OIKOS 100: 333– 341, 2003
Breeding success of sympatric dabbling ducks in relation to
population density and food resources
Johan Elmberg, Petri Nummi, Hannu Pöysä and Kjell Sjöberg
Elmberg, J., Nummi, P., Pöysä, H. and Sjöberg, K. 2003. Breeding success of
sympatric dabbling ducks in relation to population density and food resources. –
Oikos 100: 333– 341.
Breeding success in sympatric mallard Anas platyrhynchos, teal A. crecca and wigeon
A. penelope in a boreal watershed in Finland was studied for 12 years. Benthic and
surface-emerging prey animals were trapped to obtain annual indices of food
abundance. Mallard and teal were equally abundant over the years, being roughly
twice as numerous as wigeon.
Pair density, brood:pair ratio and duckling:pair ratio were used to test the hypothesis
that per capita breeding success decreases in a density-dependent fashion as either
pair density or the number of nesting pairs per available food unit increases. In
mallard we found no density-dependent patterns at all. In teal per capita brood
production decreased as prey animals became relatively scarcer, but this interpretation may not be robust. In wigeon, however, there were two independent significant
patterns of direct density-dependence in a temporal succession, i.e. between pair
density and per capita brood production in the early part of the breeding season, and
then between per capita abundance of surface-emerging insect prey and the number
of ducklings per pair. Despite wide dietary overlap and frequent co-occurrence on
single lakes among species in the guild, we found no evidence for interspecific
density-dependent effects. We hypothesize that there is no or infrequent food
limitation for breeding dabblers in this system, and that behavior may be the process
behind the pattern of density-dependence in wigeon.
J. Elmberg, Dept of Mathematics and Natural Sciences, Kristianstad Uni6., SE-291 88
Kristianstad, Sweden ( johan.elmberg@mna.hkr.se). – P. Nummi, Dept of Applied
Biology, Uni6. of Helsinki, P.O. Box 27, FIN-00014 Uni6ersity of Helsinki, Finland. –
H. Pöysä, Finnish Game and Fisheries Res. Inst., Joensuu Game and Fisheries
Research, Kauppakatu 18 -20, FIN-80100 Joensuu, Finland. – K. Sjöberg, Dept of
Animal Ecology, Swedish Uni6. of Agricultural Sciences, SE-901 83 Umeå, Sweden.
Nicholson (1933) was one of the first to discuss whether
animal populations are regulated by density-dependent
feed-back processes on breeding performance and mortality. Almost 70 years later the topic remains controversial and largely unresolved despite extensive research
and syntheses (Woiwood and Hanski 1992, Newton
1998). Important reasons for this are a continuous
development and change of analytical tools to detect
density-dependence as well as recurring disagreement
about the conceptual foundation (Vickery and Nudds
1984, Pollard et al. 1987, Dennis and Taper 1994,
Reddingius 1996, Shenk et al. 1998, Berryman and
Turchin 2001, White 2001). Moreover, when and where
there is actually consensus that density-dependent processes affect populations, they may vary in strength in
space and time, or act only intermittently.
Despite these difficulties, interest in density-dependent population processes is likely to remain strong,
especially when it comes to wildfowl and other harvested animals. This is because decisions about conservation as well as levels and timing of harvest need to
rest on an understanding of how and when populations
are limited or regulated (Caughley and Sinclair 1994,
Kokko et al. 1998, Boyce et al. 1999), e.g. whether
Accepted 15 July 2002
Copyright © OIKOS 2003
ISSN 0030-1299
OIKOS 100:2 (2003)
333
harvest mortality is compensatory or additive in relation to natural mortality.
Population ecology of ducks in the Holarctic has
been part of the issue of density-dependence for
decades, but evidence is still contradictory whether
duck numbers are mainly determined by density-independent factors such as winter cold and summer
drought, or by density-dependent feedback on breeding
success or mortality (Anderson and Burnham 1976,
Burnham and Andersson 1984, Kaminski and Gluesing
1987, Bethke 1993, Trost et al. 1993, Krapu et al. 1997,
Newton 1998, Sheaffer 1998). One reason for disagreement may be that patterns and processes really do
differ significantly between years, sites, species, and
even between populations of the same species. As most
studies of per capita breeding success in dabbling ducks
have been done in their North American range there is
a general lack of corresponding European data.
