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

• DOI: 10.1890/08-1481.1
• Publication Date: 2009-11-04T21:30:41Z
• Authors: J. Andrew Royle; K. Ullas Karanth; Arjun M. Gopalaswamy; N. Samba Kumar
• Keywords: Mark and recapture; Camera trap; Home range

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 hierarchical composed two components: point process describing the distribution individuals in space (or their home range centers) observation traps. suppose that trap‐ individual‐specific capture probabilities are function distance between individual centers trap locations. show can be regarded as generalized linear mixed models, where random effects. adopt Bayesian framework under these formulation augmentation. apply to tigers Nagarahole Reserve, India, collected over 48 nights 2006. For this study, 120 locations were used, but cameras only operational at 30 during any given sample occasion. Movement traps common many camera‐trapping represents an important feature we address explicitly our application.