or maximum stomach contents (Innes et al., 1987) to bioenergtic
models (Lockyer, 1981b, a; Nagy et al., 1999; Winship et al., 2002). All models are based on certain
assumptions about physiological parameters and the feeding requirements of a specific individual (e.g.,
Klumov, 1963; Innes et al., 1986) or standard metabolic rates of species (Lilliendahl and Solmundsson,
1997; Sigurjónsson and Víkingsson, 1997). Models are thus associated with high uncertainties, particularly
for baleen whales owing, e.g., to the difficulties associated with studying metabolic rates of large animals
and the non-linear relationship between body mass and consumption (Leaper and Lavigne, 2002).
In the case of marine mammals, our model ignored seasonal difference in food intake. The annual life
cycle of many marine mammal species includes extensive fasting periods, often coinciding with
reproductive activities (Brown and Lockyer, 1984). Some of the methods used to estimate daily rations
implicitly account for the seasonal differences in food intake through the adjustment of the feeding rate
exponent, but the effects of such feeding patterns are mostly ignored in these simple models.
Unfortunately, evaluating the impact of the lack of seasonal feeding patterns on our estimates is difficult
as direct comparisons with other studies that have considered such seasonal variation (Kenney et al., 1997;
Shelton et al., 1997; Sigurjónsson and Víkingsson, 1997; Boyd, 2002) are hampered by the differences in
modeling approaches and parameterization.
In the case of seabirds, energy requirements also fluctuate seasonally, because the energetic costs of
various stages in the life cycle of mature seabirds differ (see e.g., Ellis and Gabrielsen, 2002). This is why
energy demands of seabird species were estimated here using BMR and FMR for the breeding and the
non-breeding season respectively. However, BMR and FMR values were estimated using order-specific
allometric equations, which may generate bias in the predictions of the model.
Diet composition
The composition of the diet is affected by various uncertainties, including the difficulties associated with
obtaining diet information from sufficient sample sizes in the wild (Duffy and Jackson, 1986; Barros and
Clarke, 2002). Diet composition estimates based on stomach content or scat analyses tend to be biased
with respect to cephalopods, as their hard parts are less readily digested than those of other prey groups
42
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
and accumulate in the stomach (Furness et al., 1984; Zeppelin et al., 2004). Such biases may, however, be
addressed by applying correction factors that compensate for differential effects of digestion on different
prey types (Tollit et al., 1997, 2003). More serious biases are introduced, for marine mammals, by the
predominance of stranded animals in the overall sample. Such animals may not be representative of the
rest of the population, as they are often sick and/or their stomach contents over-represent the coastal
components of their diet (Barros and Clarke, 2002).
Overall, stomach and scat samples only represent brief snapshots of what is often a highly variable,
geographically and inter- and intra-annually changing diet spectrum of a given species (Haug et al., 1995;
Nilssen, 1995; Velando and Freire, 1999; Tamura 2001). More recently developed molecular methods,
including stable isotope (Hobson et al., 1994; Best and Schell, 1996; Hooker et al., 2001; Das et al., 2003)
and fatty acid (Iverson 1993, Hooker et al., 2001; Lea et al., 2002; Grahl-Nielsen et al., 2003) analyses
allow the investigation of diets over longer time periods, but results are often difficult to interpret and
come with their own set of uncertainties (Smith et al., 1997).
Spatially explicit food consumption model
There are a number of discrepancies between the species distributions that underlie our food consumption
maps and the currently-documented occurrence of the species. This is not surprising given the broad
approach we took.
By their nature, predictions are often closer to likely historical distributions of species than their currently
utilized range extent (Kaschner, 2004). The predictions likely overestimate food intake in the lower
latitudes by not considering seasonal differences in species occurrence and associated feeding patterns.
Many marine mammal species undertake extensive annual or semi-annual migrations that cover large
distances between areas used primarily for foraging and reproductive purposes (Stern, 2002; Stevick et
al., 2002). Migrations and feeding patterns have been incorporated into the model for a subset of species
(i.e. the Great whales) in the context of another project (Kaschner et al., 2006) and results indicated that
the consideration of these factors only exaggerated the patterns shown in Figure 5. Nevertheless, there are
on-going efforts to generate seasonal RES predictions for all marine mammal species in the near future
which will be incorporated in future versions of the analysis conducted here.
