Spatial close‐kin mark‐recapture models applied to terrestrial species with continuous natal dispersal

Abstract Close‐kin mark–recapture (CKMR) methods use information on genetic relatedness among individuals to estimate demographic parameters. An individual's genotype can be considered a ‘recapture’ of each of its parent's genotype, and the frequency of kin‐pair matches detected in a population sample can directly inform estimates of abundance. CKMR inference procedures require analysts to define kinship probabilities in functional forms, which inevitably involve simplifying assumptions. Among others, population structure can have a strong influence on how kinship probabilities are formulated. Many terrestrial species are philopatric or face barriers to dispersal, and not accounting for dispersal limitation in kinship probabilities, can create substantial bias if sampling is also spatially structured (e.g. via harvest). We present a spatially explicit formulation of CKMR that corrects for incomplete mixing by incorporating natal dispersal distances and spatial distribution of individuals into the kinship probabilities. We used individual‐based simulations to evaluate the accuracy of abundance estimates obtained with one spatially naïve and two spatially explicit CKMR models across six scenarios with distinct spatial patterns of relative abundance and sampling probability. Estimates of abundance obtained with a CKMR model naïve to spatial structure were negatively biased when sampling was spatially biased. Incorporating patterns of natal dispersal in the kinship probabilities helped address this bias, but estimates were not always accurate depending on the model used and the scenario considered. Incorporating natal dispersal into spatially structured CKMR models can address the bias created by population structure and heterogeneous sampling but will often require additional assumptions and auxiliary data (e.g. relative abundance indices). The models shown here were designed for terrestrial species with continuous patterns of natal dispersal and high year‐to‐year site fidelity but could be extended to other species.

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Publication Details

Journal
Methods in Ecology and Evolution
Published
2025-02-13
DOI
https://doi.org/10.1111/2041-210x.14490
Citations
3
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
5.15

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article

Spatial close‐kin mark‐recapture models applied to terrestrial species with continuous natal dispersal

Anthony Sévêque, Robert C. Lonsinger, Dana J. Morin, Lisette P. Waits
3 citations
Methods in Ecology and Evolution
Wildlife Ecology and Conservation
5.15
article

Spatial close‐kin mark‐recapture models applied to terrestrial species with continuous natal dispersal

Anthony Sévêque, Robert C. Lonsinger, Dana J. Morin, Lisette P. Waits
article en
3 citations

Abstract

Abstract Close‐kin mark–recapture (CKMR) methods use information on genetic relatedness among individuals to estimate demographic parameters. An individual's genotype can be considered a ‘recapture’ of each of its parent's genotype, and the frequency of kin‐pair matches detected in a population sample can directly inform estimates of abundance. CKMR inference procedures require analysts to define kinship probabilities in functional forms, which inevitably involve simplifying assumptions. Among others, population structure can have a strong influence on how kinship probabilities are formulated. Many terrestrial species are philopatric or face barriers to dispersal, and not accounting for dispersal limitation in kinship probabilities, can create substantial bias if sampling is also spatially structured (e.g. via harvest). We present a spatially explicit formulation of CKMR that corrects for incomplete mixing by incorporating natal dispersal distances and spatial distribution of individuals into the kinship probabilities. We used individual‐based simulations to evaluate the accuracy of abundance estimates obtained with one spatially naïve and two spatially explicit CKMR models across six scenarios with distinct spatial patterns of relative abundance and sampling probability. Estimates of abundance obtained with a CKMR model naïve to spatial structure were negatively biased when sampling was spatially biased. Incorporating patterns of natal dispersal in the kinship probabilities helped address this bias, but estimates were not always accurate depending on the model used and the scenario considered. Incorporating natal dispersal into spatially structured CKMR models can address the bias created by population structure and heterogeneous sampling but will often require additional assumptions and auxiliary data (e.g. relative abundance indices). The models shown here were designed for terrestrial species with continuous patterns of natal dispersal and high year‐to‐year site fidelity but could be extended to other species.

Methods in Ecology and EvolutionVol. 16(4)
Oklahoma State University (US), United States Geological Survey (US), University of Idaho (US), Senckenberg - Leibniz Institution for Biodiversity and Earth System Research (DE), Mississippi State University (US)
U.S. Fish and Wildlife Service, National Institute of Food and Agriculture
Openalex Percentile: Top 6%
Wildlife Ecology and Conservation
5.15
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