This EnviroAtlas dataset contains species richness metrics based on habitat models generated by the U.S. Geological Survey (USGS) National Gap Analysis Project (GAP). 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, 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 24 biodiversity metrics reflecting ecosystem services or other aspects of biodiversity for terrestrial vertebrate species. Metrics include all species richness, taxa specific species richness and other lists identifying species of conservation concern, climate vulnerabilities, etc. This dataset was produced by a joint effort of New Mexico State University, US EPA, and USGS to support research and online mapping activities related to EnviroAtlas. 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).

This map displays the total native aquatic species diversity at the HUC8 watershed level. Made for use within the USDA Forest Service - National Aquatic Biodiversity Assessment Dashboard.The source data for species richness was developed by NatureServe in partnership with the USDA Forest Service - Pacific Northwest Research Station.NatureServe. 2021. NatureServe Network Biodiversity Location Data. NatureServe, Arlington, Virginia. NatureServe. Learn more at https://www.natureserve.org/access-data.

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 14 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).

This map displays the total endangered aquatic species biodiversity at the HUC8 watershed level. Made for use within the USDA Forest Service - National Aquatic Biodiversity Assessment Dashboard.The source data for species richness was developed by NatureServe in partnership with the USDA Forest Service - Pacific Northwest Research Station.NatureServe. 2021. NatureServe Network Biodiversity Location Data. NatureServe, Arlington, Virginia. NatureServe. Learn more at https://www.natureserve.org/access-data.

This data is superseded by the MoBI 2024 data which can be found here.This map displays numbers of species in the lower 48 United States that are protected by the Endangered Species Act and/or considered to be in danger of extinction. It is part of the Map of Biodiversity Importance (MoBI) data collection, a series of maps that identify areas of high importance for protecting species from extinction in the contiguous United States.Building on habitat suitability models for 2,216 of the nation’s most imperiled species, and information on range size and degree of protection derived from those models, the MoBI project provides a series of maps that can help inform conservation efforts. This map depicts richness of Critically Imperiled (categorized by NatureServe as “G1”), Imperiled (“G2”), and ESA-listed (i.e., species listed as Endangered or Threatened under the Endangered Species Act) species in the following groups:Vertebrates (birds, mammals, amphibians, reptiles, freshwater fishes; 309 species) Freshwater invertebrates (mussels and crayfishes; 228 species) Pollinators (bumblebees, butterflies, and skippers; 43 species) Vascular plants (1,636 species)High values identify areas where more imperiled species are most likely to occur.Habitat models for most species were generated using the random forest algorithm. Data to train the models came from the NatureServe Network (e.g. state Natural Heritage Programs) supplemented by data from USGS BISON, and other sources of population and locality data. Environmental predictors used for the modeling include representations of terrain, climate, land cover, soils, and hydrology. The modeling resolution for terrestrial species was either 30 m (most species) or 330 m (some wide-ranging species). Models for aquatic species used the medium resolution National Hydrography Dataset (NHD) as the modeling unit. For species not amenable to random forest modeling, habitat maps were derived by buffering locality data and/or building simple deductive models based on habitat information. NatureServe converted habitat maps to a 990-m raster to provide a consistent unit of aggregation and avoid revealing the precise location of sensitive species. Richness values are simply a tally of the number of species with habitat overlapping a cell.These data layers are intended to identify areas of high potential value for on-the-ground biodiversity protection efforts. As a synthesis of predictive models, they cannot guarantee either the presence or absence of imperiled species at a given location. For site-specific decision-making, these data should be used in conjunction with field surveys and/or documented occurrence data, such as is available from the NatureServe Network.For more information, see:Hamilton, H., Smyth, R.L., Young, B.E., Howard, T.G., Tracey, C., Breyer, S., Cameron, D.R., Chazal, A., Conley, A.K., Frye, C. and Schloss, C. (2022), Increasing taxonomic diversity and spatial resolution clarifies opportunities for protecting imperiled species in the U.S.. Ecological Applications. Accepted Author Manuscript e2534. https://doi.org/10.1002/eap.2534April 2021 Release Note: These data were updated with improved data. 33 species were added to the aggregate result that were previously erroneously excluded. In addition, a minor issue with how the original data were snapped was fixed, ensuring that all species within all of the MOBI layers are aligned consistently, regardless of the layers to which a given species contributes. Results may thus differ somewhat from the February 2020 release.To download data as a layer package, navigate here.

