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Habitat selection studies can make important contributions to habitat prioritization efforts for species of conservation concern. We present a large-scale collaborative effort to develop habitat selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes (Wyoming, USA) and multiple seasons. Greater Sage-grouse are limited to western semi-arid landscapes in North America, range-wide population declines have been documented, and the species is currently listed a “warranted but precluded” from listing under the U.S. Endangered Species Act. Wyoming is predicted to remain a stronghold for Sage-grouse populations and contains approximately 37% of the remaining birds. We developed Resource...
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This metadata references the polygonal ARC/INFO GIS cover showing the current and historic distribution of potential habitat, or range, of the Greater Sage-grouse (Centrocercus urophasianus) and Gunnison Sage-grouse (Centrocercus minimus) in Western North America. This data was initially researched and compiled by Dr. Michael A. Schroeder, research biologist for the Washington State Department of Fish and Wildlife. The initial draft of current and historic range data was mapped and submitted to state, federal, or provincial natural resource agencies and other experts for review, comment, and editing. The final product represents the best available science and expert review available at the time of compilation. ...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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Future climates are simulated by general circulation models (GCM) using climate change scenarios (IPCC 2014). To project climate change for the sagebrush biome, we used 11 GCMs and two climate change scenarios from the IPCC Fifth Assessment, representative concentration pathways (RCPs) 4.5 and 8.5 (Moss et al. 2010, Van Vuuren et al. 2011). RCP4.5 scenario represents a future where climate policies limit and achieve stabilization of greenhouse gas concentrations to 4.5 W m-2 by 2100. RCP8.5 scenario might be called a business-as-usual scenario, where high emissions of greenhouse gases continue in the absence of climate change policies. The two selected time frames allow comparison of near-term (2020-2050) and longer-term...
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This raster represents a continuous surface of sage-grouse habitat suitability index (HSI) values for northeastern California. HSIs were calculated for spring (mid-March to June), summer (July to mid-October), and winter (November to March) sage-grouse seasons, and then multiplied together to create this composite dataset.
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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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This dataset represents the consolidated submissions for non-energy minerals and prospecting permit application data from BLM states responding to the WO 300 data call during the time period of November 2011 through May 2012. It is intended solely for use in the GRSG cumulative effects analysis. Source data, their acquisition methods and errors/omission rate vary. All original datasets used to create this dataset are stored in the BLM’s NOC E-GIS file structure. The paths to the original data are stored in this file’s attribute table. See the source data for detailed metadata and error analysis. Processing to develop this dataset: 1. Added a "Source" field to the attribute table of the original submission. 2. Populated...
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This product is as subset of a legacy dataset and is included in the REA publication as it was used in the analysis for the Colorado Plateau REA. The legacy dataset was not part of the GRSG official HMA designations or planning process in 2015. For the most current version of sage-grouse habitat delinations assiciated with BLM Land Use Plans please visit the Greater Sage Grouse page on the Landscape Approach Data Portal. Updated in December, 2012 to the National Sage-grouse Planning Effort area. Canada, Washington, and Bi-State Distinct Population Segment areas were removed. Original versions exist in the 'Wildlife/Data' Sage-grouse directories at the NOC. This spatial dataset represents modeled occupied greater...
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This USGS data release represents geospatial data for the sage-grouse habitat mapping project. This study provides timely and highly useful information about greater sage-grouse over a large area of the Great Basin. USGS researchers and their colleagues created a template for combining landscape-scale occurrence or abundance data with habitat selection data in order to identify areas most critical to sustaining populations of species of conservation concern. The template also identifies those areas where land use changes have minimal impact. To inform greater sage-grouse conservation planning, the researchers developed greater sage-grouse habitat management categories based on habitat selection indices (HSI) and...
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Sage-grouse habitat areas divided into proposed management categories within Nevada and California project study boundaries. HABITAT CATEGORY DETERMINATION The process for category determination was directed by the Nevada Sagebrush Ecosystem Technical team. Sage-grouse habitat was determined from a statewide resource selection function model and first categorized into 4 classes: high, moderate, low, and non-habitat. The standard deviations (SD) from a normal distribution of RSF values created from a set of validation points (10% of the entire telemetry dataset) were used to categorize habitat ‘quality’ classes. 1) High quality habitat comprised pixels with RSF values < 0.5 SD. 2) Moderate > 0.5 and < 1.0 SD. 3)...