Taking the mallard (Anas platyrhynchos L.) as an
example, there is no consistent pattern even in the
rather few European studies which have addressed resource limitation during the breeding period and density-dependence in breeding success. Based on
long-term observational data, Hill (1984) found evidence for direct density-dependence in breeding success,
and we have experimental data showing that ducklings
may experience food limitation on some oligotrophic
boreal lakes (Nummi et al. 2000, Pöysä et al. 2000,
Sjöberg et al. 2000). However, in contrast to the latter
three studies, descriptive long-term data from similar
settings in Finland reveal no pattern of density-dependent breeding success (Pöysä 2001). From a European
perspective per capita breeding success and recruitment
patterns thus need to be studied under yet a wider
range of natural settings, regionally as well as on the
continental scale.
Another but general and more fundamental problem
to this date is the total lack of studies of density-dependence in waterfowl and in other species in which per
capita birth or death rate is related to resource units
instead of density (i.e. individuals per area unit; cf.
Newton 1998, p. 115). As levels of crucial resources
frequently vary between years and among superficially
similar patches, this lack may disqualify conclusions in
many previous studies, especially if density-dependence
is thought to be mediated through resource competition. A connection between abundance of invertebrate
prey and breeding success, specifically duckling performance, is well established for waterfowl (Hill et al.
1987, Sediger 1992, Cooper and Anderson 1996, Cox et
al. 1998), highlighting the relevance of studies
combining density and per capita resource availability.
We here relate variation in per capita breeding success in three sympatric breeding dabbling ducks to
population density and food resource abundance over a
12-year period. Specifically, we: a) describe natural
variation in the number of pairs, broods, and older
334
(pre-fledgling) ducklings, b) describe between-year variation in nesting success and brood mortality, c) test the
hypothesis of intraspecific density-dependent breeding
success (per capita birth rate), and d) test the rarely
addressed hypothesis of intraguild heterospecific density-dependence in breeding success.
Materials and methods
Study area
This study was carried out in an oligotrophic mid-boreal watershed (area 39 km2) at Evo in southern Finland (61°10% N, 25°05% E). All 52 permanent lakes and
ponds within the watershed were included, except for
one with obvious human disturbance (Kaitalammi at
the Evo Game Research Station). Total lake area is 290
hectares and their total shoreline is 50 775 m (mean lake
area 5.6 ha, range 0.1 – 49.5 ha, only nine lakes larger
than 10 ha). Boreal evergreen forest covers most of the
watershed, with lakes and mires mixed in. Agriculture
and human settlement are very limited and local, hence
also lake eutrophication and vegetation change.
Lakeshores are generally steep with little emergent vegetation (mainly Carex spp.), although a few are more
mesotrophic with narrow stands of Equisetum spp.,
Typha spp., and Phragmites australis (Ca6.) Steud.
Located in a continental cool climate, the study lakes
are frozen over from November to late April. They are
thus ‘‘colonized anew’’ each spring by long-distance
migrating ducks. We regard the waterfowl populations
in the watershed as closed during the breeding season,
with negligible immigration and emigration of adults
and broods. However, broods may sometimes move
between adjacent lakes within the watershed.
Waterfowl counts
The number of nesting pairs of mallard, teal (Anas
crecca L.), and wigeon (Anas penelope L.) was estimated using data from the earlier of two pair counts in
May each year in 1989 –2000 (Nummi and Pöysä 1995;
see Koskimies and Pöysä 1991 for general method).
Breeding success was monitored in five brood counts
(combined point and round counts as described in
Nummi and Pöysä 1995) in June through July. Duckling age was determined following the classification by
Pirkola and Högmander (1974) i.e. a combination of
schemes in Gollop and Marshall (1954) and Linkola
(1962). Breeding success is here expressed as: a) the
number of broods, and b) the number of ducklings in
stage 2a or older per brood (i.e. 19 – 25 days old;
Schemnitz 1980). When there were multiple observations of a brood in stage 2a or older, we used data from
the latest sighting until stage 3 if fledglings were obOIKOS 100:2 (2003)
served too. If fledged juveniles but not stage 3 ducklings
were seen, the number of juveniles on a lake was used
instead. Fledged birds on lakes where there were no
previous duckling observations were included, as they
were supposed to be of local origin.
mates assumed to be representative for the entire watershed that breeding season (cf. pp. 583 –585 in Pöysä et
al. 2000). There were generally four traps of each type
on all lakes, but food indices are expressed as means
per 100 trap days to compensate for lost traps and a
shorter sampling period in 1989.
