The University of St Andrews

Research@StAndrews:FullText >
University of St Andrews Research >
University of St Andrews Research >
University of St Andrews Research >

Please use this identifier to cite or link to this item:
This item has been viewed 246 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
Borchers_Non_tech_Overview_secr_JORN_2010.pdf451.12 kBAdobe PDFView/Open
Title: A non-technical overview of spatially explicit capture-recapture models
Authors: Borchers, David
Keywords: Spatially explicit capture-recapture
Spatial sampling
Measurement error
Capture function
Plot sampling
Distance sampling
HA Statistics
Issue Date: Feb-2012
Citation: Borchers , D 2012 , ' A non-technical overview of spatially explicit capture-recapture models ' Journal of Ornithology , vol 152 , no. 2 , pp. S435-S444 . , 10.1007/s10336-010-0583-z
Abstract: Most capture-recapture studies are inherently spatial in nature, with capture probabilities depending on the location of traps relative to animals. The spatial component of the studies has until recently, however, not been incorporated in statistical capture-recapture models. This paper reviews capture-recapture models that do include an explicit spatial component. This is done in a non-technical way, omitting much of the algebraic detail and focussing on the model formulation rather than on the estimation methods (which include inverse prediction, maximum likelihood and Bayesian methods). One can view spatially explicit capture-recapture (SECR) models as an endpoint of a series of spatial sampling models, starting with circular plot survey models and moving through conventional distance sampling models, with and without measurement errors, through mark-recapture distance sampling (MRDS) models. This paper attempts a synthesis of these models in what I hope is a style accessible to non-specialists, placing SECR models in the context of other spatial sampling models.
Version: Postprint
Status: Peer reviewed
ISSN: 2193-7192
Type: Journal article
Rights: This is the author's accepted version of this article. The original publication is available at
Appears in Collections:Centre for Higher Education Research (CHER) Research
Scottish Oceans Institute Research
Centre for Research into Ecological & Environmental Modelling (CREEM) Research
Mathematics & Statistics Research
University of St Andrews Research

This item is protected by original copyright

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


DSpace Software Copyright © 2002-2012  Duraspace - Feedback
For help contact: | Copyright for this page belongs to St Andrews University Library | Terms and Conditions (Cookies)