Similarly to marine mammals, the current lack of consideration of seasonal difference in distributions will
have impacted the seabird results presented here. For instance, some species of the genus Puffinus
(shearwaters) breed in areas of the southern hemisphere. At the end of the breeding season they migrate
to feed and winter in the temperate and polar waters of the North Pacific and the North Atlantic Oceans
(e.g., Spear and Ainley, 1999; Ito, 2002).
Spatially-explicit resource overlap and sensitivity analysis
A multitude of different conceptual approaches have been developed to investigate different aspects of
ecological niche overlap between species and communities (Hanski, 1978; Hurlbert, 1978; Chase and
Leibold, 2003). The index developed by Horn (1966) and Morisita (1959) that formed the basis for our
resource overlap index (Equation 3) has been deemed inappropriate to measure ecological niche overlap
by some (e.g., Hurlbert, 1978). Hurlbert’s (1978) main criticism concerns an implicit assumption of this
approach that the overlap index is partially determined by the niche width outside the overlap zone (i.e.,
the extent of utilization of non-shared resources by either player and the overall availability of the resource
used is not taken into account). However, in the context of investigating marine mammal-fisheries and
seabird-fisheries interactions, we regarded the extent to which either relied on resources not
consumed/targeted by the others as an important factor. The abundance or availability of resources would
be an important consideration that will partially determine the extent of actual competition between two
players (i.e., if the resource is limited and available amounts cannot sustain existing demands of all
present consumers). Given the index used here, our model would, for instance, predict low overlap in
areas where both marine mammals (or seabirds) and fisheries take relatively small amounts. However, if
the abundance of the targeted food type is very low, competition may still conceivably be high in areas of
predicted low resource overlap.
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
43
Efforts are underway to develop models to generate large-scale biomass estimates of fish (Christensen et
al., 2003) that could be incorporated into the analysis in the future. However, for the most part, global
estimates for most prey types are currently unavailable, making the consideration of prey abundance in
overlap equations difficult.
Our analysis of resource overlap was affected by the biases of all input parameters as discussed above. Yet,
the nature of the models and the type of data used make it difficult to attach a quantitative estimate of
uncertainty to our predictions. Nevertheless, a basic sensitivity analysis was conducted by running the
model with global marine mammal food consumption estimates that varied by an order of magnitude.
Results showed that such variation had little to no effect on the spatial extent of areas of predicted high
resource overlap. This indicates that areas of high overlap are largely caused by extremely high catch rates,
due to highly concentrated fishing effort.
REFERENCES
Anker-Nilssen, T., Barrett, R.T., Krasnov, J.V. 1997. Long- and short-term responses of seabirds in the Norwegian and Barents Seas
to changes in stocks of prey fish. p. 683-698. In: Forage fishes in marine ecosystems. Proceeding of the International Symposium
on the Role of Forage Fishes in Marine Ecosystems, Alaska Sea Grant College Program Report 97-01, University of Alaska,
Fairbanks, USA.
Anon. 2001a. Didn't we forget something? Cetaceans and food for humankind. Institute of Cetacean Research, Tokyo, Japan.
Anon. 2001b. What can we do for the coming food crisis in the 21st century? Institute of Cetacean Research, Tokyo, Japan.
Anon. 2006. Avibase – the world bird database [Available at http://www.bsc-eoc.org/avibase/avibase.jsp. Accessed 18 July, 2006].
Barrett, R.T., Anker-Nilssen, T., Gabrielsen, G.W., Chapdelaine, G. 2002. Food consumption by seabirds in Norwegian waters. ICES
Journal of Marine Science 59, 43-47.
Barros, N.B., Clarke, M.R. 2002. Diet. p 323-327. In: Perrin, W.F., Würsig, B., Thewissen, J.G.M. (eds). Encyclopedia of Marine
Mammals. Academic Press.
Bearzi, G., Holcer, D., Notarbartolo di Sciara, G. 2004. The role of historical dolphin takes and habitat degradations in shaping the
present status of Northern Adriatic cetaceans. Aquatic Conservation: Marine and Freshwater Ecosystems 14, 363-379.
