A quantitative approach to conservation planning: using resource selection functions to map the distribution of mountain caribou at multiple spatial scales

• Published in: Journal of Applied Ecology
• Main Authors: Johnson, Chris J., Seip, Dale R., Boyce, Mark S.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2004
• Subjects: Canada; British Columbia; Caribou Range; Rangifer tarandus
• Online Access: http://dx.doi.org/10.1111/j.0021-8901.2004.00899.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fj.0021-8901.2004.00899.x; https://besjournals.onlinelibrary.wiley.com/doi/pdf/10.1111/j.0021-8901.2004.00899.x

Summary Visualizing the distribution of rare or threatened species is necessary for effective implementation of conservation initiatives. Generalized linear models and geographical information systems (GIS) are now powerful tools for conservation planning, but issues of data availability, scale and model extrapolation complicate some applications. Mountain caribou are an endangered ecotype of woodland caribou Rangifer tarandus caribou that occurs across central and southern British Columbia, Canada. Currently, conservation professionals use coarse small‐scale maps of important habitats to manage forest harvesting and human access across the northern extent of mountain caribou range. These maps were produced before the advent of readily available digital spatial information and are based on expert opinion and limited empirical data. With the purpose of refining existing maps, we used survey results, radio‐telemetry locations and GIS data to construct resource selection functions (RSF) that quantified the habitat affinities and predicted the relative probability of occurrence of mountain caribou at two spatial scales. At the scale of the patch, the most parsimonious RSF model consisted of covariates for vegetation and aptly predicted the occurrence of caribou across low‐ to mid‐elevation habitats, but performed poorly across steep alpine terrain. At the landscape scale, a model containing Gaussian terms for elevation and slope was effective at predicting the broader distribution of caribou. We produced a map consisting of the product of the relative probabilities of the patch and landscape RSF. The final map represented the relative probability of occurrence of caribou in vegetative patches weighted by the relative probability of occurrence across the larger study area. We found strong agreement between current definitions of important caribou habitats developed from expert opinion and RSF‐based maps generated from empirical data. Synthesis and applications . Both expert opinion and RSF‐based approaches offer ...