Assessing Risk to Birds from Industrial Wind Energy Development via Paired Resource Selection Models

Journal Article

Title: Assessing Risk to Birds from Industrial Wind Energy Development via Paired Resource Selection Models
Publication Date:
January 09, 2014
Journal: Conservation Biology
Volume: 28
Pages: 745-755
Publisher: Wiley
Receptor:

Document Access

Website: External Link

Citation

Miller, T.; Brooks, R.; Lanzone, M.; Brandes, D.; Cooper, J.; O'Malley, K.; Maisonneuve, C.; Tremblay, J.; Duerr, A.; Katzner, T. (2014). Assessing Risk to Birds from Industrial Wind Energy Development via Paired Resource Selection Models. Conservation Biology, 28, 745-755.
Abstract: 

When wildlife habitat overlaps with industrial development animals may be harmed. Because wildlife and people select resources to maximize biological fitness and economic return, respectively, we estimated risk, the probability of eagles encountering and being affected by turbines, by overlaying models of resource selection for each entity. This conceptual framework can be applied across multiple spatial scales to understand and mitigate impacts of industry on wildlife. We estimated risk to Golden Eagles (Aquila chrysaetos) from wind energy development in 3 topographically distinct regions of the central Appalachian Mountains of Pennsylvania (United States) based on models of resource selection of wind facilities (n = 43) and of northbound migrating eagles (n = 30). Risk to eagles from wind energy was greatest in the Ridge and Valley region; all 24 eagles that passed through that region used the highest risk landscapes at least once during low altitude flight. In contrast, only half of the birds that entered the Allegheny Plateau region used highest risk landscapes and none did in the Allegheny Mountains. Likewise, in the Allegheny Mountains, the majority of wind turbines (56%) were situated in poor eagle habitat; thus, risk to eagles is lower there than in the Ridge and Valley, where only 1% of turbines are in poor eagle habitat. Risk within individual facilities was extremely variable; on average, facilities had 11% (SD 23; range = 0–100%) of turbines in highest risk landscapes and 26% (SD 30; range = 0–85%) of turbines in the lowest risk landscapes. Our results provide a mechanism for relocating high-risk turbines, and they show the feasibility of this novel and highly adaptable framework for managing risk of harm to wildlife from industrial development.

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