Habitat selection is a process that spans space, time and individual life histories. Ecological analyses of animal distributions and preferences are most accurate when they account for inherent dynamics of the habitat selection process. Strong territoriality can constrain perception of habitat availability by individual animals or groups attempting to colonize or establish new territory. Because habitat selection is a function of habitat availability, broad-scale changes in habitat availability or occupancy can drive density-dependent habitat functional responses. We investigated density-dependent habitat selection over a 19-year period of grey wolf (Canis lupus) recovery in Michigan, USA, using a generalized linear mixed model framework to develop a resource selection probability function (RSPF) with habitat coefficients conditioned on random effects for wolf packs and random year intercepts. In addition, we allowed habitat coefficients to vary as interactions with increasing wolf density over space and time. Results indicated that pack presence was driven by factors representing topography, human development, winter prey availability, forest structure, roads, streams and snow. Importantly, responses to many of these predictors were density-dependent. Spatio-temporal dynamics and population changes can cause considerable variation in wildlife–habitat relationships, possibly confounding interpretation of conventional habitat selection models. By incorporating territoriality into an RSPF analysis, we determined that wolves’ habitat use in Michigan shifted over time, for example, exhibiting declining responses to winter prey indices and switching from positive to negative responses with respect to stream densities. We consider this an important example of a habitat functional response in wolves, driven by colonization, density-dependence and changes in occupancy during a time period of range expansion and population increase.
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Ethics. All capture and handling protocols were approved by Michigan Department of Natural Resources, State Wildlife Veterinarian. We followed American Society of Mammalogists guidelines for use of wild animals in research . Capture and handling of wolves was permitted under Michigan’s §6 Cooperative Agreement with the United States Fish and Wildlife Service in accordance with 50 CFR 17.21. Data accessibility. Code and data to perform model reduction and fit the hierarchical wolf habitat selection RSPFs using the R-INLA library are archived in DRUM (Data Repository for the University of Minnesota) and are currently accessible at the following location: https://doi.org/10.13020/s40h-fv72 . Authors’ contributions. S.T.O., D.E.B. and J.K.B. conceived ideas, compiled long-term datasets, designed methodology and contributed critically to initial drafts and revisions; S.T.O. analysed the data and led writing of the manuscript; all authors gave final approval for publication. Competing interests. We declare that we have no competing interests with respect to this study. Funding. This work was primarily supported by funding from the Michigan Department of Natural Resources (Michigan Technological University grant no. 751B4300037) and additionally funded by Federal Aid in the Wildlife Restoration Act under Pittman-Robertson (project no. W-147-R), the National Science Foundation (grants to J.K.B.; NSF ID no. 1545611, NSF ID no. 1556676), the DeVlieg Foundation, and the Ecosystem Science Center within the School of Forest Resources and Environmental Science at Michigan Technological University, Michigan, USA. Acknowledgements. We thank Erin Largent, Robert Doepker, Steven Carson, Brian Roell and Chris Webster for assisting with data needs during analysis. Mike Haen, Brad Johnson, Donald Lonsway, Jeff Lukowski and Kristie Sitar assisted with capturing and radio-collaring wolves. Pilots Neil Harris, Dean Minett and Gordon Zuehlke collected collared wolf relocation data. Anna Nisi and Emily Fifelski assisted with data processing. Additional thanks go to two anonymous reviewers for helping us improve the manuscript.
© 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
- Density-dependent habitat selection
- Habitat selection functional response
- Resource selection function