Data from: Balancing food and density-dependence in the spatial distribution of an interference-prone forager
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https://datadryad.org/dataset/doi:10.5061/dryad.s8n05
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资源简介:
Foraging distributions are thought to be density-dependent, because
animals not only select for a high availability and quality of resources,
but also avoid conspecific interference. Since these processes are
confounded, their relative importance in shaping foraging distributions
remains poorly understood. Here we aimed to rank the contribution of
density-dependent and density-independent effects on the spatio-temporal
foraging patterns of eurasian oystercatchers. In our intertidal study
area, tides caused continuous variation in oystercatcher density,
providing an opportunity to disentangle conspecific interference and
density-independent interactions with the food landscape. Spatial
distributions were quantified using high-resolution individual tracking of
foraging activity and location. In a model environment that included a
realistic reconstruction of both the tides and the benthic food, we tested
a family of behaviour-based optimality models against these tracking data.
Density-independent interactions affected spatial distributions much more
strongly than conspecific interference, even in an interference-prone
species like oystercatchers. Spatial distributions were governed by
avoidance of bill injury costs, selection for high interference-free
intake rates and a decreasing availability of benthic bivalve prey after
their exposure. These density-independent interactions outweighed
interference competition in terms of effect size. We suggest that the
bottleneck in our mechanistic understanding of foraging distributions may
be primarily the role of density-independent prey attributes unrelated to
intake rates, like damage costs in the case of oystercatchers foraging on
perilous prey. At a landscape scale, above the finest inter-individual
distances, effects of conspecific interaction on spatial distributions may
have been overemphasised.
提供机构:
Dryad
创建时间:
2017-02-20