Important Note: This item is in mature support as of September 2023 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The USGS Protected Areas Database of the United States (PAD-US) is the official inventory of public parks and other protected open space. The spatial data in PAD-US represents public lands held in trust by thousands of national, state and regional/local governments, as well as non-profit conservation organizations.GAP 1 and 2 areas are primarily managed for biodiversity, GAP 3 are managed for multiple uses including conservation and extraction, GAP 4 no known mandate for biodiversity protection. Provides a general overview of protection status including management designations. PAD-US is published by the U.S. Geological Survey (USGS) Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity conservation, recreation, public health, climate change adaptation, and infrastructure investment. See the GAP webpage for more information about GAP and other GAP data including species and land cover.The USGS Protected Areas Database of the United States (PAD-US) classifies lands into four GAP Status classes:GAP Status 1 - Areas managed for biodiversity where natural disturbances are allowed to proceedGAP Status 2 - Areas managed for biodiversity where natural disturbance is suppressedGAP Status 3 - Areas protected from land cover conversion but subject to extractive uses such as logging and miningGAP Status 4 - Areas with no known mandate for protectionIn the United States, areas that are protected from development and managed for biodiversity conservation include Wilderness Areas, National Parks, National Wildlife Refuges, and Wild & Scenic Rivers. Understanding the geographic distribution of these protected areas and their level of protection is an important part of landscape-scale planning. Dataset SummaryPhenomenon Mapped: Areas protected from development and managed to maintain biodiversity Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, the Northern Mariana Islands and other Pacific Ocean IslandsVisible Scale: 1:1,000,000 and largerSource: USGS Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP) PAD-US version 3.0Publication Date: July 2022Attributes included in this layer are: CategoryOwner TypeOwner NameLocal OwnerManager TypeManager NameLocal ManagerDesignation TypeLocal DesignationUnit NameLocal NameSourcePublic AccessGAP Status - Status 1, 2, or 3GAP Status DescriptionInternational Union for Conservation of Nature (IUCN) Description - I: Strict Nature Reserve, II: National Park, III: Natural Monument or Feature, IV: Habitat/Species Management Area, V: Protected Landscape/Seascape, VI: Protected area with sustainable use of natural resources, Other conservation area, UnassignedDate of EstablishmentThe source data for this layer are available here. What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter for Gap Status Code = 3 to create a map of only the GAP Status 3 areas.Add labels and set their propertiesCustomize the pop-upArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Note that many features in the PAD-US database overlap. For example wilderness area designations overlap US Forest Service and other federal lands. Any analysis should take this into consideration. An imagery layer created from the same data set can be used for geoprocessing analysis with larger extents and eliminates some of the complications arising from overlapping polygons.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Conservation planning in the Great Plains often depends on understanding the degree of fragmentation of the various types of grasslands and savannas that historically occurred in this region. To define ecological subregions of the Great Plains, we used a revised version of Kuchler’s (1964) map of the potential natural vegetation of the United States. The map was digitized from the 1979 physiographic regions map produced by the Bureau of Land Management, which added 10 physiognomic types. All analyses are based on data sources specific to the United States; hence, we only analyze the portion of the Great Plains occurring in the United States.We sought to quantify the current amount of rangeland in the US Great Plains converted due to 1) woody plant encroachment; 2) urban, exurban, and other forms of development (e.g., energy infrastructure); and 3) cultivation of cropland. At the time of this analysis, the most contemporary measure of land cover across the United States was the 2011 NLCD (Homer et al. 2015). One limitation of the NLCD is that some grasslands with high rates of productivity, such as herbaceous wetlands or grasslands along riparian zones, are misclassified as cropland. A second limitation is the inability to capture cropland conversion occurring after 2011 (Lark et al. 2015). Beginning in 2009 (and retroactively for 2008), the US Department of Agriculture - NASS has annually produced a Cropland Data Layer (CDL) for the United States from satellite imagery, which maps individual crop types at a 30-m spatial resolution. We used the annual CDLs from 2011 to 2017 to map the distribution of cropland in the Great Plains. We merged this map with the 2011 NLCD to evaluate the degree of fragmentation of grasslands and savannas in the Great Plains as a result of conversion to urban land, cropland, or woodland. We produced two maps of fragmentation (best case and worst case scenarios) that quantify this fragmentation at a 30 x 30 m pixel resolution across the US Great Plains, and make them available for download here. Resources in this dataset: Resource title: Data Dictionary for Figure 2 derived land cover of the US portion of the North American Great Plains File name: Figure2_Key for landcover classes.csv Resource title: Figure 1. Potential natural vegetation of US portion of the North American Great Plains, adapted from Kuchler (1964). File name: Figure1_Kuchler_GPRangelands.zip Resource description: Extracted grassland, shrubland, savanna, and forest communities in the US Great Plains from the revised Kuchler natural vegetation map Resource title: Figure 2. Derived land cover of the US portion of the North American Great Plains. File name: Figure2_Key for landcover classes.zip Resource description: The fNLCD-CDL product estimates that 43.7% of the Great Plains still consists of grasslands and shrublands, with the remainder consisting of 40.6% cropland, 4.4% forests, 3.0% UGC, 3.0% developed open space, 2.9% improved pasture or hay fields, 1.2% developed land, 1.0% water, and 0.2% barren land, with important regional and subregional variation in the extent of rangeland loss to cropland, forests, and developed land. Resource title: Figure 3. Variation in the degree of fragmentation of Great Plains measured in terms of distance to cropland, forest, or developed lands. File name: Figure3_bestcase_disttofrag.zip Resource description: This map depicts a “best case” scenario in which 1) croplands are mapped based only on the US Department of AgricultureNational Agricultural Statistics Service Cropland Data Layers (2011e2017), 2) all grass-dominated cover types including hay fields and improved pasture are considered rangelands, and 3) developed open space (as defined by the National Land Cover Database) are assumed to not be a fragmenting land cover type. Resource title: Figure 4. Variation in the degree of fragmentation of Great Plains measured in terms of distances to cropland, forest, or developed lands. File name: Figure4_worstcase_disttofrag.zip Resource description: This map depicts a ‘worst case’ scenario in which 1) croplands are mapped based on the US Department of AgricultureNational Agricultural Statistics Service Cropland Data Layers (2011e2017) and the 2011 National Land Cover Database (NLCD), 2) hay fields and improved pasture are not included as rangelands, and 3) developed open space (as defined by NLCD) is included as a fragmenting land cover type.

