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Person

Brian G Prochazka

WILDLIFE BIOLOGIST

Email: bprochazka@usgs.gov
Office Phone: 530-669-5061
ORCID: 0000-0001-7270-5550

Location
800 Business Park Drive
Suite D
Dixon , CA 95620
US
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We present five hierarchical demarcations of greater sage-grouse population structure, representing the spatial structure of populations which can exist due to differences in dispersal abilities, landscape configurations, and mating behavior. These demarcations represent Thiessen polygons of graph constructs (least-cost path [LCP] minimum spanning trees [MST; LCP-MST]) representing greater sage-grouse population structure. Because the graphs included locational information of sage-grouse breeding sites, we have provided polygons of the population structure. We also present two results using graph analytics representing node/connectivity importance based on our population structure. Understanding wildlife population...
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wy_lvl7_coarsescale: Wyoming hierarchical cluster level 7 (coarse-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
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wy_lvl2_finescale: Wyoming hierarchical cluster level 2 (fine-scale) for Greater sage-grouse We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different...
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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...
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We developed a hierarchical clustering approach that identifies biologically relevant landscape units that can 1) be used as a long-term population monitoring framework, 2) be repeated across the Greater sage-grouse range, 3) be used to track the outcomes of local and regional populations by comparing population changes across scales, and 4) be used to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial scales. The spatial variability in the amount and quality of habitat resources can affect local population success and result in different population growth rates among smaller clusters. Equally so, the spatial structure and ecological...
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