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A semiparametric Bayesian method for detecting Allee effects
Masatoshi Sugeno and Stephan B. Munch
Vol. 94, No. 5 (May 2013), pp. 1196-1204
Stable URL: http://www.jstor.org/stable/23435961
Page Count: 9
You can always find the topics here!Topics: Population size, Population ecology, Parametric models, Simulations, Modeling, Datasets, Fisheries science, Conservation biology, False negative errors, Error rates
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The importance of Allee effects has long been recognized both in theoretical studies of population dynamics and in conservation sciences. Although the necessary conditions for Allee effects to occur (e.g., difficulty in finding mates and mortality driven by generalist predators at low density) would seem to apply to many species, evidence for Allee effects in natural populations is equivocal at best. This apparent scarcity might be an artifact driven by poor power to detect them with traditional parametric models. To circumvent this potential problem, we developed a semiparametric Bayesian method based on a Gaussian process prior. We validated the method using simulated data sets and applied it to three herring data sets.
Ecology © 2013 Wiley