Food resources
Our general methods for trapping prey invertebrates in
activity and emergence traps are described in Nummi
and Pöysä (1993). For the present study we used catch
data from eight of the 52 lakes: Iso Vehkajärvi, Iso
Ruuhijärvi, Keskinen Mustajärvi, Majajärvi, Pitkänniemenjärvi, Rahtijärvi, Tekumi (Saukonlammi), and
Ylinen Rautjärvi. Samples were from one week’s trapping in early June each year (exact dates somewhat
different between years in order to adjust for phenological differences), assuming that prey abundance at this
time best reflects what is available to ducklings of all
three species during their early and most vulnerable
period in life (Hill et al. 1987). Activity traps were used
to catch benthic and free-swimming taxa, of which all
invertebrates and small tadpoles were used for the
present analyses. Floating emergence traps were used to
sample invertebrates leaving their aquatic stage.
Food index 1 (FI 1) is based on activity trap data
and was obtained by weighting for differences between
lakes in size-abundance distribution of prey and in
vegetation luxuriance (as in Nummi and Pöysä 1993,
1995). Food index 2 (FI 2) is based on the same data
from the same traps but is simply the mean number of
invertebrates caught per trap per day, i.e. there was no
weighting for differences in prey size or in vegetation
luxuriance. Food index 3 (FI 3) is the mean number of
insects per emergence trap per day. As the present
analysis is on the watershed level, food indices for each
of the eight lakes were pooled and averaged on a
year-by-year basis to obtain resource abundance esti-
Statistical procedures
All tests were run with SYSTAT 9.01 (SPSS Inc.), and
two-tailed probabilities were used unless stated otherwise. Variables that deviated significantly from normality as revealed by the Lilliefors test (P B0.05, N =12
years throughout) were log-transformed before subsequent analyses. Arcsine transformation was not used as
no ratio variables deviated significantly from normality.
All tests were also run with corresponding non-parametric procedures, producing the same result in 98% of
the cases (all tests but one).
Results
Duck numbers
Pair counts revealed that mallard and teal were equally
numerous in the Evo watershed over the years and
roughly twice as abundant as the wigeon (Table 1). In
all three species, pair, brood and duckling numbers
varied considerably, being up to four times higher in
‘‘peak years’’ than in ‘‘bottom years’’. Between-year
variations were larger in mallard and teal than in
wigeon. Teal and wigeon produced more broods per
pair than did mallards (ANOVA; F = 5.76, N = 36,
P B0.01). The number of ducklings per pair averaged
more similar among the species, but it was significantly
higher in teal than in mallard (t-test; t = − 2.24, P B
0.05).
Table 1. Breeding data for dabbling ducks on 52 lakes in a watershed in southern Finland in 1989–2000. All numbers are based
on data from 12 breeding seasons. ‘‘Density’’ denotes mean per 1000 m shoreline.
Mallard
Mean
Range
CV
Density
Teal
Mean
Range
CV
Density
Wigeon
Mean
Range
CV
Density
OIKOS 100:2 (2003)
Pairs
Broods
Ducklings
Broods/pair
Ducklings/pair
21.3
9–35
0.39
0.42
5.1
2–11
0.55
0.10
20.7
7–46
0.52
0.41
0.24
0.11–0.41
0.41
0.96
0.56–1.48
0.31
20.2
12–41
0.39
0.40
8.0
2–16
0.46
0.16
28.0
8–68
0.58
0.55
0.40
0.15–0.58
0.34
1.36
0.62–2.42
0.40
8.9
4–14
0.36
0.18
3.33
2–5
0.32
0.07
10.2
1–17
0.43
0.20
0.42
0.17–0.71
0.42
1.23
0.11–2.20
0.47
335
Teal and mallard co-varied in the sense that ‘‘good
mallard years’’ were also ‘‘good teal years’’, measured
as the correlation between pair number, brood number
and duckling number in these species (Pearson correlation coefficients (r): 0.77 (P B 0.001), 0.63 (P B 0.02),
0.73 (P B 0.005), N =12 years throughout). Pair, brood
as well as duckling number in wigeon varied independently of the other two species (P \ 0.1 in all cases;
N = 12).
