A spatial open‐population capture‐recapture model

A spatial open-population capture-recapture model is described that extends both the non-spatial open-population model of Schwarz and Arnason (1996) and the spatially explicit closed-population model of Borchers and Efford (2008). The superpopulation of animals available for detection at some time during a study is conceived as a 2-dimensional Poisson point process. Individual probabilities of birth and death follow the conventional open-population model. Movement between sampling times may be modeled with a dispersal kernel using a recursive Markovian algorithm. Observations arise from distance-dependent sampling at an array of detectors. As in the closed-population spatial model, the observed data likelihood relies on integration over the unknown animal locations; maximization of this likelihood yields estimates of the birth, death, movement and detection parameters. The models were fitted to data from a live-trapping study of brushtail possums (Trichosurus vulpecula) in New Zealand. Simulations confirmed that spatial modeling can greatly reduce the bias of capture-recapture survival estimates, and that there is a degree of robustness to misspecification of the dispersal kernel. An R package is available that includes various extensions. This article is protected by copyright. All rights reserved.

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