4.3 Article

Estimating abundance of mountain lions from unstructured spatial sampling

期刊

JOURNAL OF WILDLIFE MANAGEMENT
卷 76, 期 8, 页码 1551-1561

出版社

WILEY
DOI: 10.1002/jwmg.412

关键词

Bayesian analysis; cougars; genetic sampling; Montana; Puma concolor; snow tracking; spatial capture-recapture; spatial models

资金

  1. Montana and Montana Fish, Wildlife and Parks (FWP) Federal Aid in Wildlife Restoration grants

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Mountain lions (Puma concolor) are often difficult to monitor because of their low capture probabilities, extensive movements, and large territories. Methods for estimating the abundance of this species are needed to assess population status, determine harvest levels, evaluate the impacts of management actions on populations, and derive conservation and management strategies. Traditional markrecapture methods do not explicitly account for differences in individual capture probabilities due to the spatial distribution of individuals in relation to survey effort (or trap locations). However, recent advances in the analysis of capturerecapture data have produced methods estimating abundance and density of animals from spatially explicit capturerecapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capturerecapture models to estimate density and abundance of mountain lions in western Montana. Volunteers and state agency personnel collected mountain lion DNA samples in portions of the Blackfoot drainage (7,908?km2) in west-central Montana using 2 methods: snow back-tracking mountain lion tracks to collect hair samples and biopsy darting treed mountain lions to obtain tissue samples. Overall, we recorded 72 individual capture events, including captures both with and without tissue sample collection and hair samples resulting in the identification of 50 individual mountain lions (30 females, 19 males, and 1 unknown sex individual). We estimated lion densities from 8 models containing effects of distance, sex, and survey effort on detection probability. Our population density estimates ranged from a minimum of 3.7 mountain lions/100?km2 (95% CI 2.35.7) under the distance only model (including only an effect of distance on detection probability) to 6.7 (95% CI 3.111.0) under the full model (including effects of distance, sex, survey effort, and distance?x?sex on detection probability). These numbers translate to a total estimate of 293 mountain lions (95% CI 182451) to 529 (95% CI 245870) within the Blackfoot drainage. Results from the distance model are similar to previous estimates of 3.6 mountain lions/100?km2 for the study area; however, results from all other models indicated greater numbers of mountain lions. Our results indicate that unstructured spatial sampling combined with spatial capturerecapture analysis can be an effective method for estimating large carnivore densities. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.

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