Food resources
A general picture of the taxonomic composition of the
catch in the activity traps is given by Elmberg et al.
(1992) and in Table 1 in Pöysä et al. (1994a, b).
Emergence trap catches were totally dominated by
Diptera, Trichoptera, and Ephemeroptera in order of
decreasing abundance. Overall prey abundance varied
considerably between years as revealed by the food
indices, but decreasingly so from FI 1 to FI 3 (Table 2).
Fluctuations were general on the watershed level, i.e.
lakes kept their general rank between years, further
justifying the use of pooled indices as measures of food
resource levels (Fig. 1; Kendall%s coefficient of concordance (W): 0.23 for FI 1, 0.36 for FI 2, and 0.25 for FI
3; PB 0.006 in all cases; M =12 years, N = 8 lakes).
Food indices were not significantly correlated with each
other, and r-values in pair-wise tests were not even
consistent in sign. Thus, all three indices were used as
independent variables in subsequent analyses when
looking for patterns in breeding success.
Although nesting and brooding generally preceded
prey sampling, the number of broods observed was
Table 2. Food indices (FI 1–3) obtained from eight lakes in
the Evo watershed. Annual numbers are mean and standard
deviation (N = 8 lakes). All indices are expressed per 100 trap
days. FI 1 and FI 2 were obtained from activity traps catching
mainly benthic and free-swimming taxa, whereas FI 3 was
based on floating emergence traps catching insects leaving
their aquatic stage.
Year
Food
index 1
Food
index 2
Food
index 3
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
69.4 (45.9)
184 (110)
202 (272)
426 (338)
177 (74.7)
196 (142)
118 (36.0)
103 (67.1)
382 (381)
447 (326)
475 (296)
318 (273)
138 (85.4)
156 (172)
217 (351)
264 (212)
60.7 (32.0)
311 (274)
126 (49.6)
156 (123)
118 (89.6)
146 (58.2)
134 (45.0)
109 (88.9)
72.6
40.2
71.4
46.2
26.8
55.4
30.4
43.3
24.1
58.9
33.0
44.2
12 year mean
12 year range
CV
257.8
69.4–475
0.56
161.4
60.7–311
0.43
45.6
24.1–72.6
0.36
336
(48.5)
(19.8)
(35.3)
(18.1)
(21.8)
(24.1)
(19.5)
(21.6)
(17.0)
(23.5)
(17.8)
(39.9)
Fig. 1. Lake-level between-year variation in food resources on
eight lakes. Food index 1 and 2 concern benthic invertebrates,
food index 3 surface-emerging insects (see methods for calculation and units). Year 1 – 12 is 1989 – 2000.
positively correlated with FI 3 in teal (r =0.74, P B
0.005, N =12) and with FI 1 in wigeon (r =0.56,
PB 0.05, N = 12). Mallard brood number did not correlate with any food index (P \ 0.2). Based on the
well-established positive association between invertebrate abundance and duckling performance (Hill et al.
1987, Sediger 1992, Cooper and Anderson 1996, Cox et
al. 1998) we next considered an explicitly one-sided
assumption of positive correlation between food indices
and duckling number. There was none in mallard and
wigeon, but in teal duckling number was significantly
correlated with FI 3, i.e. surface-emerging insects (r =
0.51, P B 0.05, N =12 years).
Per capita breeding success vs density
As lake area and shoreline length did not vary between
years, the number of nesting pairs in a given year
became a density measure in itself. We thus used pair
number as ‘‘the classical density measure’’, and broods/
nesting pair as well as ducklings/nesting pair as measures of per capita breeding success. In pair-wise
correlations there is no pattern of density-dependent
decrease in productivity in either mallard or teal (denOIKOS 100:2 (2003)
density on the one hand, and per capita brood or
duckling productivity on the other (test results as in
previous sentence).
Per capita breeding success vs food resources
Fig. 2. Intraspecific direct density-dependence in per capita
brood production in wigeon in an oligotrophic watershed in
southern Finland. Pearson correlation coefficient= −0.72,
PB 0.005, N = 12 years. ‘‘Breeding density index’’ is the number of pairs in the watershed. To obtain pairs per km2 lake
area divide the index by 2.9, and to obtain pairs per 1000 m
shoreline divide by 50.8. Two data points have the same value
at X = 9, Y = 0.44.
sity vs broods per pair and density vs ducklings per
pair: P \ 0.5, and N =12 in all four cases). In wigeon,
however, brood:pair ratio decreases significantly as pair
density increases (Fig. 2). Tested similarly, there is no
significant density-dependence in wigeon duckling productivity, although the trend was clearly negative also
in this case (r = −0.43, P \0.10).
