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This shapefile provides general range information for all landscape species for which distributions were mapped based upon models previously developed by the U.S. Geological Survey’s Southwest Regional Gap Analysis Project (SWReGAP). It was created to support the mapping of detailed distributions for these species. The range data provided here represents an amalgamation of range data from SWReGap, the California Wildlife Habitat Relationships database (http://www.dfg.ca.gov/biogeodata/cwhr/cawildlife.aspx ), NatureServe species distribution shapefiles, and expert opinion. SWReGap defined range based on 8-digit hydrologic units. Where it was necessarily to extend these ranges into California, Idaho, and/or Oregon,...
Scorecard analysis for terrestrial conservation elements and near-future landscape condition. The landscape condition score represents area weighted mean value based upon the combined count and condition score. sum(count*score) / sum(count) *where count equals the cell count and score is the condition value. NatureServe’s ecological integrity framework provides a practical approach to organize criteria and indicators for this purpose (Faber-Langendoen et al. 2006, Unnasch et al. 2008). This framework provides a scorecard for reporting on the ecological status of a given CE within a given location, and if needed, facilitates the aggregation and synthesis of the component results for broader measures of ecological...
Scorecard analysis for terrestrial conservation elements and near future landscape condition. The landscape condition score represents area weighted mean value based upon the combined count and condition score. sum(count*score) / sum(count) *where count equals the cell count and score is the condition value. NatureServe’s ecological integrity framework provides a practical approach to organize criteria and indicators for this purpose (Faber-Langendoen et al. 2006, Unnasch et al. 2008). This framework provides a scorecard for reporting on the ecological status of a given CE within a given location, and if needed, facilitates the aggregation and synthesis of the component results for broader measures of ecological...
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal Mean Annual Ground Temperature at 1 Meter Depth (°C) for the decades 2010-2019, 2020-2029, and 2060-2069 at 2km spatial resolution. It represents the A2 emissions scenario and the spatial extent is the NOS REA study area.
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average January temperature (in °C) for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a decadal mean calculated from monthly totals, using the A2 emissions scenario. The spatial extent is clipped to the NOS REA...
This shapefile provides general range information for all landscape species for which distributions were mapped based upon models previously developed by the U.S. Geological Survey’s Southwest Regional Gap Analysis Project (SWReGAP). It was created to support the mapping of detailed distributions for these species. The range data provided here represents an amalgamation of range data from SWReGap, the California Wildlife Habitat Relationships database (http://www.dfg.ca.gov/biogeodata/cwhr/cawildlife.aspx ), NatureServe species distribution shapefiles, and expert opinion. SWReGap defined range based on 8-digit hydrologic units. Where it was necessarily to extend these ranges into California, Idaho, and/or Oregon,...
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average May temperature (in °C) for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a decadal mean calculated from monthly totals, using the A2 emissions scenario. The spatial extent is clipped to the NOS REA study...
Some of the NOS rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This file includes a downscaled projection of decadal average of spring (March, April, May) total precipitation (in millimeters) for the decades 2010-2019, 2020-2029, and 2060-2069 at 771x771 meter spatial resolution. The file represents a decadal mean of seasonal totals calculated from monthly totals, using the A2 emissions...
Some of the YKL rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors' discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - The landscape condition model (LCM) evaluates the degree of human impact on the landscape. The current landscape condition was extracted to the current distribution of spruce forest. The intersection of the white spruce or black spruce CE distribution with the LCM suggests that over 94% of the total CE area is very high (intact)...
For each variable the per pixel change between the recent time slice (1981-2012) or future timslice (2050s) and the baseline (1900-1980) was calculated, identifying climate “deltas” for each pixel. Recent deltas are 800m resolution and use PRISM as the source dataset. Future deltas are 4km resolution and use ClimateWNA as the source dataset. Delta = later timeslice (recent or future) - baseline. Raster values are expressed in climate units either mm for precipitation or degrees c for temperature. delta ratio values are included for precipitation and CMD, which are ratios of change (1 = no change, < 1 = decreasing, > 1 = increasing).
