{80560C72-C9B8-4CBB-B480-CE8A39167E58} eng; USA utf8 dataset EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact 2017-05-22 ISO 19115 Geographic Information - Metadata ISO 19115:2003/Cor.1:2006(E) EnviroAtlas - Biodiversity Metrics by 12-digit HUC for the Southwestern United States 2015-05-07 publication U.S. EPA Office of Research & Development (ORD) - National Exposure Research Laboratory (NERL) Research Triangle Park NC publisher Center for Applied Spatial Ecology, NMCFWRU, NMSU originator This EnviroAtlas dataset was produced by a joint effort of New Mexico State University, US EPA, and the US Geological Survey (USGS) to support research and online mapping activities related to EnviroAtlas. Ecosystem services, i.e., services provided to humans from ecological systems, have become a key issue of this century in resource management, conservation planning, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national interests for integrating ecology with economics to help understand the effects of human policies and actions and their subsequent impacts on both ecosystem function and human well-being. Some aspects of biodiversity are valued by humans in varied ways, and thus are important to include in any assessment that seeks to identify and quantify the benefits of ecosystems to humans. Some biodiversity metrics clearly reflect ecosystem services (e.g., abundance and diversity of harvestable species), whereas others may reflect indirect and difficult to quantify relationships to services (e.g., relevance of species diversity to ecosystem resilience, or cultural and aesthetic values). Wildlife habitat has been modeled at broad spatial scales and can be used to map a number of biodiversity metrics. We map 15 biodiversity metrics reflecting ecosystem services or other aspects of biodiversity for all vertebrate species except fish. Metrics include species richness for all vertebrates, specific taxon groups, harvestable species (i.e., waterfowl, furbearers, small game, and big game), threatened and endangered species, and state-designated species of greatest conservation need, as well as a metric for ecosystem (i.e., land cover) diversity. The EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets). The biodiversity metrics were created from grouping 817 single species habitat models created by the USGS Gap Analysis Program into smaller, ecologically-based, phylogeny-based, or stakeholder-suggested composites. This data could be used in conjunction with other biodiversity data or ecosystem service data to identify concordance and discordance between metrics. Areas of concordance highlight the similarity between the two metrics. Areas of discordance highlight dissimilar areas, but must then be reviewed to understand why the dissimilarity occurs. The overall goal of EnviroAtlas is to employ and develop the best available science to map indicators of ecosystem services production, demand, and drivers for the nation. METRIC DESCRIPTION Land Cover Diversity: Number of land cover types within a 1-km neighborhood by pixel. Land cover diversity can be an indicator of the diversity of ecosystems present within a given area. High numbers can indicate a system with a mosaic of differing ecosystems, which can indicate a biologically diverse area that has important bearing on biodiversity conservation. Areas with a high number of land cover types can be important attributes relative to recreational use or aesthetic values. Total Vertebrate Species Richness: Number of terrestrial vertebrate species (i.e., amphibians, birds, mammals, reptiles) as measured by predicted habitat present within a pixel. Total Vertebrate Species Richness can be used to characterize an area of interest. Total Vertebrate Species Richness can be indicative of recreational opportunities or aesthetic qualities. Vertebrate species such as big game and birds are often mentioned in tourist brochures to highlight the recreational opportunities available within an area. Total Vertebrate Species Richness has been used as an indicator of the biodiversity conservation potential of an area and considered an important indicator of biodiversity 'hot spots.' This metric is important to ecological service categories related to biodiversity conservation and recreation, culture, and aesthetics. Bat Species Richness: Number of bat species as measured by predicted habitat present within a pixel. Bat Species Richness provides an important metric to characterize an area of interest. Bats are known to provide valuable pest control and pollination services. This metric is important to ecological service categories related to biodiversity conservation and food, fuel, and materials. Amphibian Species Richness: Number of amphibian species as measured by predicted habitat present within a pixel. Amphibian Species Richness provides a characterization of the area of interest. In the last 20 years, amphibian declines have become a national focus. The reasons are varied, but amphibians can act as important sentinels for water quality and can highlight the negative effects of pollution and pesticides in our streams and rivers. This metric is important to ecological service categories related to biodiversity conservation and recreation, culture, and aesthetics. Mammal Species Richness: Number of mammal species as measured