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Summary lists by HUC10 watershed for CBR and MBR of Landscape Species, Local Species, Coarse Filter Species, and Assemblages, prepared by NatureServe from sensitive Element Occurrence (EO) and Observation data provided by NatureServe member programs for use in the BLM REA projects. Landscape species analyses are based on final distribution models created for the BLM REA projects. Bald Eagle and Golden Eagle data were supplemented by data downloaded from the Global Biodiversity Information Facility (http://www.gbif.org/).
This dataset is a raster summarizing the change in suitable bioclimate by looking at the difference between current and A2 2050s. Value coding:-3 = Lost bioclimate; 0 = absence (current and future); 1= maintained bioclimate; 4 = gained bioclimate
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,...
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,...
This is a 100-meter cell resolution raster dataset consisting of 1:750,000-scale surficial geology for California and 1:500,000-scale for Nevada, and parts of Utah, Colorado, New Mexico, and Arizona. This data set was aggregated from a compilation of geologic maps of the Southwest Regional GAP Analysis Project (ReGAP) along with California geology and the very southern portion of Oregon and Idaho geology.
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)...
This table contains information about the amount of each threat analysis attribute, indicator and metric quantified for the 6th level Hydrological Unit (HUC12). These attributes were calculated for the entire HUC 12, the streams within the HUC 12, or the riparian corridor within the HUC 12. The attributes were calculated using ArcMap Tools These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. The User is encouraged to carefully consider the content of the metadata file associated with these data.
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.)
This map shows habitat connectivity compiled from multiple sources. Habitat connectivity was modeled separately in California and Arizona. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics appropriate for applications that potential users of the data may contemplate. The User is encouraged to carefully consider the content of the metadata file associated with these data. The BLM should be cited...
This map shows risk models for invasive species within the ecoregion. Samples of invasive species are presenting -- falling within 4 categories (exotic, annual grasses, noxious forbs, and woody riparian). Bioclimate data for cheatgrass and tamarisk weed is also shown. The input dataset used for all analysis done for these models are also included. These data are provided by Bureau of Land Management (BLM) "as is" and may contain errors or omissions. The User assumes the entire risk associated with its use of these data and bears all responsibility in determining whether these data are fit for the User's intended use. These data may not have the accuracy, resolution, completeness, timeliness, or other characteristics...
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