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This dataset contains landscape-scale greater sage-grouse Preliminary General Habitat. Specifically, it represents the remaining Sagebrush, Perennial grassland, Conifer encroachment, and some Persistence greater than 25% not accounted for in the 2012 Preliminary Priority Habitat dataset (Version 2 - April 2012). A combination of Key Habitat (Sather-Blair et al., 2000; ISAC 2006; BLM 2012), important winter and breeding habitat, local priority areas (spatially identified by the local working groups, BLM, IDFG biologists), known migration movement corridors, the revised 2011PA polygons, and exclusion of modeled agricultural and timber lands were used to further refine the 2012 Preliminary Priority Habitat (PPH) and...
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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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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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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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A GAP Analysis uses GIS layers provided by the GAP Analysis Program (species distribution models, stewardship data) to determine which areas within a species distribution have protected status and to identify possible conservation gaps. This GAP Analysis was conducted for Greater Sage-grouse within the boundary of the Southern Rockies LCC. About 7.6% of the Sage-grouse's total predicted distribution is within the SRLCC (based on GAP distribution models). There are four products in this ScienceBase item: an Excel spreadsheet with analysis data (see list below), a GIF image map of the SRLCC (displaying predicted sage-grouse distribution and areas with protected status), a map package containing the GIS layers used...
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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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nv_lvl6_coarsescale: Nevada hierarchical cluster level 6 (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_lvl8_coarsescale: Wyoming hierarchical cluster level 8 (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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The delineation of priority areas in western North America for managing Greater Sage-Grouse (Centrocercus urophasianus) represents a broad-scale experiment in conservation biology. The strategy of limiting spatial disturbance and focusing conservation actions within delineated areas may benefit the greatest proportion of Greater Sage-Grouse. However, land use under normal restrictions outside priority areas potentially limits dispersal and gene flow, which can isolate priority areas and lead to spatially disjunct populations. We used graph theory, representing priority areas as spatially distributed nodes interconnected by movement corridors, to understand the capacity of priority areas to function as connected...


map background search result map search result map Greater Sage-Grouse Preliminary General Habitat (Version 2, April 2012) for Idaho GAP Analysis for the SRLCC: Greater Sage-grouse Current Distribution of the Sage-grouse in North America Sage-grouse Habitat Categories in Nevada and NE California (August 2014) Integrating Spatially Explicit Indices of Abundance and Habitat Quality: An Applied Example for Greater Sage-grouse Management Raster digital data sets identifying a range-wide network of priority areas for greater sage-grouse Precipitation (Proportion July - Sep) - 2070-2100 - RCP8.5 - Mean Precipitation (Mean: July - Sep) - 2070-2100 - RCP8.5 - Mean Precipitation (Mean: July - Sep) - 2020-2050 - RCP8.5 - Min Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 6 (Nevada), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 2 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 8 (Wyoming), Interim Composite Habitat Suitability Index Raster Dataset BLM GRSG BER: Non-Energy Minerals and Prospecting Permit Applications (polygon) BLM REA COP 2014 Greater Sage Grouse Predicted Current Distribution in the COP, USA Greater sage-grouse population structure and connectivity data to inform the development of hierarchical population units (western United States) State-and-Transition Simulation Models, parameters, input data, and simulation results NW-Interior Nevada time series (2018-2068) of potential habitat and 50-year change Composite Habitat Suitability Index Raster Dataset BLM REA COP 2014 Greater Sage Grouse Predicted Current Distribution in the COP, USA Greater Sage-Grouse Preliminary General Habitat (Version 2, April 2012) for Idaho Integrating Spatially Explicit Indices of Abundance and Habitat Quality: An Applied Example for Greater Sage-grouse Management State-and-Transition Simulation Models, parameters, input data, and simulation results Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 2 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 8 (Wyoming), Interim Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Cluster Level 6 (Nevada), Interim Sage-grouse Habitat Categories in Nevada and NE California (August 2014) GAP Analysis for the SRLCC: Greater Sage-grouse Hierarchically nested and biologically relevant monitoring frameworks for Greater Sage-grouse, 2019, Nevada and Wyoming, Interim BLM GRSG BER: Non-Energy Minerals and Prospecting Permit Applications (polygon) Current Distribution of the Sage-grouse in North America Greater sage-grouse population structure and connectivity data to inform the development of hierarchical population units (western United States) Raster digital data sets identifying a range-wide network of priority areas for greater sage-grouse Precipitation (Proportion July - Sep) - 2070-2100 - RCP8.5 - Mean Precipitation (Mean: July - Sep) - 2070-2100 - RCP8.5 - Mean Precipitation (Mean: July - Sep) - 2020-2050 - RCP8.5 - Min