A Genoscape Framework for Assessing the Population-Level Impacts of Renewable Energy Development on Migratory Bird Species in California

With California’s mandate to produce more clean, renewable electricity, every effort must be made to assess and mitigate the impacts of renewable energy development on California’s sensitive ecosystems and the wildlife species they support. The researchers took a three-pronged approach to assess the population-specific impacts of renewable energy development on migratory birds. First, to locate population boundaries for four species, they applied a newly developed, high-resolution genetic tagging method to map population-specific migratory pathways using the DNA from feathers collected from across the annual life cycle. Maps of fine-scale spatial structure of genetic diversity (called genoscapes) and population-specific migratory timing in two of the four species highlight the importance of understanding the population structure when developing mitigation strategies for these species. Second, they used completed genoscapes to identify the breeding populations of origin of carcasses salvaged from renewable energy facilities along the Pacific migration corridor. The results support the idea that the majority of individual birds exposed to renewable energy facilities came from the largest genetically distinct populations within each species; carcasses from rare and declining populations made up a smaller percentage of the total number of birds sampled. Finally, they created maps that combined multi-species migration hotspots with information on regions of high renewable energy potential to influence selection of renewable energy sites that minimize harm to migratory birds. The results demonstrated that prioritization of renewable energy siting practices varied across the taxonomic groups analyzed (nine target species as well as three groups: raptors, waterfowl, and songbirds), but generally supported prioritization of renewable energy siting in four California counties: Modoc, Lassen, Riverside, and San Bernardino. Overall, this work supports the idea that high-resolution genetic tagging improves identification of population-level exposure of migratory birds to wind and solar development and provides tools for siting and monitoring renewable energy facilities in the future.