Between 2004 and 2011 bighorn sheep were darted in Glacier National Park. Blood was drawn. These are the genotypes resulting from an Ovine HD array from 30 of those bighorns.

This GIS shapefile, "quantile_bands," is derived from a parent shapefile, "density_contours," which describes 1) a bison study area in the North Unit of Theodore Roosevelt National Park, North Dakota and 2) 25%, 50%, 75%, and 99% kernel density contours for locations of bison marked with GPS collars during 2017-2020. Percentages associated with contours describe nominal coverage, i.e., proportions of observations they are expected to encompass, and approximate the distribution of bison activity within the study area. Each contour encompasses lower-coverage contours: the 75% contour, for example, encompasses the 50% and 25% contours but not the 99% contour. Quantile bands correspond with intervals between contours in "density_contours." Each of the first 4 bands encompasses approximately 25% of bison locations. Percentages associated with contours describe nominal coverage, i.e., quantiles the bands are expected to encompass. Bands comprise a partition of the bison study area and do not overlap. Users are advised that ground conditions within the study area may change over time, leading to changes in bison distribution.

Between 2004 and 2011 bighorn sheep were darted in Glacier National Park and in Dinosaur National Monument. Blood was drawn. These are the genotypes resulting from an Ovine HD array from the bighorns. The first 3 columns refers to bighorn sheep identifiers: 'Herd_Unit', 'IndID', and 'AgencyID'. IndID is the identifier assigned at Montana State University. Subsequent columns each represent a locus, with the values in the locus representing the allele.

This GIS shapefile, "quantile_bands," is derived from a parent shapefile, "density_contours," which describes 1) a bison study area at Badlands National Park, South Dakota, and 2) 25%, 50%, 75%, and 99% kernel density contours for locations of bison marked with GPS collars during 2015-2024. Percentages associated with parent contours describe nominal coverage, i.e., proportions of observations they are expected to encompass, and approximate the distribution of bison activity within the study area. Each contour encompasses lower-coverage contours: the 75% contour, for example, encompasses the 50% and 25% contours but not the 99% contour. Quantile bands correspond with intervals between contours in "density_contours." Each of the first 4 bands encompasses approximately 25% of bison locations. Percentages associated with contours describe nominal coverage, i.e., quantiles the bands are expected to encompass. Bands comprise a partition of the bison study area and do not overlap. Users are advised that ground conditions within the study area may change over time, leading to changes in bison distribution.

We developed and report a microsatellite data set composed of 52 microsatellite loci for 2305 individuals from 20 bison conservation herds (17 US federal, 1 tribal, 2 Canadian) and a single nucleotide polymorphism (SNP) data set composed of 5013 biallic loci for 376 individuals from 16 bison conservation herds that were used as part of a broader study. We also developed an algorithm to select a subset of SNPs that captures the genetic variation present in the full SNP data set. Human expansion is a major driver of both declining wildlife species abundance and the contraction of species’ distributions, increasing the risk of genetic erosion and the need for genetic monitoring. Rapidly advancing technology has expanded the types of genetic data that are available for wildlife conservation. However, the use of different genetic markers could result in different management decisions and, thus, must be considered carefully. Rebounding from near extinction in the early 1900s, the majority of plains bison (Bison bison bison) are managed as small and isolated herds. Microsatellite-based analyses are currently used to inform management of the US federal bison conservation herds. Transitioning from monitoring with tens of multiallelic loci (e.g., microsatellite loci) to thousands of biallelic loci (e.g., SNP loci) could increase genotyping efficiency and improve the precision of population genetic inference but would require an understanding of the inferential differences between genetic marker types.

288 adult and yearling female elk were captured on 22 Wyoming winter supplemental elk feedgrounds and monitored with GPS collars during the brucellosis risk period (February – July) from 2007 to 2015. There were 4 to 64 individual elk per feedground and each elk was monitored for 1 to 2 years. Here we provide the unique identifier for each individual elk, the GPS location of the elk, the date/time stamp of the GPS location, and the feedground the elk was captured on in Wyoming.

288 adult and yearling female elk were captured on 22 Wyoming winter supplemental elk feedgrounds and monitored with GPS collars during the brucellosis risk period (February – July) from 2007 to 2015. There were 4 to 64 individual elk per feedground and each elk was monitored for 1 to 2 years. Here we provide the unique identifier for each individual elk, the GPS location of the elk, the date/time stamp of the GPS location, and the feedground the elk was captured on in Wyoming.

The data release details the samples, methods, and raw data used to generate high-quality genome assemblies for greater sage-grouse (Centrocercus urophasianus), white-tailed ptarmigan (Lagopus leucura), and trumpeter swan (Cygnus buccinator). The raw data have been deposited in the Sequence Read Archive (SRA) of the National Center for Biotechnology Information (NCBI), the authoritative repository for public biological sequence data, and are not included in this data release. Instead, the accessions that link to those data via the NCBI portal (www.ncbi.nlm.nih.gov) are provided herein. The release consists of a single file, sample.metadata.txt, which maps NCBI accessions to the samples sequenced and the different types of sequencing performed to generate the assemblies and annotate their gene features.

This data set provides sample data and NCBI accession information for genomic sequencing of ptarmigan and grouse from Alaska.