A semiparametric Bayesian method for detecting Allee effects. Issue 5 (1st May 2013)

• Record Type: Journal Article
• Authors: Sugeno, Masatoshi; Munch, Stephan B
• Is Part Of: Ecology. Volume 94:Issue 5(2013)
• Page Start: 1196
• Page End: 1204
• Publication Date: 2013-05-01
• Subjects: Allee effects -- depensation -- Gaussian process -- semiparametric Bayesian modeling; Ecology -- Periodicals; Ecology -- Periodicals; Écologie -- Périodiques; Ecologie; Écologie; Écologie animale; Écologie végétale; Ecology; Periodicals; 577.05
• DOI: 10.1890/12-0454.1
• Languages: English
• ISSNs: 0012-9658

Abstract

Abstract : 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.