ArticleProceedings of the National Academy of Sciences of the United States of America2020
Spatial proximity moderates genotype uncertainty in genetic tagging studies.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. 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.
- Abundance-mediated species interactions.Ecology · 2025Article
- Modelling heterogeneity in the classification process in multi-species distribution models can improve predictive performance.Ecology and evolution · 2024Article
- Occupancy data improves parameter precision in spatial capture-recapture models.Ecology and evolution · 2022Article
- Evaluating otter reintroduction outcomes using genetic spatial capture-recapture modified for dendritic networks.Ecology and evolution · 2021Article
- Perspectives on Individual Animal Identification from Biology and Computer Vision.Integrative and comparative biology · 2021Review
- Spatial capture-recapture with random thinning for unidentified encounters.Ecology and evolution · 2021Article
- Spatial proximity moderates genotype uncertainty in genetic tagging studies.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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4 authors.
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Abstract
Accelerating declines of an increasing number of animal populations worldwide necessitate methods to reliably and efficiently estimate demographic parameters such as population density and trajectory. Standard methods for estimating demographic parameters from noninvasive genetic samples are inefficient because lower-quality samples cannot be used, and they assume individuals are identified without error. We introduce the genotype spatial partial identity model (gSPIM), which integrates a genetic classification model with a spatial population model to combine both spatial and genetic information, thus reducing genotype uncertainty and increasing the precision of demographic parameter estimates. We apply this model to data from a study of fishers (
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