Random placement models predict species-area relationships in duck communities despite species aggregation / Mark T. Bidwell, Andy J. Green, and Robert G. Clark.
Material type: TextSeries: Oikos. 123(12) 1499-1508 Publication details: 2014.Description: illustrations ; 28 cmLOC classification:- BID
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Includes bibliographical references (pages 1507-1508).
Species – area relationships are the product of many ecological processes and their interactions. Explanations for the
species – area relationship (SAR) have focused on separating putative niche-based mechanisms that correlate with area
from sampling eff ects caused by patches with more individuals containing more species than patches with fewer
individuals. We tested the hypothesis that SARs in breeding waterfowl communities are caused by sampling eff ects
(i.e. random placement from the regional species pool). First, we described observed SARs and patterns of species
associations for fourteen species of ducks on ponds in prairie Canada. Second, we used null models, which randomly
allocated ducks to ponds, to test if observed SARs and patterns of species associations diff ered from those expected
by chance. Consistent with the sampling eff ects hypothesis, observed SARs were accurately predicted by null models
in three diff erent years and for diving and dabbling duck guilds. Th is is the fi rst demonstration that null models can
predict SARs in waterbirds or any other aquatic organisms. Observed patterns of species association, however, were not
well predicted by null models as in all years there was less observed segregation among species (i.e. more aggregation)
than under the random expectation, suggesting that intraspecifi c competition could play a role in structuring duck
communities. Taken together, our results indicate that when emergent properties of ecological communities such
as the SAR appear to be caused by random processes, analyses of species associations can be critical in revealing the
importance of niche-based processes (e.g. competition) in structuring ecological communities.