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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...
The Alaska Exotic Plants Information Clearinghouse (AKEPIC) is a database and mapping application that provide geospatial information for non-native plant species in Alaska and Canada. These products are the result of an ongoing cooperation between the United States Forest Service, National Park Service, Bureau of Land Management, Fish and Wildlife Service, Department of Natural Resources Plant Material Center and Alaska Natural Heritage Program in support of the Alaska Committee for Noxious and Invasive Plants Management (CNIPM) and the Strategic Plan for Noxious and Invasive Plants Management in Alaska. The Alaska Natural Heritage Program administers the mapping application, database and website associated with...
This layer represents the scorecard of one indicator of ecosytem integrity. This ecosystem assessment is for SNK 2010 landscape condtion (LCM). 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 integrity at broader scales.
This layer represents the scorecard of one indicator of ecosytem integrity. This ecosystem assessment is for SNK 2010 landscape condtion (LCM). 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 integrity at broader scales.
This data set contains vector lines and polygons representing the shoreline and coastal habitats of Western Alaska classified according to the Environmental Sensitivity Index (ESI) classification system. This data set comprises a portion of the ESI for Western Alaska. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.
Types: Downloadable;
Tags: BLM,
Bureau of Land Management,
Coastal Zone Management,
Coastal resources,
DOI,
Some of the SNK 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. - Low gradient streams were defined as streams of third order or higher with gradient less than two percent. A raster stream network was created using ArcHydro's terrain preprocessing tools and a detailed description of the steps are included in the metadata and model for headwater streams. The stream network was separated...
Some of the SNK 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 dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and baseline climate conditions, and then projecting these correlations 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 1-5 show...
Summary list of rare plant species for SNK REA, prepared by NatureServe from sensitive plant data provided by the Alaska Natural Heritage Progra, (AKNHP). AKNHP maintains georeferenced G3-G1 vascular plant collection locations for AK.
This layer represents the scorecard of one indicator of ecosytem integrity. This ecosystem assessment is for SNK 2010 landscape condtion (LCM). 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 integrity at broader scales.
This layer represents the scorecard of one indicator of ecosytem integrity. This ecosystem assessment is for SNK 2010 landscape condtion (LCM). 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 integrity at broader scales.
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.
This dataset depicts polygons of white-tailed prairie dog colonies in Colorado digitized from figure 1 in the White-tailed Prairie Dog Conservation Assessment (Seglund et al. 2004). This dataset should be used with caution because there were few reference points to use during georeferencing. The original GIS data should be obtained directly from Seglund et al. if possible.
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 dataset represents the probability of occurrence for the noncarbonate alpine 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, geology, NatureServe's ecological systems map, distance to calcium carbonate soils, soil pH, slope, and aspect. Classification Model: 1 - High Potential Habitat NoData - Very Low Habitat Potential or "Non-Habitat"
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 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...
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