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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,...
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 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...
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/.
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.
This map shows the current predicted distribution of Lucy's Warbler, along with current and near-term status and long term potential for change. 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...
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.
Geospatial data sets for the Wyoming Basin REA spatially quantify explicit cumulative effects and provide a broad-scale ecological context for decision-making and planning that cannot be determined using local-level information.
This dataset shows point locations and data specific to wildlife guzzlers in Sonoran Desert ecoregion.
The potential effect of development on patch size was used as an index of fragmentation. Patch size was quantified for relatively undeveloped patches (Terrestrial Development Index scores less than or equal to 1 percent) of sagebrush steppe. Because TDI is calculated for a 2.25 km radius moving window, relatively undeveloped patches are defined at this analysis scale. Patch sizes for relatively undeveloped areas can then be compared to baseline conditions.
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.
Average percent of land cover accounted for by herbaceous cover in the Wyoming Basins Ecoregional Assessment area (5 km scale), a summary of the percent cover of herbaceous cover produced by Homer and others, 2012 (Homer, C. G., C. L. Aldridge, D. K. Meyer, and S. J. Schell. 2012. Multi scale remote sensing sagebrush characterization with regression trees over Wyoming, USA: laying a foundation for monitoring. International Journal of Applied Earth Observation and Geoinformation. 14: 233 to 244.), by running the focalsum command in ArcGIS Spatial Analyst
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...
Core area risk is classified by the percent of aspen that is core area, summarized by township. Core area was defined as aspen greater than 60 m from nonforest edges and roads or railroads.
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...
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