by predicted habitat present within a pixel. Mammal Species Richness provides a characterization of the area of interest. Mammals include many large, charismatic species such as Elk and Deer, but also provide some of the main prey items for carnivorous wildlife. This metric is important to ecological service categories related to biodiversity conservation and recreation, culture, and aesthetics. Total Harvestable Species Richness: Total Harvestable Species Richness identifies the number of harvestable terrestrial vertebrate species (defined by state hunting regulations), as measured by predicted habitat present within a pixel. This metric is important to ecological service categories related to food, fuel and materials and recreation, culture, and aesthetics. These species are regulated by state wildlife agencies in Arizona, Colorado, Nevada, New Mexico and Utah. Harvestable species are an important source of food and revenue in many states. Wildlife agencies in many states rely on proceeds from hunting licenses to fund conservation activities within the state. Hunting also provides a significant source of recreation along with supplying food. Small Game Species Richness: Small Game Species Richness identifies the number of small game species as measured by predicted habitat present within a pixel. This metric is important to ecological service categories related to food, fuel and materials and recreation, culture, and aesthetics. Examples include sandhill crane, scaled quail and dusky grouse. These species are regulated by state wildlife agencies in Arizona, Colorado, Nevada, New Mexico and Utah. Big Game Species Richness: Big Game Species Richness identifies the number of big game species as measured by predicted habitat present within a pixel. This metric is important to ecological service categories related to food, fuel and materials and recreation, culture, and aesthetics. These species are regulated by state wildlife agencies in Arizona, Colorado, Nevada, New Mexico and Utah. These species also represent watchable wildlife. Species include elk, mule deer, and pronghorn. Furbearer Species Richness: Furbearer Species Richness identifies the number of furbearer species as measured by predicted habitat present within a pixel. This metric is important to ecological service categories related to food, fuel and materials and recreation, culture, and aesthetics. These species are regulated by state wildlife agencies in Arizona, Colorado, Nevada, New Mexico and Utah. These species are often trapped for the main purpose of the fur trade. Species include beaver, badger, and marten. Waterfowl Species Richness: Waterfowl Species Richness identifies the number of waterfowl species as measured by predicted habitat present within a pixel. This metric is important to ecological service categories related to food, fuel and materials and recreation, culture, and aesthetics. These species are regulated by state wildlife agencies in Arizona, Colorado, Nevada, New Mexico and Utah. The species include ducks and geese. Also, revenue is generated from the sale of "duck stamps" as a federal license required for hunting migratory waterfowl. Birders may also purchase these stamps to gain free access to national wildlife refuges. Modeled Threatened And Endangered Vertebrate Species: Number of Federally listed Threatened and Endangered (T&E) Species as measured by predicted habitat present within a pixel (US Fish and Wildlife Service [USFWS], 2011). This metric is important to ecological service categories related to biodiversity conservation and recreation, culture, and aesthetics. These species are regulated by the USFWS as required by the Endangered Species Act. completed EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact asNeeded Ecosystem Environment theme EPA GIS Keyword Thesaurus 12-digit HUCs Biodiversity Biota Conservation Ecology Ecosystem Services Endangered EnviroAtlas Environment Environmental Atlas Habitat Land Land Cover Modeling Natural Resources Recreation Supply of Ecosystem Services Threatened Species theme EnviroAtlas Arizona Colorado Nevada New Mexico United States Utah place None https://edg.epa.gov/EPA_Data_License.html otherRestrictions Use Constraints: None. Please check sources, scale, accuracy, currency and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the EPA would be appreciated. otherRestrictions Access Constraints: None PUBLIC https://project-open-data.github.io/schema/#accessLevel Standard Technical Controls eng; USA environment -122.0670 -100.7463 28.9403 44.1821 2013-03-25 This EnviroAtlas dataset is based on data originally developed using a version of the Watershed Boundary Dataset (WBD 2011) extracted for EnviroAtlas on March 22, 2011. In 2015, EnviroAtlas transitioned from the WBD 2011 to a newer version - the National Hydrography Dataset Plus (NHDPlus) V2 WBD Snapshot, EnviroAtlas version - which includes updated 12-digit HUC boundaries for the Conterminous United States. This EnviroAtlas dataset was created by reallocating the original WBD 2011 dataset to the NHDPlus V2 WBD Snapshot using area-weighted reallocation. The area weighting process assumes that values are distributed evenly across HUCs. In cases where values are unevenly distributed within a HUC, this can result in misallocated values in the new dataset. Therefore, users