Title: Estimating abundance of mountain lions from unstructured spatial sampling
Author: Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; McKelvey, Kevin S.
Source: The Journal of Wildlife Management. doi: 10.1002/jwmg.412.
Publication Series: Journal/Magazine Article (JRNL)
Description: 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 mark-recapture 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 capture-recapture data have produced methods estimating abundance and density of animals from spatially explicit capture-recapture data that account for heterogeneity in capture probabilities due to the spatial organization of individuals and traps. We adapt recently developed spatial capture-recapture 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 westcentral 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).
Keywords: Bayesian analysis, cougars, genetic sampling, Montana, Puma concolor, snow tracking, spatial capture-recapture, spatial models
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
XML: View XML
Russell, Robin E.; Royle, J. Andrew; Desimone, Richard; Schwartz, Michael K.; Edwards, Victoria L.; Pilgrim, Kristy P.; McKelvey, Kevin S. 2012. Estimating abundance of mountain lions from unstructured spatial sampling. The Journal of Wildlife Management. doi: 10.1002/jwmg.412.
Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility