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The Science Framework for the Conservation and Restoration Strategy of the Sagebrush Biome provides a strategic, multiscale approach for prioritizing areas for management and determining effective management strategies across the sagebrush biome. It includes: A six step process linking information on sagebrush ecosystem resilience to species habitat requirements An assessment of the predominant ecosystem and anthropogenic threats Decision tools including a habitat matrix to aid in determining project areas and appropriate management actions at multiple scales Geospatial data, maps and models provided through the U.S. Geological Survey ScienceBase and BLM Landscape Approach Data Portal to support future assessments...
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...
We produced 13 hierarchically nested cluster levels that reflect the results from developing a hierarchical monitoring framework for greater sage-grouse across the western United States. Polygons (clusters) within each cluster level group a population of sage-grouse leks (sage-grouse breeding grounds) and each level increasingly groups lek clusters from previous levels. We developed the hierarchical clustering approach by identifying biologically relevant population units aimed to use a statistical and repeatable approach and include biologically relevant landscape and habitat characteristics. We desired a framework that was spatially hierarchical, discretized the landscape while capturing connectivity (habitat...
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