ReviewEcology and evolution2022
A review of spatial capture-recapture: Ecological insights, limitations, and prospects.
Review in Ecology and evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
14 citing papers in PubMed.
- Integrating Multiple Data Sources Improves Abundance Estimation in Spatial Capture-Recapture Models.Ecology and evolution · 2026Article
- Article
- Individual encounter data of six African carnivore species optimized for multi-species density estimation.Scientific data · 2026Article
- Multidisciplinary monitoring and stakeholder engagement support large carnivore restoration in human-dominated landscape.Ecological applications : a publication of the Ecological Society of America · 2025Article
- Environmental variability across space and time drives the recolonization pattern of a historically persecuted large carnivore.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Correction: Beyond words: From jaguar population trends to conservation and public policy in Mexico.PloS one · 2025Article
- When enough is enough: Optimising monitoring effort for large-scale wolf population size estimation in the Italian Alps.Ecology and evolution · 2024Article
- Estimating distribution and abundance of wide-ranging species with integrated spatial models: Opportunities revealed by the first wolf assessment in south-central Italy.Ecology and evolution · 2024Article
- Shining a light on elusive lynx: Density estimation of three Eurasian lynx populations in Ukraine and Belarus.Ecology and evolution · 2023Article
- Sexual segregation results in pronounced sex-specific density gradients in the mountain ungulate, Rupicapra rupicapra.Communications biology · 2023Article
- The first comprehensive population size estimations for the highly endangered largest diving beetle Dytiscus latissimus in Europe.Scientific reports · 2023Article
- Spatial variation in red deer density in a transboundary forest ecosystem.Scientific reports · 2023Article
- Photo-identification shows the spatio-temporal distribution of two sea turtle species in a Brazilian developmental foraging ground.Marine biology · 2023Article
- A review of spatial capture-recapture: Ecological insights, limitations, and prospects.Ecology and evolution · 2022Review
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
First described by Efford (2004), spatial capture-recapture (SCR) has become a popular tool in ecology. Like traditional capture-recapture, SCR methods account for imperfect detection when estimating ecological parameters. In addition, SCR methods use the information inherent in the spatial configuration of individual detections, thereby allowing spatially explicit estimation of population parameters, such as abundance, survival, and recruitment. Paired with advances in noninvasive survey methods, SCR has been applied to a wide range of species across different habitats, allowing for population- and landscape-level inferences with direct consequences for conservation and management. I conduct a literature review of SCR studies published since the first description of the method and provide an overview of their scope in terms of the ecological questions answered with this tool, taxonomic groups targeted, geography, spatio-temporal extent of analyses, and data collection methods. In addition, I review approaches for analytical implementation and provide an overview of parameters targeted by SCR studies and conclude with current limitations and future directions in SCR methods.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.