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This raster dataset represents the boundaries of the hydrogeologic areas of the Southwest Principal Aquifer (SWPA) study of the National Water Quality Assessment (NAWQA) program. It is a compilation of the pre-existing Hydrogeologic Areas of the Southwest Ground-Water Resources Project, with additional data from the Central and Coastal basins of California, Northern New Mexico Rio Grande Valley, and South Central Colorado San Luis Valley.
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...
This dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and current climate (1950-1999 average) , and then projecting that niche into the future. The future timeslices used are 2020's, which is an average of 2020-2029, and 2050's which is 2050-2059. The Values 1-6 show the degree of model agreement (For example: areas with a value of 1 is where only 1 GCM predicted suitability; pixels with a value of 6 are where 6 GCMs predicted suitability, ect). *see Maxent output pdfs for more details about model inputs and settings.
This dataset contains values on the potential number of visitors via in year ~2030 who are hikers/cyclists. This assumes a "push" factor of the number of recreationists is equal to 20.9% of population in the CBR/MBR region, which is the average participation rate of off-road recreation usage of both metro and non-metro residents of AZ, CA, NV, and UT from the National survey on recreation and the environment. Cordell et al. 2008. Visitation is assume to decline in half with each 1 hour of travel time.
This dataset represents the location and class density of potential annual grass risk within the Central Great Basin and Mojave Basin Ecoregion for the 2010 time period. This model represent a composite of multiple inductive (Maximum Entropy) models of varying annual grass cover using non-spectral landscape variables. Input Variables: elevation, aspect, distance to fire, geology, distance to hydric soils, distance to intermitant streams, landform, ombrotype, distance to perrenial streams, soil pH, density of primary roads, density of secondary/local roads, percent sandy soil, slope, thermotype. Classification of Model 0-No/Low Risk 1- < 5% Cover Risk 2- 5%-15% Cover Risk 3 - 15%-25% Cover Risk 4 - 25%-45% Cover...
This dataset represents the probability of occurrence for the sand dunes and sandy soils species assemblage within the Central Great Basin and Mohave Basin Ecoregion. This model represents the composite of multiple cross-validated inductive (Maximum Entropy) models of species distributions using non-spectral landscape variables. Input Variables: Elevation, NatureServe's ecological systems map, soil pH, percentage of coarse sands within soils, percentage of total sands within soil, distance to hydric soils, slope, geology, aspect, and available water holding capacity. Classification Model: 1 - High Potential Habitat NoData - Very Low Habitat Potential or "Non-Habitat"
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 data set contains distribution information for all terrestrial and aquatic reptiles, crocodilians, and turtles occurring in the United States and Canada.
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
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,...
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