This map is displayed in NatureServe's Conservation Data Portal for the Western United States.Building on habitat suitability models for 2,493 of the nation's most imperiled species, and information on range size and degree of protection derived from those models, the MoBI project provides a series of maps that can help inform conservation efforts. This map depicts measurements of Critically Imperiled (categorized by NatureServe as "G1"), Imperiled ("G2"), and ESA-listed (i.e., species listed as Endangered or Threatened under the Endangered Species Act) species in the following groups:Vertebrates (birds, mammals, amphibians, reptiles, freshwater fishes; 333 species)Freshwater invertebrates (mussels and crayfishes; 234 species)Pollinators (bumblebees, solitary bees, butterflies, and skippers; 80 species)Vascular plants (1,957 species)Habitat models for most species were generated using the random forest algorithm. Data to train the models came from the NatureServe Network (e.g. state Natural Heritage Programs) supplemented by data from Global Biodiversity Information Facility, and other publicly available sources of population and locality data. Environmental predictors used for the modeling include representations of terrain, climate, land cover, soils, and hydrology. The modeling resolution for terrestrial species was either 30-m (most species) or 330-m (some wide-ranging species). Models for aquatic species used the medium resolution National Hydrography Dataset (NHD) as the modeling unit. For species not amenable to random forest modeling, habitat maps were derived by buffering locality data and/or building simple deductive models based on habitat information. NatureServe converted habitat maps to a 330-m raster to provide a consistent unit of aggregation and avoid revealing the precise location of sensitive species.Richness of Imperiled Species:This measure depicts the richness of Critically Imperiled (categorized by NatureServe as “G1”), Imperiled (“G2”), and ESA-listed (i.e., species listed as Endangered or Threatened under the Endangered Species Act) species. High values identify areas where more imperiled species are most likely to occur.The Richness of Imperiled Species view for the Western US used in this map can be found here.The full extent of Richness of Imperiled Species for the lower 48 United States can be found on Living Atlas here and downloaded as a layer package here.Range Size Rarity:Range-size rarity for each species is the inverse of the total area mapped as habitat. This measure is the sum of the range-size rarity values for all species with habitat that overlaps a cell. High values identify where species with very small ranges (and thus fewer places where they can be conserved) are likely to occur; the presence of multiple imperiled species contributes to higher scores.The Range Size Rarity view for the Western US used in this map can be found here.The full extent of Range Size Rarity for the lower 48 United States can be found on Living Atlas here and downloaded as a layer package here.Protection Weighted Range Size Rarity (PWRSR):This measure combines information on both range-size rarity and the degree to which habitat for the species is protected. Protected habitat was defined as that occurring within protected areas managed for biodiversity (i.e., Gap Status 1 and 2 lands in the USGS Protected Areas Database; PAD-US 4.0). Each species was assigned a PWRSR score equal to the product of range-size rarity and the percent of habitat that is unprotected. The PWRSR raster sums these scores for all species with habitat that overlaps a cell. High values identify areas where unprotected, restricted-range species are likely to occur. These areas are of interest to conservationists due to both the restricted range sizes and need for protection from threats such as habitat loss.The Protection Weighted Range Size Rarity view for the Western US used in this map can be found here.The full extent of PWRSR for the lower 48 United States can be found on Living Atlas here and downloaded as a layer package here.Areas of Unprotected Biodiversity Importance (AUBI):This displays areas of unprotected biodiversity importance (AUBIs) for imperiled species. Values of "1" identify areas where under-protected and range-restricted species are most likely to occur, including areas where the presence of multiple imperiled species contributes to higher scores. These areas are of interest to conservationists due to both the restricted range sizes and need for protection from threats such as habitat loss.The AUBI view for the Western US used in this map can be found here.The full extent of AUBI for the lower 48 United States can be found on Living Atlas here and downloaded as a layer package here.For more information, see:Hamilton, H., Smyth, R.L., Young, B.E., Howard, T.G., Tracey, C., Breyer, S., Cameron, D.R., Chazal, A., Conley, A.K., Frye, C. and Schloss, C. (2022), Increasing taxonomic diversity and spatial resolution clarifies opportunities for protecting imperiled species in the U.S.. Ecological Applications. Accepted Author Manuscript e2534.https://doi.org/10.1002/eap.2534Note that the above citation is based on the MoBI 2020 product and does not reflect the most current information. Please contact NatureServe for more information.

