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      Functional response of wolves to human development across boreal North America

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          Abstract

          Aim

          The influence of humans on large carnivores, including wolves, is a worldwide conservation concern. In addition, human‐caused changes in carnivore density and distribution might have impacts on prey and, indirectly, on vegetation. We therefore tested wolf responses to infrastructure related to natural resource development (i.e., human footprint).

          Location

          Our study provides one of the most extensive assessments of how predators like wolves select habitat in response to various degrees of footprint across boreal ecosystems encompassing over a million square kilometers of Canada.

          Methods

          We deployed GPS‐collars on 172 wolves, monitored movements and used a generalized functional response (GFR) model of resource selection. A functional response in habitat selection occurs when selection varies as a function of the availability of that habitat. GFRs can clarify how human‐induced habitat changes are influencing wildlife across large, diverse landscapes.

          Results

          Wolves displayed a functional response to footprint. Wolves were more likely to select forest harvest cutblocks in regions with higher cutblock density (i.e., a positive functional response to high‐quality habitats for ungulate prey) and to select for higher road density in regions where road density was high (i.e., a positive functional response to human‐created travel routes). Wolves were more likely to use cutblocks in habitats with low road densities, and more likely to use roads in habitats with low cutblock densities, except in winter when wolves were more likely to use roads regardless of cutblock density.

          Main conclusions

          These interactions suggest that wolves trade‐off among human‐impacted habitats, and adaptively switch from using roads to facilitate movement (while also risking encounters with humans), to using cutblocks that may have higher ungulate densities. We recommend that conservation managers consider the contextual and interacting effects of footprints when assessing impacts on carnivores. These effects likely have indirect impacts on ecosystems too, including on prey species.

          Abstract

          We deployed GPS‐collars on 172 wolves and evaluated resource selection across boreal ecosystems encompassing over a million square kilometers of North America. Wolves traded‐off among human impacted habitats, and more specifically adaptively switch from using roads to facilitate movement (while also risking encounters with humans), to using cutblocks that may have higher ungulate densities. We therefore recommend that conservation managers consider the contextual and interacting effects of human footprints when assessing impacts on carnivores and on their prey.

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          Most cited references50

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          Predation, apparent competition, and the structure of prey communities

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            Application of random effects to the study of resource selection by animals.

            1. Resource selection estimated by logistic regression is used increasingly in studies to identify critical resources for animal populations and to predict species occurrence. 2. Most frequently, individual animals are monitored and pooled to estimate population-level effects without regard to group or individual-level variation. Pooling assumes that both observations and their errors are independent, and resource selection is constant given individual variation in resource availability. 3. Although researchers have identified ways to minimize autocorrelation, variation between individuals caused by differences in selection or available resources, including functional responses in resource selection, have not been well addressed. 4. Here we review random-effects models and their application to resource selection modelling to overcome these common limitations. We present a simple case study of an analysis of resource selection by grizzly bears in the foothills of the Canadian Rocky Mountains with and without random effects. 5. Both categorical and continuous variables in the grizzly bear model differed in interpretation, both in statistical significance and coefficient sign, depending on how a random effect was included. We used a simulation approach to clarify the application of random effects under three common situations for telemetry studies: (a) discrepancies in sample sizes among individuals; (b) differences among individuals in selection where availability is constant; and (c) differences in availability with and without a functional response in resource selection. 6. We found that random intercepts accounted for unbalanced sample designs, and models with random intercepts and coefficients improved model fit given the variation in selection among individuals and functional responses in selection. Our empirical example and simulations demonstrate how including random effects in resource selection models can aid interpretation and address difficult assumptions limiting their generality. This approach will allow researchers to appropriately estimate marginal (population) and conditional (individual) responses, and account for complex grouping, unbalanced sample designs and autocorrelation.
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              FUNCTIONAL RESPONSES IN HABITAT USE: AVAILABILITY INFLUENCES RELATIVE USE IN TRADE-OFF SITUATIONS

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                Author and article information

                Contributors
                mmusiani@ucalgary.ca
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                30 August 2019
                September 2019
                : 9
                : 18 ( doiID: 10.1002/ece3.v9.18 )
                : 10801-10815
                Affiliations
                [ 1 ] Forest Analysis and Inventory Branch Ministry of Forests, Lands, Natural Resource Operations and Rural Development Government of British Columbia Victoria BC Canada
                [ 2 ] Science and Technology Branch of Environment and Climate Change Canada Ottawa ON Canada
                [ 3 ] Wildlife Biology Program Department of Ecosystem and Conservation Sciences W.A. Franke College of Forestry and Conservation University of Montana Missoula MT USA
                [ 4 ] Department of Biological Sciences University of Alberta Edmonton AB Canada
                [ 5 ] Department of Biology Centre d'étude de la forêt Université Laval Québec QC Canada
                [ 6 ] Department of Integrated Biology University of Guelph Guelph ON Canada
                [ 7 ] Manaaki Whenua Landcare Research Lincoln New Zealand
                [ 8 ] Department of Biology University of Saskatchewan Saskatoon SK Canada
                [ 9 ] Department of Geography University of Victoria Victoria BC Canada
                [ 10 ] Wildlife Research and Monitoring Section Ministry of Natural Resources and Forestry Trent University Peterborough ON Canada
                [ 11 ] Department of Renewable Resources University of Alberta c/o Yukon Research Centre Whitehorse YT Canada
                [ 12 ] Transmission Line and Civil Construction Manitoba Hydro Winnipeg MB Canada
                [ 13 ] Department of Biological Sciences Faculty of Science University of Calgary Calgary AB Canada
                Author notes
                [*] [* ] Correspondence

                Marco Musiani, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada.

                Email: mmusiani@ 123456ucalgary.ca

                Author information
                https://orcid.org/0000-0002-2149-2492
                https://orcid.org/0000-0002-6097-5841
                Article
                ECE35600
                10.1002/ece3.5600
                6787805
                31624583
                4cdfaafb-71cd-4cef-ba39-87e085f8122f
                © 2019 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 11 December 2018
                : 29 July 2019
                : 30 July 2019
                Page count
                Figures: 7, Tables: 3, Pages: 15, Words: 10076
                Funding
                Funded by: Alberta Innovates–Technology Futures
                Funded by: Alberta Conservation Association , open-funder-registry 10.13039/100007583;
                Funded by: Alberta Outfitters Association
                Funded by: Wildsheep Foundation Alberta
                Funded by: Safari Club International Northern Alberta Chapter , open-funder-registry 10.13039/100009354;
                Funded by: Alberta Fish and Game Association
                Funded by: Chaire de Recherche Industrielle
                Funded by: CRSNG‐Université Laval en Sylviculture et Faune
                Funded by: Parks Canada
                Funded by: University of Montana
                Funded by: Natural Sciences and Engineering Research Council of Canada , open-funder-registry 10.13039/501100000038;
                Award ID: 261091‐02
                Funded by: National Aeronautics and Space Administration , open-funder-registry 10.13039/100000104;
                Award ID: NNX15AW71A
                Categories
                Original Research
                Original Research
                Custom metadata
                2.0
                September 2019
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.0 mode:remove_FC converted:11.10.2019

                Evolutionary Biology
                boreal forest,ecosystem conservation,forestry,functional response,habitat selection,roads,trade‐offs,wolves

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