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Wildlife habitat selection on landscapes with industrial disturbance

Published online by Cambridge University Press:  04 July 2016

BOGDAN CRISTESCU ,
GORDON B. STENHOUSE ,
MARC SYMBALUK ,
SCOTT E. NIELSEN  and
MARK S. BOYCE
BOGDAN CRISTESCU*
Affiliation:
Grizzly Bear Program, Foothills Research Institute, Hinton, Alberta, Canada Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
GORDON B. STENHOUSE
Affiliation:
Grizzly Bear Program, Foothills Research Institute, Hinton, Alberta, Canada
MARC SYMBALUK
Affiliation:
Environment Department, Teck Coal Ltd, Canada
SCOTT E. NIELSEN
Affiliation:
Department of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada
MARK S. BOYCE
Affiliation:
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
*
*Correspondence: Bogdan Cristescu, e-mail: [email protected]
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Summary

Technological advancements in remote sensing and telemetry provide opportunities for assessing the effects of expanding extractive industries on animal populations. Here, we illustrate the applicability of resource selection functions (RSFs) for modelling wildlife habitat selection on industrially-disturbed landscapes. We used grizzly bears (Ursus arctos) from a threatened population in Canada and surface mining as a case study. RSF predictions based on GPS radiocollared bears (nduring mining = 7; npost mining = 9) showed that males and solitary females selected areas primarily outside mineral surface leases (MSLs) during active mining, and conversely inside MSLs after mine closure. However, females with cubs selected areas within compared to outside MSLs irrespective of mining activity. Individual variability was pronounced, although some environmental- and human-related variables were consistent across reproductive classes. For males and solitary females, regional-scale RSFs yielded comparable results to site-specific models, whereas for females with cubs, modelling the two scales produced divergent results. While mine reclamation may afford opportunities for bear persistence, managing public access will likely decrease the risk of human-caused bear mortality. RSFs are powerful tools that merit widespread use in quantitative and visual investigations of wildlife habitat selection on industrially-modified landscapes, using Geographic Information System layers that precisely characterize site-specific conditions.

Keywords

environmental impact assessmentgrizzly bearindividual variationminingresource selection functionRSFscaleUrsus arctos
Type
Papers
Information
Environmental Conservation , Volume 43 , Issue 4 , December 2016 , pp. 327 - 336
Copyright
Copyright © Foundation for Environmental Conservation 2016 

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Figure S1

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Table S1

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