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Cameron L. Aldridge

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Potential future greater sage-grouse (Centrocercus urophasianus) habitat restoration was projected (2018-2068) for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin using outputs from a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. These datasets, for the NW-Interior Nevada, USA (NWINV) sage-grouse population, include: 1) a set of 78 categorical raster layers illustrating a time series (decade intervals) of potential future habitat, and 2) a set of 15 uncategorized raster layers illustrating potential change in habitat classification across space, after simulating 50 years...
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This is a spatially-explicit state-and-transition simulation model (STSM) of sagebrush-steppe vegetation dynamics for greater sage-grouse (Centrocercus urophasianus) Priority Areas for Conservation (PACs) in the Great Basin. The STSM was built using the ST-Sim platform and uses an integrated stock-flow submodel (STSM-SF) to simulate and track continuous vegetation component cover changes caused by annual growth, natural regeneration, and post-fire sagebrush seeding and planting restoration. Spatially explicit models were built for three sage-grouse PACs (Klamath Oregon/California [KLAM], NW Interior Nevada [NWINV], Strawberry Utah [STRAW]) that differed in historic wildfire patterns and the amounts of various component...
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This data, grsg_lcp_ThiessenPoly_mst3, is one of five hierarchical delineations of greater sage-grouse population structure. The data represent Thiessen polygons of graph constructs (least-cost path minimum spanning tree [LCP-MST]) that defined our population structure of sage-grouse breeding sites in the western United States. This data was developed by applying dispersal and genetic rules to decompose the fully connected population structure (graph) into the product presented here. Understanding wildlife population structure and connectivity can help managers identify conservation strategies, as structure can facilitate the study of population changes and habitat connectivity can provide information on dispersal...
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Closeness centrality (cc; grsg_lcp_closeness_centrality) measures the average length of the shortest path between the node and all other nodes in the graph. The more central a node, the closer it is to all other nodes and the more likely information/movements can flow to other nodes. Closeness is computed as one divided by the average path lengths from a node to its neighbors, which assumes that important nodes are close to other nodes. The data were defined from least-cost paths (LCPs) constructed into minimum spanning trees (MSTs). We identified a threshold of the cc normalized value (>0.047) where patterns of network connectivity occurred in our graph. The cc identified leks with the greatest number of shortest...
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Potential future greater sage-grouse (Centrocercus urophasianus) habitat restoration was projected (2018-2068) for three sage-grouse Priority Area for Conservation (PACs) populations located along the northwestern, central, and eastern edge of the Great Basin using outputs from a spatially explicit state-transition simulation model (STSM) developed for sagebrush ecosystems. These datasets, for the Strawberry Utah, USA (STRAW) sage-grouse population, include: 1) a set of 78 categorical raster layers illustrating a time series (decade intervals) of potential future habitat, and 2) a set of 15 uncategorized raster layers illustrating potential change in habitat classification across space, after simulating 50 years...
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