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A Gibbs sampler for Bayesian analysis of site-occupancy data

January 1, 2013

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.

Citation Information

Publication Year 2012
Title A Gibbs sampler for Bayesian analysis of site-occupancy data
DOI 10.1111/j.2041-210X.2012.00237.x
Authors Robert M. Dorazio, Daniel Taylor Rodriguez
Publication Type Article
Publication Subtype Journal Article
Series Title Methods in Ecology and Evolution
Series Number
Index ID 70045496
Record Source USGS Publications Warehouse
USGS Organization Southeast Ecological Science Center

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