Years of high or low per capita productivity were not
the same in the three species; i.e. there was no correlation in pair-wise comparisons (mallard vs teal, teal vs
wigeon, mallard vs wigeon), neither for per capita
brood number nor for per capita duckling number (r
with no consistency in sign within species-pair comparisons; P\0.1 and N = 12 in all six cases).
As a consequence of the wide dietary overlap between ducklings of dabbling ducks (Sugden 1973, Sediger 1992) it is fair to hypothesize that densitydependent processes may also occur within the guild,
i.e. as a result of interspecific interactions. We thus
tested for correlation between breeding performance in
a certain species and its corresponding heterospecific
pair density, i.e. the combined pair number (density) of
the two other species in a given year. Neither
brood:pair ratio nor duckling:pair ratio correlated with
the combined heterospecific pair density in any of the
three species (P \ 0.5 in mallard and teal, P \ 0.05 in
wigeon; N= 12). Finally, assuming combined intraand interspecific competition produced the same result
for all species, i.e. no correlation between combined
OIKOS 100:2 (2003)
When it comes to food and the general hypothesis of
resource-mediated density-dependence in breeding success we have an explicitly directional prediction; brood
and duckling production per pair should both increase
as the number of food units per pair and brood increases. This is often considered ‘the true test’ of density-dependence, though so far only rarely performed
(Newton 1998).
For each species each food index was divided by pair
number on an annual basis to obtain an intraspecific
estimate of ‘‘food units per pair’’, which in turn was
tested for correlation with the per capita breeding success variables for this species (Table 3, ‘‘conspecific
rows’’). For mallard there was neither any significant
correlation nor any consistency in sign. However, the
correlation coefficient was positive throughout for teal
and wigeon, and four pair-wise tests were significant,
meeting the prediction of increased per capita breeding
success with increased per capita food abundance in
both species. Per capita production of ducklings in
wigeon was the most significant association and FI 3 is
here in practice abundance of Diptera, mainly Chironomidae (Fig. 3).
Similarly, annual food indices were divided by the
combined number of pairs of two species at a time to
obtain a heterospecific ‘‘food units per pair’’ estimate
for the third species (e.g. FI 1 for a given year was
divided by the combined number of mallard and teal
pairs that year to address food-mediated heterospecific
density-dependence in breeding success in wigeon).
Again, per capita breeding success in a species was
predicted to increase as the food abundance per putative competitor increased, but there were no significant
correlations and no consistency in sign for any species
(Table 3, lower three rows). With respect to food
resources our data thus refute the hypothesis of intraguild heterospecific density dependence in breeding
success.
Models for density-dependence
Multiple stepwise regression was applied to analyze the
three cases in which breeding success showed densitydependent patterns in pair-wise tests, i.e. brood:pair
ratio in teal and both breeding success measures in
wigeon. Independent variables were pair density for
each of the three species and the intraspecific food unit
abundance for FI 1 through FI 3. Combining variables
of plain pair density and food units per pair in this way,
did not, however shed any new light. When the original
337
Ducklings/pair
0.29, P \ 0.10
0.25, P \ 0.10
0.65, PB0.01
0.07, P \ 0.25
−0.43, P \ 0.05
0.10, P \ 0.25
Broods/pair
0.42, P \ 0.05
0.42, P \0.05
0.49, PB0.05
0.28, P \0.10
−0.24, P \0.10
−0.18, P \ 0.25
Food resource measure
FI 1/breeding conspecific pairs
FI 2/breeding conspecific pairs
FI 3/breeding conspecific pairs
FI 1/breeding heterospecific pairs
FI 2/breeding heterospecific pairs
FI 3/breeding heterospecific pairs
Broods/pair
0.44, P \ 0.05
−0.10, P \ 0.25
−0.14, P \0.25
0.32, P \ 0.10
−0.25, P \0.10
−0.25, P \0.10
Ducklings/pair
−0.13, P \ 0.25
0.27, P \ 0.10
−0.10, P \ 0.25
−0.05, P \ 0.25
0.22, P \ 0.10
−0.12, P \ 0.25
Broods/pair
0.36, P \ 0.10
0.49, PB0.05
0.49, PB0.05
0.29, P \ 0.10
−0.01, P \ 0.25
0.31, P \ 0.10
Ducklings/pair
0.14, P \ 0.25
0.40, P \0.05
0.14, P \ 0.25
0.19, P \0.25
0.18, P \ 0.25
0.06, P \0.25
Wigeon breeding success
Teal breeding success
Mallard breeding success
Table 3. Per capita breeding success in relation to per capita prey abundance in dabbling ducks. Given are Pearson correlation coefficients, and one-tailed probabilities because a
positive association is assumed. N = 12 years in all cases. Food indices (FI 1, FI 2, and FI 3) are explained briefly in Table 2 and fully in the methods section.
