Methods for Spatially Explicit Capture-Recapture: An Overview

Speaker: David Borchers (CREEM)

Abstract

 Spatially Explicit capture-recapture (SECR) models are varieties of capture-recapture models which use spatially referenced capture-recapture data to draw inferences about the dependence of capture probability on spatial location. One of their distinguishing features is that they allow rigorous estimates of density to be obtained from the (spatially referenced) capture-recapture data itself.

In recent years a variety of SECR estimation models and estimation methods have appeared in the literature.  In this talk I focus on the models underlying the estimation methods. It turns out that there is a neat connection between SECR models and some distance sampling models. You can construct a kind of continuum of increasingly complex models, starting with circular plot sampling, moving through varieties of distance sampling model and ending (for the moment) with SECR models. The talk includes a brief overview of SECR models in the literature. Areas of current and possible future research in the area are also briefly discussed.