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Landscape context and behavioral clustering contribute to flexible habitat selection strategies in a large mammal

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An understanding of individual variation in animal habitat selection is important for effective conservation and management as well as predicting species responses to a rapidly changing world. Functional responses to habitat availability can explain some of this variation, but not accounting for behavioral grouping may oversimplify inference and mask the diversity of habitat use strategies present in a population. We investigated within-home range habitat selection variation at the group level in a reintroduced population of elk (Cervus canadensis) in Kentucky, USA, during 2020–2022, analyzing satellite tracking data from 103 individuals to quantify variance in responses to seven landscape variables. We used group-level selection coefficients estimated with mixed-effects resource selection functions to model population-level functional responses and classify groups into within-season behavioral clusters. We then used cross validation to assess if these methods of generalizing group-level variation improved predictions of space use. We found that elk had highly variable responses to several covariates, and that some of this variation could be attributed to functional responses to either cover type availability or configuration. When we generalized behavioral tactics via clustering, we found significant increases in group-level predictive ability over the global model and, in some cases, the functional models. This suggests that clustered behaviors are also driving individual heterogeneity in this population. Our results highlight the importance of considering individual differences when studying wildlife-habitat relationships and underscore the need for a more complete understanding of the mechanisms behind this variation to inform habitat management and conservation efforts.

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Data availability

Pre-processed datasets used in analysis are available from a Zenodo repository ( R scripts used to clean and analyze data are available from GitHub ( Given the sensitive nature of animal location data, raw GPS relocations analyzed in this study are not publicly available but can be provided by the corresponding author upon reasonable request.


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We also want to acknowledge the staff and volunteers who assisted in the field with elk capture and data collection, especially: C. Casey, J. Fusaro, K. Sams, T. Curry, G. Jenkins, D. Brewster, Z. Hahn, S. Maywald, A. Riggs, J. Wissmann, P. Clements, K. Bosch, and D. Yancy. Finally, we thank the landowners and managers for allowing us to capture elk on their properties across the KERZ.


This study was funded by Pittman-Robertson federal aid administered by KDFWR and supplemented by the U.S. Department of Agriculture McIntire-Stennis program (Project #1021936) and the Rocky Mountain Elk Foundation. NDH was supported by a teaching assistantship through the Department of Forestry and Natural Resources at the University of Kentucky during part of this study. We also thank the Department of Forestry and Natural Resources at the University of Kentucky (UK) for logistical support and UK’s Robinson Center for Appalachian Resource Sustainability for providing field housing.

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All authors contributed to the study conception and design. Field data collection was performed by Nathan D. Hooven, Kathleen E. Williams, John T. Hast, Joseph R. McDermott, and R. Daniel Crank. Project administration was performed by Matthew T. Springer and John J. Cox. Nathan D. Hooven conducted statistical analysis and visualization and wrote the first draft of the manuscript and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Nathan D. Hooven.

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Ethical approval

All animal capture protocols were approved by the Institutional Animal Care and Use Committee of the University of Kentucky (protocol #2019–3382).

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The authors declare no competing interests.

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Communicated by: Marietjie Landman.

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Hooven, N.D., Williams, K.E., Hast, J.T. et al. Landscape context and behavioral clustering contribute to flexible habitat selection strategies in a large mammal. Mamm Res (2024).

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