Data from: Habitat selection predicts genetic relatedness in an alpine ungulate
- Description:
- Landscape heterogeneity plays an integral role in shaping ecological and evolutionary processes. Despite links between the two disciplines, ecologists and population geneticists have taken different approaches to evaluating habitat selection, animal movement, and gene flow across the landscape. Ecologists commonly use statistical models such as resource selection functions (RSFs) to identify habitat features disproportionately selected by animals, while population genetic approaches model genetic differentiation according to the distribution of habitat variables. We combined ecological and genetic approaches by using RSFs and step-selection functions (SSFs) to predict genetic relatedness across a heterogeneous landscape. We constructed sex and season-specific resistance surfaces based on RSFs and SSFs estimated using data from 102 GPS radiocollared mountain goats (Oreamnos americanus) in southeast Alaska. Based on mountain goat ecology, we hypothesized that summer and male surfaces would be the best predictors of relatedness. All individuals were genotyped at 22 microsatellite loci, which we used to estimate genetic relatedness. Summer resistance surfaces derived from RSFs were the best predictors of genetic relatedness, and winter models the poorest. Male and female specific surfaces were similar, except for winter where male habitat selection better predicted genetic relatedness. The null models of isolation-by-distance and barrier only outperformed the winter models. This study merges high-resolution individual locations through GPS telemetry and genetic data, that can be used to validate and parameterize landscape genetics models, and further elucidates the relationship between landscape heterogeneity and genetic differentiation.
Usage Notes:Shafer_LG_data_DRYAD_2011_1021_sub
Introductory information: Mountain goat (Oreamnos americanus) capture and genotype data. Collected by Kevin White (Alaska Department of Fish and Game) and Aaron Shafer (University of Alberta). Please contact either Kevin White (kevin.white@alaska.gov) or Aaron Shafer (shafer@ualberta.ca) with any questions of location and genotype data, respectively. Row 1 - Headings (descriptions in subheadings): Identification – lab ID, capture ID, capture date, sex, and estimated age of animal; Capture Location - latitude and longitude; Home Range centroid location - latitude and longitude (of 100% Minimum Convex Polygon); Loci - names of microsatellite loci analyzed. Row 2 - Subheadings: Lab ID - ID number used in lab; Capture ID - ID number used in field; Capture Date – Day-Month-Year; Sex – male or female; Est. Age – estimated age based on horn annuli; Latitude, Longitude - latitude (Y) and longitude (X) coordinates (datum = WGS84) of capture and home range centroid; Name of Loci - 21 in total, two alleles provided per loci in adjacent columns, missing data given a zero. Row 3 - Data. - , , , , Côté, Steeve D.et
- Dépôt source:
- Dryad
- Éditeur(s):
- Dryad
- Accès:
- Public
- URL:
- http://datadryad.org/stash/dataset/doi:10.5061/dryad.6b6k8b83
- Date de publication:
- 2012-06-14
- Mots-clés (en):
- Identificateur:
- https://doi.org/10.5061/dryad.6b6k8b83
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