Spatial Capture–Recapture: A Promising Method for Analyzing Data Collected Using Artificial Cover Objects

Sutherland, Chris; Muñóz, David; Miller, David A. W.; Grant, Evan H. Campbell

doi:10.1655/herpetologica-d-15-00027

Cited by 42 publications

(46 citation statements)

References 42 publications

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“…We defined a state-space, that is, the area encompassing all potential activity centers of the observed individuals, by building a grid that buffered outermost camera trap locations by 15 km (corresponding to at least 2σ; Royle et al, 2014) with a resolution of 1.5 km (or pixels of area 2.25 km 2 ). We fitted SCR models in the maximum likelihood framework using the R package oSCR (Sutherland, Muñoz, Miller, & Grant, 2016;Sutherland, Royle, & Linden, 2019).…”

Section: Doubs Inmentioning

confidence: 99%

Spatial density estimates of Eurasian lynx (Lynx lynx) in the French Jura and Vosges Mountains

Giménez

Gatti

Duchamp

et al. 2019

Ecology and Evolution

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Obtaining estimates of animal population density is a key step in providing sound conservation and management strategies for wildlife. For many large carnivores however, estimating density is difficult because these species are elusive and wide‐ranging. Here, we focus on providing the first density estimates of the Eurasian lynx (Lynx lynx) in the French Jura and Vosges mountains. We sampled a total of 413 camera trapping sites (with two cameras per site) between January 2011 and April 2016 in seven study areas across seven counties of the French Jura and Vosges mountains. We obtained 592 lynx detections over 19,035 trap days in the Jura mountains and 0 detection over 6,804 trap days in the Vosges mountains. Based on coat patterns, we identified a total number of 92 unique individuals from photographs, including 16 females, 13 males, and 63 individuals of unknown sex. Using spatial capture–recapture (SCR) models, we estimated abundance in the study areas between 5 (SE = 0.1) and 29 (0.2) lynx and density between 0.24 (SE = 0.02) and 0.91 (SE = 0.03) lynx per 100 km2. We also provide a comparison with nonspatial density estimates and discuss the observed discrepancies. Our study is yet another example of the advantage of combining SCR methods and noninvasive sampling techniques to estimate density for elusive and wide‐ranging species, like large carnivores. While the estimated densities in the French Jura mountains are comparable to other lynx populations in Europe, the fact that we detected no lynx in the Vosges mountains is alarming. Connectivity should be encouraged between the French Jura mountains, the Vosges mountains, and the Palatinate Forest in Germany where a reintroduction program is currently ongoing. Our density estimates will help in setting a baseline conservation status for the lynx population in France.

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Section: Doubs Inmentioning

confidence: 99%

Spatial density estimates of Eurasian lynx (Lynx lynx) in the French Jura and Vosges Mountains

Giménez

Gatti

Duchamp

et al. 2019

Ecology and Evolution

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“…Therefore, we would predict σ to be larger for the lead-backed morph in autumn and larger for striped morphs in the spring (prediction 4; Table 1). For location, we used the coordinate of the cover board under which a salamander was found (Muñoz et al, in press;Sutherland, Muñoz, Miller, & Grant, 2016). We ran the spatial capture-recapture model separately for each season, using program R and package "runjags" to call program JAGS (Denwood, 2016;Plummer, 2003;R Core Team, 2014…”

Section: Surface Use and Timingmentioning

confidence: 99%

Evaluating within‐population variability in behavior and demography for the adaptive potential of a dispersal‐limited species to climate change

Muñóz

Hesed

Grant

et al. 2016

Ecology and Evolution

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Multiple pathways exist for species to respond to changing climates. However, responses of dispersal‐limited species will be more strongly tied to ability to adapt within existing populations as rates of environmental change will likely exceed movement rates. Here, we assess adaptive capacity in Plethodon cinereus, a dispersal‐limited woodland salamander. We quantify plasticity in behavior and variation in demography to observed variation in environmental variables over a 5‐year period. We found strong evidence that temperature and rainfall influence P. cinereus surface presence, indicating changes in climate are likely to affect seasonal activity patterns. We also found that warmer summer temperatures reduced individual growth rates into the autumn, which is likely to have negative demographic consequences. Reduced growth rates may delay reproductive maturity and lead to reductions in size‐specific fecundity, potentially reducing population‐level persistence. To better understand within‐population variability in responses, we examined differences between two common color morphs. Previous evidence suggests that the color polymorphism may be linked to physiological differences in heat and moisture tolerance. We found only moderate support for morph‐specific differences for the relationship between individual growth and temperature. Measuring environmental sensitivity to climatic variability is the first step in predicting species' responses to climate change. Our results suggest phenological shifts and changes in growth rates are likely responses under scenarios where further warming occurs, and we discuss possible adaptive strategies for resulting selective pressures.

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“…For example, a camera trapping study might take place in multiple reserves or use multiple camera trap grids spaced far apart. Or sampling for amphibians using artificial cover objects (ACOs) involves replicated ACO arrays in different habitats (Sutherland et al 2016, Schmidt et al 2017). Replication might occur over time as well -sampling in different seasons or years.…”

Section: Multi-session Structurementioning

confidence: 99%

“…Here we outline a typical oSCR analysis and pair the workflow with an example using redbacked salamander (RBS) data (Sutherland et al 2016). A complete annotated workflow is provided in the Supplementary vignette Appendix 1, and here we highlight the data objects and functions required to conduct an SCR analysis in oSCR (Table 1).…”

Section: Describing the Oscr Workflowmentioning

confidence: 99%

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

2019

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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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Spatial Capture–Recapture: A Promising Method for Analyzing Data Collected Using Artificial Cover Objects

Cited by 42 publications

References 42 publications

Spatial density estimates of Eurasian lynx (Lynx lynx) in the French Jura and Vosges Mountains

Spatial density estimates of Eurasian lynx (Lynx lynx) in the French Jura and Vosges Mountains

Evaluating within‐population variability in behavior and demography for the adaptive potential of a dispersal‐limited species to climate change

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

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