A hierarchical model for spatial capture-recapture data

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Estimating density is a fundamental objective of many animal population studies. Application of methods for estimating population size from ostensibly closed populations is widespread, but ineffective for estimating absolute density because most populations are subject to short-term movements or so-called temporary emigration. This phenomenon invalidates the resulting estimates because the effective sample area is unknown. A number of methods involving the adjustment of estimates based on heuristic considerations are in widespread use. In this paper, a hierarchical model of spatially indexed capture recapture data is proposed for sampling based on area searches of spatial sample units subject to uniform sampling intensity. The hierarchical model contains explicit models for the distribution of individuals and their movements, in addition to an observation model that is conditional on the location of individuals during sampling. Bayesian analysis of the hierarchical model is achieved by the use of data augmentation, which allows for a straightforward implementation in the freely available software WinBUGS. We present results of a simulation study that was carried out to evaluate the operating characteristics of the Bayesian estimator under variable densities and movement patterns of individuals. An application of the model is presented for survey data on the flat-tailed horned lizard (Phrynosoma mcallii) in Arizona, USA.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title A hierarchical model for spatial capture-recapture data
Series title Ecology
Volume 89
Issue 8
Year Published 2008
Language English
Contributing office(s) Patuxent Wildlife Research Center
Description 2281-2289
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Ecology
First page 2281
Last page 2289