Multi‐level thresholds of residential and agricultural land use for elk avoidance across the Greater Yellowstone Ecosystem

• Published in: The Journal of applied ecology Vol. 60; no. 6; pp. 1089 - 1099
• Main Authors: Gigliotti, Laura C., Atwood, M. Paul, Cole, Eric K., Courtemanch, Alyson, Dewey, Sarah, Gude, Justin A., Hurley, Mark, Kauffman, Matthew, Kroetz, Kailin, Leonard, Bryan, MacNulty, Daniel R., Maichak, Eric, McWhirter, Douglas, Mong, Tony W., Proffitt, Kelly, Scurlock, Brandon, Stahler, Daniel R., Middleton, Arthur D.
• Format: Journal Article
• Language: English
• Published: Oxford Blackwell Publishing Ltd 01-06-2023
• Subjects: Agricultural ecosystems; Agricultural land; Agriculture; Availability; Avoidance; Cervus canadensis; Cervus elaphus; Conservation; Conservation easements; development; Easements; Elk; Environmental factors; Environmental protection; functional response; Global positioning systems; GPS; Habitat selection; Home range; Land use; Landscape; Landscape preservation; land‐use change; Levels; Residential development; Thresholds; Wildlife; Wildlife conservation; Wildlife habitats
• ISSN: 0021-8901; 1365-2664
• DOI: 10.1111/1365-2664.14401

Conversion of land for settlements and agriculture is increasing globally and can influence wildlife space use. However, there is limited research to identify the thresholds of land‐use change that incur wildlife avoidance and how these thresholds might vary across levels of selection.
We evaluated multi‐level avoidance thresholds of elk Cervus canadensis impacted by residential development and irrigated agriculture across the Greater Yellowstone Ecosystem in Idaho, Montana and Wyoming. Using GPS data from 765 elk in 21 herds, we estimated habitat selection in relation to development and agriculture at three levels (home range selection, within home range selection and movement path selection). Next, using individual selection covariates and associated measures of land‐use availability, we used functional‐response models to evaluate how selection varied based on availability, and in turn, to estimate avoidance thresholds.
We found individual and level‐specific variation in elk responses to environmental factors. Elk exhibited stronger responses (either selection or avoidance) when selecting home range locations (i.e. second‐order selection) than when selecting areas within home ranges (i.e. third‐order selection) or selecting movement paths (i.e. fourth‐order selection). Importantly, elk avoidance of development and agriculture changed as the amount of land in these categories changed. Across all levels of selection elk exhibited neutral selection for human development at low levels of availability (<1.1%–2.2% developed) but avoided areas that were >1.1%–2.2% developed. Conversely, elk selected positively for irrigated agriculture at low to moderate levels of availability (<52.0%–66.2% agriculture) but exhibited neutral selection in areas that were >52.0%–66.2% agriculture.
Synthesis and applications. Elk avoidance of low levels of human development suggests conservation efforts such as restrictions on future development or conservation easements could focus on areas that are still below 2% developed. Additionally, because elk selection was strongest at the landscape scale, conservation actions that are based on information about the overall landscape structure may be most impactful. Our results highlight the importance of understanding variability in wildlife habitat selection at multiple levels, particularly in relation to land‐use change, and highlight how functional response modelling can help inform landscape conservation.
Elk avoidance of low levels of human development suggests conservation efforts such as restrictions on future development or conservation easements could focus on areas that are still below 2% developed. Additionally, because elk selection was strongest at the landscape scale, conservation actions that are based on information about the overall landscape structure may be most impactful. Our results highlight the importance of understanding variability in wildlife habitat selection at multiple levels, particularly in relation to land‐use change, and highlight how functional response modelling can help inform landscape conservation.