Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development
收藏NIAID Data Ecosystem2026-05-01 收录
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http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.h44j0zprq
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资源简介:
With new motivation to increase the proportion of energy demands met by zero-carbon sources, there is a greater focus on efforts to assess and mitigate the impacts of renewable energy development on sensitive ecosystems and wildlife, of which birds are of particular interest. One challenge for researchers, due in part to a lack of appropriate tools, has been estimating the effects from such development on individual breeding populations of migratory birds. To help address this, we utilize a newly developed, high-resolution genetic tagging method to rapidly identify the breeding population of origin of carcasses recovered from renewable energy facilities and combine them with maps of genetic variation across geographic space (called ‘genoscapes’) for five species of migratory birds known to be exposed to energy development, to assess the extent of population-level effects on migratory birds. We demonstrate that most avian remains collected were from the largest populations of a given species. In contrast, those remains from smaller, declining populations made up a smaller percentage of the total number of birds assayed. Results suggest that application of this genetic tagging method can successfully define population-level exposure to renewable energy development and may be a powerful tool to inform future siting and mitigation activities associated with renewable energy programs.
Methods
For 5 migratory bird species, we used targeted SNP-genotyping of breeding reference birds and carcasses of birds sampled at alternative energy sites. We then assigned the birds recovered from renewable energy facilities (lebeled "solar") back to breeding population of origin. This repository includes data files for the 5 species and an R markdown file that can be used to replicate the assignment analyses in rubias, as well as final assignments to species as reported in the associated manuscript.
创建时间:
2024-02-20



