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May 2016 Spatial Capture–Recapture Models
David Borchers, Rachel Fewster
Statist. Sci. 31(2): 219-232 (May 2016). DOI: 10.1214/16-STS557


There has been a rapid growth in spatial capture–recapture (SCR) methods in the last decade. This paper provides an overview of existing SCR models and suggestions on how they might develop in future. The core of the paper is a likelihood framework that synthesises existing SCR models. This is used to illustrate similarities and differences between models.

The key difference between conventional capture–recapture models and SCR models is that the latter include a spatial point process model for individuals’ locations and allow capture probability to depend on location. This extends the kinds of inferences that can be drawn from capture–recapture surveys, allowing them to address questions of a fundamentally spatial nature, relating to animal distribution, habitat preference, movement patterns, spatial connectivity of habitats and dependence of demographic parameters on spatial variables.


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David Borchers. Rachel Fewster. "Spatial Capture–Recapture Models." Statist. Sci. 31 (2) 219 - 232, May 2016.


Published: May 2016
First available in Project Euclid: 24 May 2016

zbMATH: 06946223
MathSciNet: MR3506101
Digital Object Identifier: 10.1214/16-STS557

Keywords: capture–recapture , competing risks , detection hazard , Poisson process , spatial modelling

Rights: Copyright © 2016 Institute of Mathematical Statistics


Vol.31 • No. 2 • May 2016
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