Grizzly Bear Density in Glacier National Park, Montana

Abstract

: We present the first rigorous estimate of grizzly bear (Ursus arctos) population density and distribution in and around Glacier National Park (GNP), Montana, USA. We used genetic analysis to identify individual bears from hair samples collected via 2 concurrent sampling methods: 1) systematically distributed, baited, barbed‐wire hair traps and 2) unbaited bear rub trees found along trails. We used Huggins closed mixture models in Program MARK to estimate total population size and developed a method to account for heterogeneity caused by unequal access to rub trees. We corrected our estimate for lack of geographic closure using a new method that utilizes information from radiocollared bears and the distribution of bears captured with DNA sampling. Adjusted for closure, the average number of grizzly bears in our study area was 240.7 (95% CI = 202–303) in 1998 and 240.6 (95% CI = 205–304) in 2000. Average grizzly bear density was 30 bears/1,000 km2, with 2.4 times more bears detected per hair trap inside than outside GNP. We provide baseline information important for managing one of the few remaining populations of grizzlies in the contiguous United States.

Demography and Genetic Structure of a Recovering Grizzly Bear Population

“…We collected hair only from the barbed wire and passed a flame under each barb after collection to prevent contamination between sessions. We compiled capture, telemetry, mortality, age, and past DNA detection data for 766 grizzly bears handled for research or management or identified during other hair sampling studies (Kendall et al 2008) in the NCDE during . Of the bears for which tissue samples were available, 426 were successfully genotyped at !7 loci for individual identification.…”

“…Genetic distance to the Prophet River (P), British Columbia, grizzly bear population 1,150 km north of the NCDE was included for comparison with within-NCDE population distances. single sample, 2) pairs of individuals that differed at only 1 or 2 loci (1-and 2-mismatch pairs), 3) pairs of individuals that differed at 3 loci when those differences were consistent with allelic dropout (i.e., homozygous), and 4) individuals with samples geographically separated by large distances (Paetkau 2003, Roon et al 2005, Kendall et al 2008. We further minimized the risk of undetected genotyping error by replicating genetic data for all 17 markers (including gender) in !2 samples per individual or by repeating the analysis of all 17 markers in cases where just one sample was assigned to an individual.…”

“…Estimating Abundance, Mortality, Distribution, and Genetic Population Structure We developed an approach to abundance estimation that combined data from our 3 sampling methods (hair trap, bear rub, and physical capture) to construct individual bear encounter histories for use in Huggins-Pledger closed mark-recapture models (Huggins 1991, Pledger 2000, Boulanger et al 2008a, Kendall et al 2008). We performed all mark-recapture analyses in Program MARK Pledger model updated May 2007).…”

“…Factors that contributed to the precision of our estimate (CV ¼ 3.8%) included the use of multiple sampling methods, the development of advanced mark-recapture modeling techniques (Boulanger et al 2008a), and the large scale of our study. Combining detections from multiple data sources into single encounter histories yielded robust estimates with higher precision than a single-source approach (Boulanger et al 2008a, Kendall et al 2008. Mark-recapture models that can incorporate individual, group, and temporal covariates increase precision or reduce bias by more effectively modeling the heterogeneity in capture probabilities that is pervasive in wild populations (Huggins 1991, Pledger 2000, Boulanger et al 2008a.…”

Linking noninvasive genetic sampling and traditional monitoring to aid management of a trans‐border carnivore population

“…For large administrative units and for wide-ranging species, monitoring can represent a substantial challenge in terms of both resources and scientific methodology. Many management authorities rely on indirect methods, such as the collection of observation reports (e.g., Kindberg et al 2009) and harvest data (e.g., Cattadori et al 1999), as well as noninvasive field methods, including sign transects (Beier and Cunningham 1996), scent stations (e.g., Diefenbach et al 1994), camera traps (e.g., Karanth 1995) and noninvasive genetic sampling (NGS, e.g., Bellemain et al 2005, Kendall et al 2008. The latter entails the extraction of genetic material from hair, scat, and other sources of DNA, and has been implemented in numerous projects involving many species (review in Waits and Paetkau 2005).…”