For each variable the per pixel change between the recent time slice (1981-2012) or future timslice (2050s) and the baseline (1900-1980) was calculated, identifying climate “deltas” for each pixel. Recent deltas are 800m resolution and use PRISM as the source dataset. Future deltas are 4km resolution and use ClimateWNA as the source dataset. Delta = later timeslice (recent or future) - baseline. Raster values are expressed in climate units either mm for precipitation or degrees c for temperature. delta ratio values are included for precipitation and CMD, which are ratios of change (1 = no change, < 1 = decreasing, > 1 = increasing).
A polygon dataset of current road footprints in the SNK REA derived from the Alaska Department of Natural Resources infrastructure data (see the process steps for details). (This data depicts infrastructure locations in Alaska as digitized primarily from 1:24,000, 1:63,360, and 1:250,000 USGS quadrangles. The source document that represented the newest information and best geographic location was used to capture the data. All infrastructure from the primary source document was digitized and then supplemented with the information from other source documents for additional or updated infrastructure or attributes.)
Average January temperature for 2016-2030 projected by the GFDL2.1 GCM run 1 driven by the A2 emissions scenario at 1/8 degree latitude-longitude (approximately 12km by 12 km) over the Wyoming Basin and surrounding areas. BCSD data downloaded the "Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections," archived at http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/.
Developed Landcover used in Biome Analysis. Developed landcover reclassified from Landfire EVT.
Analysis of future ecological integrity to assess the near future (circa 2030) status of the Aquatic Coarse Filter Conservation Elements - Landscape Condition Model Index. Below are the aquatic caurse-filter conservation elements for this indicator: Great Basin Lake / Reservoir Great Basin Spring and Seeps Great Basin Foothill and Lower Montane Riparian Woodland and Shrubland / Stream Rocky Mountain Subalpine-Montane Riparian Woodland and Shrubland / Stream Rocky Mountain Lower Montane-Foothill Riparian Woodland and Shrubland / Stream Inter-Mountain Basins Greasewood Flat Inter-Mountain Basins Wash Inter-Mountain Basins Playa
Average annual temperature for 2016-2030 projected by the ECHAM5 GCM run 1 driven by the A2 emissions scenario at 1/8 degree latitude-longitude (approximately 12km by 12 km) from a 36-member GCM ensemble (16 GCMs with multiple runs of some GCMs, all the runs available for BCSD) over the Wyoming Basin and surrounding areas. BCSD data downloaded from the "Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections" archived at http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/.
Mapping of terrestrial vertebrates focuses on linking a spatial representation of species-habitat matrices to geographic distribution. Each model is a combination of distribution from regional and state references in association with contiguous appropriate habitats. Ranges for all species were based on 8-digit HUCs. Habitats were based on a raster SWReGAP 1 acre MMU land cover data set, with hydrology habitats added in from USGS NHD dataset directly or through modeling. Habitat association information was obtained from various state, regional, and national references with updates from scientific literature. This portion of the Southwest Regional Gap Analysis Project produced predicted habitat distribution maps for...
To assess fire frequency and extent, the perimeters of fires overlapping the distribution of pygmy rabbit. Fire occurrences since 1980 were compiled from fire occurrence data sets from U.S. Forest Service, U.S. Geological Survey (GeoMAC), National Park Service, Monitoring Trends in Burn Severity, Western Fires Database, Bureau of Land Management, and National Fire and Aviation Management Web applications.
Low risk of SAD equals current aspen distribution coincident with the 2030 SAD climatic envelope classes, Potential aspen climatic envelope expansion, or No expected change in aspen climatic envelope.
Compliation of Wyoming Bureau of Land Management field office data of Russian olive and tamarisk occurrence expressed as point locations.
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