A Gibbs sampler for Bayesian analysis of site-occupancy data

Methods in Ecology and Evolution
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Abstract

1. A Bayesian analysis of site-occupancy data containing covariates of species occurrence and species detection probabilities is usually completed using Markov chain Monte Carlo methods in conjunction with software programs that can implement those methods for any statistical model, not just site-occupancy models. Although these software programs are quite flexible, considerable experience is often required to specify a model and to initialize the Markov chain so that summaries of the posterior distribution can be estimated efficiently and accurately. 2. As an alternative to these programs, we develop a Gibbs sampler for Bayesian analysis of site-occupancy data that include covariates of species occurrence and species detection probabilities. This Gibbs sampler is based on a class of site-occupancy models in which probabilities of species occurrence and detection are specified as probit-regression functions of site- and survey-specific covariate measurements. 3. To illustrate the Gibbs sampler, we analyse site-occupancy data of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly species in Switzerland. Our analysis includes a comparison of results based on Bayesian and classical (non-Bayesian) methods of inference. We also provide code (based on the R software program) for conducting Bayesian and classical analyses of site-occupancy data.
Publication type Article
Publication Subtype Journal Article
Title A Gibbs sampler for Bayesian analysis of site-occupancy data
Series title Methods in Ecology and Evolution
DOI 10.1111/j.2041-210X.2012.00237.x
Volume 3
Issue 6
Year Published 2012
Language English
Publisher Wiley
Publisher location Hoboken, NJ
Contributing office(s) Southeast Ecological Science Center
Description 6 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Methods in Ecology and Evolution
First page 1093
Last page 1098
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