338
Fig. 3. Intraspecific prey resource-related direct density-dependence in breeding success in wigeon, i.e. the number of ducklings per pair decreases as the number of emerging insects per
wigeon pair decreases. Pearson correlation coefficient= 0.65,
PB 0.01, N = 12 years. Food index 3 is described in materials
and methods.
strongest pair-wise correlation had entered each model,
coefficients of partial correlations for the remaining
variables were too low to let them enter, and all models
thus remained univariate.
Discussion
Abundance of ducks
Species composition and relative abundance of the species in this study are representative for waterfowl communities of the boreal forest biome in the Western
Palearctic (Haapanen and Nilsson 1979, Elmberg et al.
1994, Hagemeijer and Blair 1997, Väisänen et al. 1998).
In all three species pair density corresponds well with
Finnish national means (Väisänen et al. 1998). Together
this indicates that we have been studying rather typical
duck communities in rather typical years.
Mallard brood:pair ratios are somewhat higher than
those observed in boreal Canada by Nudds and Cole
(1991), but they fall in the middle of the general range
reported for this widespread species (Johnson et al.
1992). Brood:pair ratios fell in the order wigeon – teal–
mallard, a pattern corresponding well to previous
Finnish findings (Nummi and Pöysä 1995, 1997). The
proximate cause behind this trend is unclear, but it may
reflect differences between species in nesting phenology
and a concurrent decrease in predation from early to
late nesters. Support for this hypothesis is provided
from Latvia, where Opermanis et al. (2001) found that
OIKOS 100:2 (2003)
large corvids were the main predators on early nests,
i.e. chiefly mallard.
Food resources
Plain brood number was correlated with prey abundance in two out of nine pair-wise tests (3 species ×3
indices). In general this watershed level study thus
shows surprisingly weak links between annual invertebrate abundance and overall breeding output (Hill et
al. 1987, Sediger 1992, Cooper and Anderson 1996,
Cox et al. 1998). However, none of the latter studies
concerns an oligotrophic boreal scenario, where density-independent factors such as cool weather and late
frosts may be more important on the population level
in most years than is food limitation.
Per capita breeding success vs density
Our present findings agree with those of Pöysä (2001)
in refuting direct density-dependence in breeding success in mallard. Both studies thus appear to disagree
clearly with Hill (1984), who found that mallard duckling mortality was density-dependent. It should be
noted, though, that the main regulatory mechanism in
Hill’s case was not duckling mortality but rather the
subsequent density-dependent winter mortality. The
latter factor remains to be studied in boreal populations of dabbling ducks in the Western Palearctic
(Pöysä 2001), hence the disagreement with Hill’s overall conclusion may be less than it seems. Kaminski and
Gluesing (1987) gave some support for direct densitydependence in recruitment in hemi-boreal Canadian
mallards, but we still regard the evidence for densitydependent breeding output in mallard as contradictory.
It is premature to offer an explanation why wigeon
was different from mallard and teal in its density-dependent decrease in brood and duckling production.
We may have to step down from the watershed to the
lake level in order to understand the processes behind
this pattern, and that was not the object of the present
study. However, census data show that wigeon does
not breed in lakes different from those of the other
two species, and also that it does not tend to crowd
into more lakes than the other species do. Being a
breeder of boreal forest lakes the wigeon simply remains inadequately studied and little is known of its
population biology.