Bearzi, G., Politi, E., Agazzi, S., Bruno, S., Costa, M., Bonizzoni, S. 2005. Occurrence and present status of coastal dolphins
(Delphinus delphi and Tursiops truncatus) in the Eastern Ionian Sea. Aquatic Conservation: Marine and freshwater Ecosystems
15, 3, 243-257.
Best, P.B., Schell, D.M. 1996. Stable isotopes in Southern right whale (Eubalaena australis) baleen as indicators of seasonal
movements, feeding and growth. Marine Biology (Berlin) 124, 483-494.
Boyd, I.L .2002. Estimating food consumption of marine predators: Antarctic fur seals and macaroni penguins. Journal of Applied
Ecology 39, 103-119.
Branch, T.A., Butterworth, D.S. 2001. Estimates of abundance south of 60 degree S for cetacean species sighted frequently on the
1978/79 to 1997/98 IWC/IDCR-SOWER sighting surveys. Journal of Cetacean Research and Management 3, 251-270.
Brooke, M de L .2004. The food consumption of the world's seabirds. Biology Letters 271, S246-S248.
Brown, S.G., Lockyer, C, H. 1984. Whales. p. 717-781. In: Laws, R.M. (ed) Antarctic Ecology, Vol 2. Academic Press, London, UK.
Buckland, S.T., Anderson, D.R., Burnham, K.P., Laake, J.L. 1993. Distance sampling: estimating abundance of biological populations.
Chapman and Hall, London, UK.
Chase, J.M., Leibold, M.A. 2003. Ecological niches: linking classical and contemporary approaches. University of Chicago Press,
Chicago, IL.
Christensen, V., Guénette, S., Heymans, J., Walters, C., Watson, R., Zeller, D., Pauly, D. 2003. Hundred-year decline of North
Atlantic predatory fishes. Fish and Fisheries 4, 1-24.
Cramp, S. (ed). 1985. Birds of the Western Palearctic, Vol 1. Oxford University Press, Oxford.
Das, K., Beans, C., Holsbeek, L., Mauger, G., Berrow, S.D., Rogan, E., Bouquegneau, J.M. 2003. Marine mammals from Northeast
Atlantic: relationship between their trophic status as determined by d13C and d15N measurements and their trace metal
concentrations. Marine Environmental Research 56, 349–365.
DeMaster, D.P., Fowle,r C.W., Perry, S.L., Richlin, M.F. 2001. Predation and competition: the impact of fisheries on marine-mammal
populations over the next one hundred years. Journal of Mammalogy 82, 641-651.
Duffy, D.C., Jackson, S. 1986. Diet studies of seabirds: a review of methods. Colonial Waterbirds 9, 1-17.
Dunning, J.B. (ed). 1993. CRC handbook of avian body masses. CRC Press, Boca Raton, FL.
Ellis, H.I., Gabrielsen, G.W. 2002. Energetics of free-ranging seabirds, p. 359-407. In: Schreiber EA, Burger J (eds) Biology of
Marine Birds. CRC Marine Biology Series, CRC Press, Boca Raton, FL.
44
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
Frederiksen, M., Wanless, S., Harris, M.P., Rothery, P., Wilson, L.J. 2004. The role of industrial fisheries and oceanographic change
in the decline of North Sea black-legged kittiwakes. Journal of Applied Ecology 41, 1129-1139.
Furness, B.L., Laugksch, R.C., Duffy, D.C. 1984. Cephalopod beaks and studies of seabird diets. The Auk 101, 619-620.
Gabrielsen, G.W. 1994. Energy expenditure in arctic seabirds. PhD dissertation, University of Tromsø, Norway.
Grahl-Nielsen, O., Andersen, M., Derocher, A.E., Lydersen, C., Wiig, Ø., Kovacs, K.M. 2003. Fatty acid composition of the adipose
tissue of polar bears and of their prey: ringed seals, bearded seals and harp seals. Marine Ecology Progress Series 265, 275–282.
Hanski, I. 1978. Some comments on the measurement of niche metrics. Ecology 59, 168-174.
