oSCR: a spatial capture–recapture R package for inference about spatial ecological processes

Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture–recapture methods related to heterogeneity in detectabililty, and the emergence of new technologies (e.g. came...

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Vydané v:Ecography (Copenhagen) Ročník 42; číslo 9; s. 1459 - 1469
Hlavní autori: Sutherland, Chris, Royle, J. Andrew, Linden, Daniel W.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford, UK Blackwell Publishing Ltd 01.09.2019
John Wiley & Sons, Inc
Predmet:
Accessibility
Animal populations
animals
cameras
Capture-recapture studies
capture‐recapture
computer software
density
Ecological monitoring
Ecology
Genetics
Heterogeneity
Landscape
Landscape ecology
Mathematical models
New technology
Population ecology
Population studies
SCR
SECR
Spatial data
spatial ecology
Statistical analysis
Statistical models
Workflow
ISSN:0906-7590, 1600-0587
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Shrnutí:Spatial capture–recapture (SCR) methods have become widely applied in ecology. The immediate adoption of SCR is due to the fact that it resolves some major criticisms of traditional capture–recapture methods related to heterogeneity in detectabililty, and the emergence of new technologies (e.g. camera traps, non‐invasive genetics) that have vastly improved our ability to collection spatially explicit observation data on individuals. However, the utility of SCR methods reaches far beyond simply convenience and data availability. SCR presents a formal statistical framework that can be used to test explicit hypotheses about core elements of population and landscape ecology, and has profound implications for how we study animal populations. In this software note, we describe the technical basis and analytical workflow of oSCR, an R package for analyzing spatial encounter history data using a multi‐session sex‐structured likelihood. The impetus for developing oSCR was to create an accessible and transparent analysis tool that allows users to conveniently and intuitively formulate statistical models that map directly to fundamental processes of interest in spatial population ecology (e.g. space use, resource selection, density and connectivity). We have placed an emphasis on creating a transparent and accessible code base that is coupled with a logical workflow that we hope stimulates active participation in further technical developments.
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ISSN:0906-7590
1600-0587
DOI:10.1111/ecog.04551