Skip to main content

Person

Todd B Cross

thumbnail
Characterizing genetic structure across a species’ range is relevant for management and conservation as it can be used to define population boundaries and quantify connectivity. Here, we characterized population structure and estimated effective migration in Greater Sage-grouse (Centrocercus urophasianus). Our objectives were to (1) describe large-scale patterns of population genetic structure and gene flow and (2) to characterize genetic subpopulation centers across the range of Greater Sage-grouse. Samples from 2,134 individuals were genotyped at 15 microsatellite loci. Using standard STRUCTURE and spatial principal components analyses, we found evidence for four or six areas of large-scale genetic differentiation...
thumbnail
Monitoring change in genetic diversity in wildlife populations across multiple scales could facilitate prioritization of conservation efforts. We used microsatellite genotypes from 7,080 previously collected genetic samples from across the greater sage-grouse (Centrocercus urophasianus) range to develop a modelling framework for estimating genetic diversity within a recently developed hierarchically nested monitoring framework (clusters). The majority of these genetic samples (n=6560) were used in previous research (Oyler-McCance et al. 2014; Cross et. al 2018; Row et. al. 2018). Genetic diversity values associated with clusters across multiple scales could facilitate the identification of areas with low genetic...
thumbnail
Genetic networks can characterize complex genetic relationships among groups of individuals, which can be used to rank nodes most important to the overall connectivity of the system. Ranking allows scarce resources to be guided towards nodes integral to connectivity. The greater sage-grouse (Centrocercus urophasianus) is a species of conservation concern that breeds on spatially discrete leks that must remain connected by genetic exchange for population persistence. We genotyped 5,950 individuals, from 1,200 greater sage-grouse leks distributed across the entire species’ geographic range. We found a small world network composed of 458 nodes connected by 14,481 edges that are described here. The files associated...
thumbnail
Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species’ conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., fine-scale) with low genetic diversity relative...
thumbnail
Functional connectivity, quantified using landscape genetics, can inform conservation through the identification of factors linking genetic structure to landscape mechanisms. We used breeding habitat metrics, landscape attributes, and indices of grouse abundance, to compare fit between structural connectivity and genetic differentiation within five long-established Sage-Grouse Management Zones (MZ) I–V using microsatellite genotypes from 6,009 greater sage-grouse (Centrocercus urophasianus) collected across their range. We estimated structural connectivity using a circuit theory-based approach where we built resistance surfaces using thresholds dividing the landscape into “habitat” and “nonhabitat” and nodes were...
View more...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.