Haug, T., Gjøsæter, H., Lindstrøm, U., Nilssen, K.T., Røttingen, I. 1995. Spatial and temporal variations in northeast Atlantic minke
whale Balaenoptera acutorostrata feeding habits, p. 225-239. In: Blix A.S., Walløe, L., Ulltang, Ø. (eds). Whales, seals, fish and
man - Proceedings of the International Symposium on the Biology of Marine Mammals in the North East Atlantic, Tromsø,
Norway, 29 November - 1 December 1994, Vol 4. Elsevier, Amsterdam.
Hobson, K.A., Piatt, J.F., Pitocchelli, J. 1994. Using stable isotopes to determine seabird trophic relationships. Journal of Animal
Ecology 63,786-798.
Hooker, S.K., Iverson, S.J., Ostrom, P., Smith, S.C. 2001. Diet of Northern bottlenose whales inferred from fatty acid and stable
isotope analyses of biopsy samples. Canadian Journal of Zoology 79, 1442-1454.
Horn, HS. 1966. Measurements of 'overlap' in comparative ecological studies. American Naturalist 100, 419-424.
Hurlbert, S.H. 1978. The measurement of niche overlap and some relatives. Ecology 59, 67-77
ICES. 2000. Report of the Working
http://www.ices.dk/reports/occ/2000/ .
Group
on
Seabird
Ecology.
ICES
CM
2000/C:04,
available
online
at
Innes, S., Lavigne, D.M., Eagle, W.M., Kovacs, K.M. 1986. Estimating feeding rates of marine mammals from heart mass to body
mass ratios. Marine Mammal Science 2, 227-229.
Innes, S.D., Lavigne, M., Earle, W.M., Kovacs, K.M. 1987. Feeding rates of seals and whales. Journal of Animal Ecology 56, 115-130.
Ito, S. 2002. Foraging areas of short-tailed shearwaters during their northward migration along the Pacific coast of northern Japan.
Ornithological Science 1, 159-162.
Iverson, S.J. 1993. Milk secretion in marine mammals in relation to foraging: can milk fatty acids predict diet? p. 263-291. In: Boyd
IL (ed) Marine mammals: advances in behavioural and population biology, Vol 66. The Zoological Society of London, Clarendon
Press, Oxford, UK.
Karpouzi, V.S. 2005. Modelling and mapping trophic overlap between fisheries and the world’s seabirds. M.Sc. dissertation,
University of British Columbia, Vancouver BC, Canada.
Kaschner, K. 2004. Modelling and mapping of resource overlap between marine mammals and fisheries on a global scale. Ph.D.,
University of British Columbia.
Kaschner, K., Pauly, D. 2005. Competition between marine mammals and fisheries: food for thought. p. 95-117. In: D. J. Salem and
A. N. Rowan (eds.), The state of animals III: 2005. Humane Society Press, Washington, D. C.
Kaschner, K., Watson, R., Trites, A.W., Pauly, D. 2006. Mapping worldwide distributions of marine mammals using a Relative
Environmental Suitability (RES) model. Marine Ecology Progress Series 316, 285-310.
Kenney, R.D., Scott, G.P., Thompson, T.J., Winn, H.E. 1997. Estimates of prey consumption and trophic impacts of cetaceans in the
USA northeast continental shelf ecosystem. Journal of Northwest Atlantic Fishery Science 22, 155-171.
Klumov, S.K. 1963. Food and helminth fauna of whalebone whales (Mysticeti) in the main whaling regions of the world oceans. Tr.
Inst. Okeanol. Akad. Nauk SSSR 71, 94-194.
Lea, M-A., Cherel, Y., Guinet, C., Nichols, P.D. 2002. Antarctic fur seals foraging in the Polar Frontal Zone: inter-annual shifts in diet
as shown from fecal and fatty acid analyses. Marine Ecology Progress Series 245, 281-297.
Leaper, R., Lavigne, D. 2002. Scaling prey consumption to body mass in cetaceans (SC/J02/FW2) International Whaling
Commission - Modelling Workshop on Cetacean-Fishery Competition. (unpublished), La Jolla, US, 12 p.
Lilliendahl, K., Solmundsson, J. 1997. An estimate of summer food consumption of six seabird species in Iceland. ICES Journal of
Marine Science 54, 624-630.
