ArticleEcological applications : a publication of the Ecological Society of America2022
Precision and bias of spatial capture-recapture estimates: A multi-site, multi-year Utah black bear case study.
Article in Ecological applications : a publication of the Ecological Society of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Estimating the Abundance of a Cryptic, Endangered Marsupial, Mala (Ecology and evolution · 2026Article
- First rangewide density estimate of the endemic and isolated Luangwa giraffe in Zambia.Scientific reports · 2025Article
- When enough is enough: Optimising monitoring effort for large-scale wolf population size estimation in the Italian Alps.Ecology and evolution · 2024Article
- Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture-recapture models.Movement ecology · 2024Article
- Sexual segregation results in pronounced sex-specific density gradients in the mountain ungulate, Rupicapra rupicapra.Communications biology · 2023Article
- Density estimates reveal that fragmented landscapes provide important habitat for conserving an endangered mesopredator, the spotted-tailed quoll.Scientific reports · 2022Article
- Precision and bias of spatial capture-recapture estimates: A multi-site, multi-year Utah black bear case study.Ecological applications : a publication of the Ecological Society of America · 2022Article
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Spatial capture-recapture (SCR) models are powerful analytical tools that have become the standard for estimating abundance and density of wild animal populations. When sampling populations to implement SCR, the number of unique individuals detected, total recaptures, and unique spatial relocations can be highly variable. These sample sizes influence the precision and accuracy of model parameter estimates. Testing the performance of SCR models with sparse empirical data sets typical of low-density, wide-ranging species can inform the threshold at which a more integrated modeling approach with additional data sources or additional years of monitoring may be required to achieve reliable, precise parameter estimates. Using a multi-site, multi-year Utah black bear (Ursus americanus) capture-recapture data set, we evaluated factors influencing the uncertainty of SCR structural parameter estimates, specifically density, detection, and the spatial scale parameter, sigma. We also provided some of the first SCR density estimates for Utah black bear populations, which ranged from 3.85 to 74.33 bears/100 km
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