Genetic tagging of free-ranging black and brown bears

Identification of individuals in a free-ranging animal population is potentially hampered by a lack of distinguishing features (e.g., scars, unique color patterns), poor visibility (e.g., densely forested environments), cost and invasiveness of physical capture, and mark loss. Advances in DNA-analys...

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Bibliographic Details
Main Authors: Woods, John G., Paetkau, David, Lewis, David, McLellan, Bruce N., Proctor, Michael, Strobeck, Curtis
Format: Article in Journal/Newspaper
Language:English
Published: 1999
Subjects:
DNA
Online Access:https://espace.library.uq.edu.au/view/UQ:9d631d8
Description
Summary:Identification of individuals in a free-ranging animal population is potentially hampered by a lack of distinguishing features (e.g., scars, unique color patterns), poor visibility (e.g., densely forested environments), cost and invasiveness of physical capture, and mark loss. Advances in DNA-analysis technology offer alternative methods of individual identification that may overcome several of these problems. We investigated the genetic variability of American black bears (Ursus americanus) and brown (grizzly) bears (Ursus arctos) in the Columbia River basin of British Columbia, Canada, and developed a method to obtain genetic samples from free-ranging bears. We established the background genetic variability using microsatellite genotyping at 9 loci using tissue and blood samples from captured bears. In 3 field trials, we tested methods to obtain hair from free-ranging bears. Although all methods collected hair suitable for DNA analysis, the barbed-wire enclosure hair-trap was superior. We extracted DNA from hair roots and identified sample species with a species-specific mitochondrial DNA (mtDNA) test and sample sex from a Y-chromosome test. Using 6 microsatellite loci from nuclear DNA (nDNA), we screened all hair samples for individual identity and developed match probability functions based on scenarios of random sampling (P(random)), the likely presence of parent-offspring groupings in the samples (P(par-offs)), and the likely presence of siblings in the samples (P(sib)). We applied the P(sib) to each hair sample (match criteria at P(sib)