Spatial Capture–Recapture Models

Show simple item record Borchers, D en Fewster, Rachel en 2017-06-07T21:38:44Z en 2016 en
dc.identifier.citation Statistical Science, 2016, 31 (2), 219 - 232 en
dc.identifier.issn 0883-4237 en
dc.identifier.uri en
dc.description.abstract 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. en
dc.language English en
dc.publisher Institute of Mathematical Statistics en
dc.relation.ispartofseries Statistical Science en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. Details obtained from en
dc.rights.uri en
dc.title Spatial Capture–Recapture Models en
dc.type Journal Article en
dc.identifier.doi 10.1214/16-STS557 en
pubs.issue 2 en
pubs.begin-page 219 en
pubs.volume 31 en
dc.description.version VoR - Version of Record en en
pubs.end-page 232 en
pubs.publication-status Published en
dc.rights.accessrights en
pubs.subtype Article en
pubs.elements-id 614182 en Science en Statistics en
dc.identifier.eissn 2168-8745 en
pubs.record-created-at-source-date 2017-06-08 en

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