Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

A semiparametric Bayesian method for detecting Allee effects

Masatoshi Sugeno and Stephan B. Munch
Ecology
Vol. 94, No. 5 (May 2013), pp. 1196-1204
Published by: Wiley
Stable URL: http://www.jstor.org/stable/23435961
Page Count: 9
  • Download ($42.00)
  • Subscribe ($19.50)
  • Cite this Item
A semiparametric Bayesian method for detecting Allee effects
Preview not available

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.

Page Thumbnails

  • Thumbnail: Page 
1196
    1196
  • Thumbnail: Page 
1197
    1197
  • Thumbnail: Page 
1198
    1198
  • Thumbnail: Page 
1199
    1199
  • Thumbnail: Page 
1200
    1200
  • Thumbnail: Page 
1201
    1201
  • Thumbnail: Page 
1202
    1202
  • Thumbnail: Page 
1203
    1203
  • Thumbnail: Page 
1204
    1204