should exercise caution when interpreting this data, especially in regions where there are significant changes to the 12-digit HUCs. The majority of spatial changes between the two 12-digit HUC versions took place along the California coast, in Minnesota, and along the US-Canada border, especially in New England. Metric values for most of the rest of the United States are essentially unchanged. If the user is interested in data for a specific small area, especially in areas that were modified, using the original WBD 2011 version of this dataset joined with the WBD 2011 boundary feature class should provide accurate metric values. As new versions of the dataset are developed using the 2015 HUCs, these will replace the reallocated datasets in EnviroAtlas. Before reallocating the metrics, edits were made to the area of some 12-digit HUCs. For example, along the coast of California some 12-digit HUCs had stopped at the coastline in the WBD 2011 dataset but were extended into the ocean in the NHDPlus V2 dataset. Instead of reallocating the metrics using the total area of the NHDPlus V2 HUCs, the land area based on National Land Cover Database (NLCD) 2011 was used to update the land area values. This ensured the land area of the NHDPlus V2 HUCs roughly matched the land area of the WBD 2011 HUCs. This method helped avoid incorrectly distributing terrestrial metrics, such as including the new ocean-extended area in the denominator of values that were originally calculated using land-only area as the denominator, which would result in artificially lowering the values of per-unit area metrics in the ocean-extended HUCs. true Entity and Attribute Information Entity and Attribute Overview: The mean, maximum, and Index of Average for each biodiversity metric were estimated using Southwest Regional Gap Analysis Project terrestrial vertebrate habitat models for each 12-digit HUC in the Southwestern U.S. For the Southwest, each species model was reclassed to either suitable (1) or not suitable (0) habitat. For each respective metric, species comprising that metric were combined by summing pixel values over the entire Southwest project area. Thus, a 30-m resolution grid dataset was created for all metrics. The mean value was calculated by averaging pixel values within each 12-digit HUC. The maximum value was determined by identifying the pixel in the HUC with the highest species richness. The Normalized Index of Biodiversity (Avg_i) is a normalized value that was calculated by dividing each pixel value (species richness) by the value of the highest species richness pixel within the study area (the contiguous U.S.). This value was then averaged across the 12-digit HUC. The normalized value provides a method to compare this metric with other biodiversity metrics. Entity and Attribute Detail Citation: https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas distributor https://edg.epa.gov/data/PUBLIC/ORD/ENVIROATLAS/National download Download The URL providing direct access to the downloadable dataset. download https://enviroatlas.epa.gov/arcgis/rest/services/National/National2016_master/MapServer ESRI:ArcGIS API The endpoint of a web service to access the dataset (REST endpoint, WMS GetCapabilities URL, or a SOAP WSDL endpoint). webMapService https://www.epa.gov/enviroatlas/enviroatlas-data information Documentation URL for accessing related documents such as data dictionary, technical information about a dataset, developer documentation, etc. information https://www.epa.gov/enviroatlas information Home Page Alternative landing page used to redirect user to a contextual, Agency-hosted "homepage" for the Dataset or API information dataset Horizontal Positional Accuracy Report Data were collected using methods that have unknown accuracy (EPA National Geospatial Data Policy [NGDP] Accuracy Tier 10). For more information, please see EPA's NGDP at https://epa.gov/geospatial/policies.html Features represented have not been tested for completeness Features represented have not been tested for completeness Tests for integrity have not been performed. This lineage was generated by the FGDC CSDGM to 19139 transformation Individual habitat models obtained from http://swregap.nmsu.edu/ 2013-03-25T00:00:00 Recoded models to binary with 1 for habitat present and 0 for habitat absent. 2013-03-25T00:00:00 Species lists for biodiversity metrics were created. 2013-03-25T00:00:00 Species models for each list were combined and the sum of species with potential habitat was calculated using ArcGIS cell statistics. 2013-03-25T00:00:00 Reallocated values from the original March 22 2011 WBD to the NHDPlus V2 WBD Snapshot, EnviroAtlas version for the Conterminous United States using area-weighted redistribution. 2015-04-28T00:00:00 unknown 2021-05-22 This metadata was automatically generated from the FGDC Content Standard for Digital Geospatial Metadata standard (version FGDC-STD-001-1998) using the 2024-02-09T11:11:00 version of the FGDC CSDGM to ISO 19139 transform. EnviroAtlas Coordinator U.S. Environmental Protection Agency, Office of Research and Development-Sustainable and Healthy Communities Research Program, EnviroAtlas Geospatial Data Owner (919) 541-3832 109 T.W. Alexander Drive Research Triangle Park NC 27709 EnviroAtlas@epa.gov https://www.epa.gov/enviroatlas pointOfContact