We see no support for the idea that pair density of
other dabbling ducks affects per capita breeding success in any of the three species. Although it is reasonable to look for intraguild heterospecific effects,
negative or positive (Toft et al. 1982, Elmberg et al.
1997; for statistical modelling of interspecific effects in
OIKOS 100:2 (2003)
population dynamics of small mammals see Hansen et
al. 1999, Merritt et al. 2001), our results may not be
all that surprising. Population densities were low in
absolute terms and there is sometimes temporal segregation between the brood stage of the three, which
would tend to counteract food limitation and competition.
Per capita breeding success vs food resources
Following Newton (1998), p. 115 we performed a more
stringent test for density-dependence by also relating
breeding success to a specific and measurable crucial
resource, i.e. pair-specific prey abundance (Nummi and
Pöysä 1993, Cooper and Anderson 1996). From Table
3 it appears that our data support the notion that food
resources is a more relevant measure than plain pair
density, but note that three of the four significant
correlations (r = 0.49) would not have emerged had
not the prediction been explicitly directional. Interestingly, wigeon once more stands out as being different
by showing a highly significant pattern of direct density-dependence in breeding success, especially when
considering the abundance of emerging insects. This
agrees with Gardarsson and Einarsson (1997), who
found that variations in per capita breeding success in
this species corresponded well to current abundance of
Chironomidae.
With respect to mallard and teal this study rather
provides a case against food-limitation on the watershed level. At first this seems to contradict our experimental results from similar oligotrophic lakes in
near-by Sweden (Nummi et al. 2000, Sjöberg et al.
2000). However, the latter studies are lake-level approaches implying that some lakes are simply too poor
for successful brood-rearing, and we may moreover
have a situation where lake-level patterns do not translate to the watershed or population level. Similarly,
Pöysä (2001) found that habitat distribution of breeding mallards indicated habitat-specific limitation but
this did not translate to limitation at the population
level. In other words, our migratory duck females return to their natal sites, but may change lakes within
the watershed in response to current lake-specific food
conditions or to some other cue.
We did not study diet choice in ducklings in detail,
but as far as we could tell all three species foraged in
the same microhabitats at the same time of the day,
and they should thus encounter similar prey. We thus
believe that dietary overlap is very large. Still, we find
no support for density-dependent effects of food resource abundance on breeding success when related to
the number of heterospecific congeners. This suggests
that the density-dependent patterns in wigeon do indeed arise from intraspecific interactions, possibly aggressive and territorial behavior.
339
Conclusions
For this boreal setting we find no support for the
hypothesis of direct density-dependence in breeding
success in mallard. In teal there is a pattern of decreasing per capita brood production with decreasing number of food units per teal pair, but this interpretation
may be fragile. In wigeon, however, there is a consistent
and highly significant pattern of density-dependence in
temporal sequence, i.e. between plain pair density and
per capita brood production in the early part of the
breeding season, and later between per capita prey
abundance and the number of ducklings per pair.
We are well aware of the problems with time series
data and type II statistical errors, especially when it
comes to analysing patterns of density-dependence in
fluctuating population (Woiwood and Hanski 1992).
There is also a potential problem of statistical mass
significance in our analyses (Rice 1989). However, even
though we have the longest time series published for
this type of study in a multi-species assemblage of
dabbling ducks the power of our tests is low. In addition, we have tested and rejected or accepted the hypothesis of density-dependent breeding success
individually in each species. Therefore we do not consider it necessary to correct the type-I error rate (see
also Rice 1989, p. 225). Moreover, the patterns observed appear robust because results as well as interpretations were identical when we re-ran all tests with
non-parametric methods.
In order to understand population and community
processes of these species we need: 1) more data from
breeding grounds farther south in Europe, or where the
overall breeding density is higher; and 2) to look at
mortality patterns on staging and wintering grounds.
After all, Hill (1984) found the strongest density-dependent effects in winter, and similar patterns may prevail
in some shorebirds (Durell et al. 2001). To truly disentangle causal links behind undiscovered as well as documented patterns of birth and death rate in waterfowl we
strongly advocate a more experimental approach
(Sheaffer 1998, Shenk et al. 1998).
Acknowledgements – We thank all Finnish field workers who
helped in collecting data. This study was supported by the
Foundation for Research on Natural Resources in Finland
and more recently by the Swedish Environmental Protection
Agency (Naturvårdsverket), grant V-000263-99-1-00.
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