Sub-Sampling Genetic Data to Estimate Black Bear Population Size: A Case Study

Costs for genetic analysis of hair samples collected for individual identification of bears average approximately US$50 [2004] per sample. This can easily exceed budgetary allowances for large-scale studies or studies of high-density bear populations. We used 2 genetic datasets from 2 areas in the s...

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Détails bibliographiques
Publié dans:Ursus. - International Association for Bear Research and Management, 1998. - 18(2007), 2, Seite 179-188
Auteur principal: Tredick, Catherine A. (Auteur)
Autres auteurs: Vaughan, Michael R., Stauffer, Dean F., Simek, Stephanie L., Eason, Thomas
Format: Article en ligne
Langue:English
Publié: 2007
Accès à la collection:Ursus
Sujets:American black bear budget constraints noninvasive genetic sampling population estimates sub-sampling Ursus americanus Social sciences Information science Biological sciences Mathematics
Description
Résumé:Costs for genetic analysis of hair samples collected for individual identification of bears average approximately US$50 [2004] per sample. This can easily exceed budgetary allowances for large-scale studies or studies of high-density bear populations. We used 2 genetic datasets from 2 areas in the southeastern United States to explore how reducing costs of analysis by sub-sampling affected precision and accuracy of resulting population estimates. We used several sub-sampling scenarios to create subsets of the full datasets and compared summary statistics, population estimates, and precision of estimates generated from these subsets to estimates generated from the complete datasets. Our results suggested that bias and precision of estimates improved as the proportion of total samples used increased, and heterogeneity models (e.g., $M_{h[\text{CHAO}]}$ ) were more robust to reduced sample sizes than other models (e.g., behavior models). We recommend that only high-quality samples (>5 hair follicles) be used when budgets are constrained, and efforts should be made to maximize capture and recapture rates in the field.
ISSN:19385439