Bayes and Emprical Bayes Estimators of Abundance and Density from Spatial Capture-Recapture Data

• Activity Number: 525
• Type: Topic Contributed
• Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Robert Dorazio*+
• Companies: U.S. Geological Survey
• Keywords: animal movement ; capture-recapture ; mark-resight ; spatial point process

Abstract

In capture-recapture surveys movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the capture (or resighting) locations of each individual, allow population density and abundance to be estimated while accounting for differences in detectability of individuals induced by their movements. I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In both models Poisson point processes are used to specify spatial variation in individual activity centers. I show that estimators of population density and abundance follow naturally from the underlying assumptions of these models and are directly related to empirical Bayes estimators associated with classical (non-Bayesian) methods of analysis. I compare Bayes and empirical Bayes esimates of abundance for a population of tigers detected in camera-trap surveys and for a population of lizards detected in area-search surveys.