Lockyer, C. 1981a. Estimates of growth and energy budget for the sperm whale, Physeter catodon, p. 379-487. In: Mammals in the
Seas: General Papers and Large Cetaceans, Vol 3. FAO Fisheries Series 5, Rome.
Lockyer, C. 1981b. Growth and energy budgets of large baleen whales from the southern hemisphere, p. 379-487. In: Mammals in the
Seas: General Papers and Large Cetaceans, Vol 3. FAO Fisheries Series 5, Rome.
MacArthur, R.H., Levins, R. 1967. The limiting similarity, convergence and divergence of coexisting species. American Naturalist 101,
377-385.
Morisita, M. 1959. Measuring of interspecific association and similarities between communities. Memoirs of the Faculty of Science,
Kyushu University, Series E, 3, 64-80.
Mullin, K.D., Fulling, G.L. 2003. Abundance and distribution of cetaceans in the southern U.S. Atlantic Ocean during summer 1998.
Fishery Bulletin 101, 603-613.
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
45
Nagy, K.A., Girard, I.A., Brown, T.K. 1999. Energetics of free-ranging mammals, reptiles, and birds. Annual Reviews of Nutrition 19,
247-277
Nilssen, K.T. 1995. Seasonal distribution, condition and feeding habits of Barents Sea harp seals (Phoca groenlandica). p. 241-254.
In: Blix AS, Walløe L, Ulltang Ø (eds) Whales, seals, fish and man - Proceedings of the International Symposium on the Biology
of Marine Mammals in the North East Atlantic, Tromsø, Norway, 29 November - 1 December 1994, Vol 4. Elsevier, Amsterdam.
Pauly, D., Trites, A.W., Capuli, E., Christensen, V. 1998. Diet composition and trophic levels of marine mammals. ICES Journal of
Marine Science 55, 467-481.
Perrin, W.F., Würsig, B., Thewissen, J.G.M. (eds). 2002. Encyclopedia of marine mammals, Academic Press.
Punt, A.E., Butterworth, D.S. 1995. The effects of future consumption by Cape fur seal on catches and catch rates of the Cape hakes.
4. Modelling the biological interaction between Cape fur seals Arctocephalus pusillus pusillus and the Cape hake Merluccius
capensis and Merluccius paradoxus. South African Journal of Marine Science 16, 255-285.
Reijnders, P., Brasseur, S., van der Toorn, J., van der Wolf, R., Boyd, I.L., Harwood, J., Lavigne, D.M., Lowry, L. 1993. Seals, fur
seals, sea lions, and walrus. Status survey and conservation action plan, IUCN/SSC Specialist Group, International Union for the
Conservation of Nature and Natural Resources, Gland, Switzerland.
Ridgway S.H., Harrison, R.J. (eds). 1999. The Second Book of Dolphins and the Porpoises, Vol 6. Academic Press, New York.
Schreiber, E.A., Burger, J. (eds). 2002. Biology of Marine Birds. CRC Marine Biology Series, CRC Press, Boca Raton, FL.
Shelton, P.A., Warren, W.G., Stenson, G.B. 1997. Quantifying some of the major sources of uncertainty associated with estimates of
harp seal prey consumption. Part II: Uncertainty in consumption estimates associated with population size, residency, energy
requirements and diet. Journal of Northwest Atlantic Fishery Science 22, 303-315.
Sigurjónsson, J., Víkingsson, G.A. 1997. Seasonal abundance of and estimated food consumption by cetaceans in Icelandic and
adjacent waters. Journal of Northwest Atlantic Fishery Science 22, 271-287.
Smith, S.J., Iverson, S.J., Bowen, W.D .1997. Fatty acid signatures and classification trees: new tools for investigating the foraging
ecology of seals. Canadian Journal of Fisheries and Aquatic Sciences 54, 1377-1386.
Spear, L.B, Ainley, D.G .1999. Migration routes of Sooty shearwaters in the Pacific Ocean. Condor 101, 205-218.
Stern, S.J. 2002. Migration and movement patterns. p. 742-748. In: Perrin WF, Würsig B, Thewissen HGM (eds) Encyclopedia of
Marine Mammals. Academic Press, San Diego, USA.
