Bayesian inference in camera trapping studies for a class of spatial capture-recapture models

Andrew Royle, J. ; Ullas Karanth, K. ; Gopalaswamy, Arjun M. ; Samba Kumar, N. (2009) Bayesian inference in camera trapping studies for a class of spatial capture-recapture models Ecology, 90 (11). pp. 3233-3244. ISSN 0012-9658

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Official URL: http://www.esajournals.org/doi/abs/10.1890/08-1481...

Related URL: http://dx.doi.org/10.1890/08-1481.1

Abstract

We develop a class of models for inference about abundance or density using spatial capture-recapture data from studies based on camera trapping and related methods. The model is a hierarchical model composed of two components: a point process model describing the distribution of individuals in space (or their home range centers) and a model describing the observation of individuals in traps. We suppose that trap- and individual-specific capture probabilities are a function of distance between individual home range centers and trap locations. We show that the models can be regarded as generalized linear mixed models, where the individual home range centers are random effects. We adopt a Bayesian framework for inference under these models using a formulation based on data augmentation. We apply the models to camera trapping data on tigers from the Nagarahole Reserve, India, collected over 48 nights in 2006. For this study, 120 camera locations were used, but cameras were only operational at 30 locations during any given sample occasion. Movement of traps is common in many camera-trapping studies and represents an important feature of the observation model that we address explicitly in our application.

Item Type:Article
Source:Copyright of this article belongs to Ecological Society of America.
Keywords:Abundance; Bayesian Analysis; Binomial Point Process; Camera Trapping; Carnivore Surveys; Data Augmentation; Density Estimation; Hierarchical Model; Markov Chain Monte Carlo; Spatial Capture- recapture; Tigers; Trapping Array; Trapping Grid
ID Code:89470
Deposited On:27 Apr 2012 13:58
Last Modified:19 May 2016 04:01

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