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The Utah Well & Spring database contains data of 2981 wells, springs, and miscellaneous sites such as collector wells and mines. It is available from the Utah Geological Survey at:http://geology.utah.gov/emp/geothermal/wells_springs_database.htmThe Conservation Biology Institute selected geothermal wells from this database. The geothermal well layer was then used in further analysis and modeling.
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.
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/.
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.
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.
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.
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
Foothills Aspen Distribution Functional Type no null values
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.
Ranks of landscape level ecological risks for pygmy rabbit, summarized by township, in the Wyoming Basin Rapid Ecoregional Assessment project area. Landscape level risk based on Terrestrial Development Index (TDI). Risk classes based on mean TDI score by township. Lowest risk corresponds to TDI less than 1, medium risk corresponds to TDI 1 to 3, Highest risk corresponds TDI greater than 3. See table 27.3 and appendix in the Wyoming Basin REA report at http://pubs.er.usgs.gov/publication/ofr20151155 for additional details.
The potential effect of development on patch size was used as an index of fragmentation. Patch size was quantified for baseline conditions for pygmy rabbit. This provides a reference for comparing patch size for relatively undeveloped patches (Terrestrial Development Index scores less than or equal to 1 percent) of pygmy rabbit.
This dataset approximates areas available for utility-grade solar energy development under the Solar Energy Zone Alternative of the Solar Energy Development Programmatic Environmental Impact Statement (PEIS). Refer to the Solar Energy Development PEIS for more details.
This dataset shows the distribution of investigated and proposed hydroelectric source sites.
Most communities in the western and interior parts of the state rely primarily on electricity generated with diesel fuel. These communities had the most expensive electricity in 2011. Most remote rural communities are eligible for the Power Cost Equalization (PCE) program instituted by the state to offset the high fuel prices in these communities. The program pays 95% of residential electricity cost However, the program has not been fully funded by the Legislature in 15 out of its 25 years of existence, and electricity rates in rural Alaska with PCE are still higher than in urban Alaska. There has been a recent dramatic increase in fuel prices throughout Alaska. This dataset shows the change in price of a gallon...
The potential effect of development on patch size was used as an index of fragmentation. Patch size was quantified for baseline conditions for Greater Sage Grouse. This provides a reference for comparing patch size for relatively undeveloped patches (Terrestrial Development Index scores less than or equal to 1 percent).
Fifth-level watersheds (HUC10) with high or very high conservation potential for at least one aquatic species evaluated as a Conservation Element by land ownership and protection from PADUS.
Rather than using the ARDF to determine future mining activity, which is a work in progress we used additional datasets. Future mines are difficult to predict but we used three datasets to represent future mining activity: Ambler mining belt, Nanushuk coal mine, and USGS mineral potential GIS database (Jones et al. 2015). Jones et al. (2015) documented the potential and certainty of six minerals deposit groups. The mineral resource potential datasets produced by the USGS (Jones et al. 2015) was used in conjunction with access to identify areas with the most likely long-term future mining activity. Mineral resource potential datasets only cover a portion of our study area (63.9% or 252,845 km2) but can still provide...
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