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Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development

Harrigan, Ryan1; Rajbhandary, Jasmine1; Bossu, Christen2; Sanzenbacher, Peter3; Dietsch, Thomas3; Gruppi, Cristian1; Katzner, Todd4; Smith, Thomas1; Ruegg, Kristen2

Research facility: University of California, Los Angeles
Published Aug 18, 2023; Updated Feb 20, 2024 on Dryad. https://doi.org/10.5061/dryad.h44j0zprq

Cite this dataset

Harrigan, Ryan et al. (2024). Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development [Dataset]. Dryad. https://doi.org/10.5061/dryad.h44j0zprq

Abstract

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.

README: Dataset for: Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development

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 "solar" birds back to breeding population of origin. This repository includes data files for the 5 species and a R markdown that can be used to replicate the assignment analyses in rubias.

Description of the data and file structure

  1. AMKE_genotypes_rubias.xlsx - Consisting of two tabs: a) AMKE.186SNPgenotypes.breeders - This tab includes genotype of 186 SNP-type assays for 597 American Kestrel (AMKE) breeding individuals. These are the reference individuals used in the rubias analysis. Missing genotypes are categorized as NA. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T, and
    b) AMKE.solar.rubias.input - This tab includes 186 genotypes for 190 birds collected at alternative energy sites. These "solar" birds are assigned back to breeding unites defined on the first tab: AMKE.186SNPgenotypes.breeders. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T.

  2. COLO_genotypes_rubias.xlsx - Consisting of two tabs: a) COLO.158SNPgenotypes.breeders - This tab includes genotype of 158 SNP-type assays for 301 Common Loon (COLO) breeding individuals. These are the reference individuals used in the rubias analysis. Missing genotypes are categorized as NA. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T, and
    b) COLO.solar.rubias.input - This tab includes 158 genotypes for 15 birds collected at alternative energy sites. These "solar" birds are assigned back to breeding unites defined on the first tab: COLO.158SNPgenotypes.breeders. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T.

  3. COYE_genotypes_rubias.xlsx - Consisting of two tabs: a) COYE.96SNPgenotypes.breeders - This tab includes genotype of 96 SNP-type assays for 235 Common Yellowthroat (COYE) breeding individuals. These are the reference individuals used in the rubias analysis. Missing genotypes are categorized as NA. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T, and
    b) COYE.solar.rubias.input - This tab includes 96 genotypes for 25 birds collected at alternative energy sites. These "solar" birds are assigned back to breeding unites defined on the first tab: COYE.96SNPgenotypes.breeders. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T.

  4. WIWA_genotypes_rubias.xlsx - Consisting of two tabs: a) WEWA.96SNPgenotypes.breeders - This tab includes genotype of 96 SNP-type assays for 407 Wilson's Warbler (WIWA) breeding individuals. These are the reference individuals used in the rubias analysis. Missing genotypes are categorized as NA. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T, and
    b) WIWA.solar.rubias.input - This tab includes 96 genotypes for 216 birds collected at alternative energy sites. These "solar" birds are assigned back to breeding unites defined on the first tab: WEWA.96SNPgenotypes.breeders. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T.

  5. YEWA_genotypes_rubias.xlsx - Consisting of two tabs: a) YEWA.96snpgenotypes.breeders - This tab includes genotype of 96 SNP-type assays for 418 Yellow Warbler (YEWA) breeding individuals. These are the reference individuals used in the rubias analysis. Missing genotypes are categorized as NA. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T, and
    b) YEWA.solar.rubias.input - This tab includes 96 genotypes for 288 birds collected at alternative energy sites. These "solar" birds are assigned back to breeding unites defined on the first tab: YEWA.96SNPgenotypes.breeders. Genotypes are labeled as: 1=A, 2=C, 3=G, 4=T.

  6. Final.assignment.to.species.xlsx: This excel sheet holds the meta data for each individual genotyped for 5 species. The data includes Sample name, State, Alternative energy site, Day, Month and Year the sample was collected, Latitude and Longitude, as well as the assignment results of rubias in the form of the probability of assignment of each bird to each population-specific breeding unit.

Describe relationships between data files, missing data codes, other abbreviations used. Be as descriptive as possible.

Sharing/Access information

Links to other publicly accessible locations of the data:

Code/Software

  1. Solar_Indiv_PopAssignment.Rmd: This is a R markdown script that will assign solar birds back to a distinct breeding unit defined in the breeding bird input file using the rubias software program.

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.  

Usage notes

R

RUBIAS

Funding

United States Department of Energy, Award: DE-EE0009005, Solar Energy Technologies Office

California Energy Commission, Award: EPC-14-061

California Energy Commission, Award: EPC-15-043