Spatio‐temporal co‐occurrence of cougars ( Felis concolor), wolves ( Canis lupus) and their prey during winter: a comparison of two analytical methods

Abstract Aims To examine the spatio‐temporal co‐occurrence of cougars ( Felis concolor ), wolves ( Canis lupus ), and their prey during winter using monthly (November–March) species–environment relationship models. In addition, to contrast predictions across two methods: logistic regression and Geog...

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Bibliographic Details
Published in:Journal of Biogeography
Main Authors: Alexander, S. M., Logan, T. B., Paquet, P. C.
Format: Article in Journal/Newspaper
Language:English
Published: Wiley 2006
Subjects:
Online Access:http://dx.doi.org/10.1111/j.1365-2699.2006.01564.x
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.1365-2699.2006.01564.x
https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2699.2006.01564.x
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Summary:Abstract Aims To examine the spatio‐temporal co‐occurrence of cougars ( Felis concolor ), wolves ( Canis lupus ), and their prey during winter using monthly (November–March) species–environment relationship models. In addition, to contrast predictions across two methods: logistic regression and Geographic Information System (GIS) image correlation. Location The eastern front ranges of the Canadian Rocky Mountains (south‐central Alberta), approximately 100 km west of Calgary, including portions of Banff National Park and Kananaskis Country. Methods Snow‐tracking data were collected simultaneously for cougars, wolves, elk ( Cervus elaphus ), and deer ( Odocoileus virginianus and O. hemionus ) between November and March, 1997–2000. Track data were synthesized in a GIS. Logistic regression and Akaike's information criterion (AIC) were used to select optimal environmental relationship models for each species. We first examined co‐occurrence by iteratively using each species as a dependent variable (presence/absence) in a logistic regression analysis and using all other species track‐density estimates as independent variables. We built predictive surfaces in a GIS using the exponent form of the logistic regression models, and assessed model accuracy with a receiver operating characteristic curve. We then re‐examined co‐occurrence using pairwise correlations of species probability surfaces by month. The correlation results were compared with logistic regression results to illuminate mechanisms of co‐occurrence and to investigate predictive consistency across the two methods. Results Cougars showed a trend in distribution from higher elevation and less rugged terrain in December, to lower elevation and more rugged terrain in March. This trend differed from that for wolves, which showed a more stable affinity for low elevation and less rugged valley bottoms across all months. The logistic regression models indicated variable positive and negative associations of cougars with wolves by month, and changes in prey ...