Stevick, P.T., McConnell, B.J., Hammond, P.S. 2002. Patterns of Movement. p. 185-216. In: Hoelzel AR (eds) Marine Mammal
Biology - An Evolutionary Approach. Blackwell Science Ltd.
Tamura, T. 2001. Geographical and seasonal changes of prey species and prey consumption in the western North Pacific minke
whales. (SC/9/EC/8) International Whaling Commission - Scientific Committee Meeting (unpublished), Norway, 13 p.
Tamura, T. 2003. Regional assessment of prey consumption and competition by marine cetaceans in the world. p. 143-170. In:
Sinclair M, Valdimarsson G (eds) Responsible Fisheries in Marine Ecosystems. Food and Agricultural Organisation of the United
Nations and CABI Publishing, Wallingford, UK.
Tollit, D.J., Steward, M., Thompson, P.M., Pierce, G.J., Santos, M.B., Hughes, S. 1997. Species and size differences in the digestion of
otoliths and beaks; implications for estimates of pinniped diet composition. Canadian Journal of Fisheries and Aquatic Sciences
54, 105-119.
Tollit, D.J., Wong, M., Winship, A.J., Rosen, D.A.S., Trites, A.W. 2003. Quantifying errors associated with using prey skeletal
structures from fecal samples to determine the diet of Steller’s sea lion (Eumetopias jubatus). Marine Mammal Science 19, 724–
744.
Trites, A.W., Christensen,V., Pauly D. 1997. Competition between fisheries and marine mammals for prey and primary production in
the Pacific Ocean. Journal of North West Atlantic Fishery Science 22, 173-187.
Trites, A.W., Pauly D. 1998. Estimating mean body masses of marine mammals from maximum body lengths. Canadian Journal of
Zoology 76, 886-896.
Velando, A., Freire, J .1999. Intercolony and seasonal differences in the breeding diet of European shags on the Galician coast (NW
Spain). Marine Ecology Progress Series 188, 225-236.
Watson, R., Kitchingman, A., Gelchu, A., Pauly, D. 2004. Mapping global fisheries: sharpening our focus. Fish and Fisheries 5, 168177.
WCMC 2006. The World Conservation Monitoring Centre Species Database. [Available at http://www.unep-wcmc.org/right.htm.
Accessed 18 July 2006].
Whitehead, H.P. 2002. Estimates of the current global population size and historical trajectory for sperm whales. Marine Ecology
Progress Series 242, 295-304.
Wickens, P., York, A.E. 1997. Comparative population dynamics of fur seals. Marine Mammal Science 13, 241-292.
Wickens, P.A., Japp, D.W., Shelton, P.A., Kriel, F., Goosen, P.C., Rose, B., Augustyn, C.J., Bross, C.A.R., Penney, A.J., Krohn, R.G.
1992. Seals and fisheries in South Africa - competition and conflict. p 773-789. In: Payne, A.I.L., Brink, K.H., Mann, K.H.,
Hilborn, R. (eds.) Benguela Trophic Functioning, Vol 12.
Winship, A.J., Trites, A.W., Rosen, D.A.S. 2002. A bioenergetic model for estimating the food requirements of Steller sea lions
Eumetopias jubatus in Alaska, USA. Marine Ecology Progress Series 229, 291-312.
46
Forage fish c0nsumption by marine mammals and seabirds, K. Kaschner, V. Karpouzi, R. Watson and D. Pauly
Yodzis, P. 2001. Must top predators be culled for the sake of fisheries? Trends in Ecology and Evolution 16, 78-83.
Young, J.W .2000. Do large whales have an impact on commercial fishing in the South Pacific Ocean. Journal of International
Wildlife Law and Policy 3, 1-32.
Zeppelin, T.K., Tollit, D.J., Call, K.A., Orchard, T.J., Gudmundson, C.J. 2004. Sizes of walleye pollock (Theragra chalcogramma)
and Atka mackerel (Pleurogrammus monopterygius) consumed by the western stock of Steller sea lions (Eumetopias jubatus) in
Alaska from 1998-2000. Fishery Bulletin 102, 3, 509-521.