This EnviroAtlas dataset describes the native freshwater aquatic biodiversity by 12-digit HUC (subwatershed) for the conterminous United States. It includes amphibians, fish, mollusks, decapods, and turtles. The metrics are: total species richness; count of threatened and endangered species; a rarity index; and a native vulnerability index. This dataset was produced by the US EPA to support research and online mapping activities related to the EnviroAtlas. 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).

Maps of predicted total species richness (fish, mussels, and crayfish) and predicted richness of globally rare, threatened, and endangered species for Missouri.

This dataset was produced by a joint effort of New Mexico State University (NMSU), the U.S. Environmental Protection Agency (EPA), and the U.S. 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 bird species. Metrics include all bird species richness, lists identifying species of conservation concern, climate vulnerabilities, etc. This dataset was produced by the Center for Applied Spatial Ecology, New Mexico Cooperative Fish and Wildlife Unit (NMCFWRU), NMSU to support research and online mapping activities related to EnviroAtlas. 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 Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.Terrestrial and Freshwater Data• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels, such that the spatial features of CPAD correspond to ownership boundaries. • The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity. Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership. • The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such, boundaries represented within it may not align with other data sources. • Numerous datasets representing designated boundaries for entities such as National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas, and others, were downloaded from publicly available sources, typically hosted by the managing agency.Methodology1. CPAD and CCED represent the most accurate location and ownership information for parcels in California which contribute to the preservation of open space and cultural and biological resources.2. Superunits are collections of parcels (Holdings) within CPAD which share a name, manager, and access policy. Most Superunits are also managed with a generally consistent strategy for biodiversity conservation. Examples of Superunits include Yosemite National Park, Giant Sequoia National Monument, and Anza-Borrego Desert State Park. 3. Some Superunits, such as those owned and managed by the Bureau of Land Management, U.S. Forest Service, or National Park Service , are intersected by one or more designations, each of which may have a distinct management emphasis with regards to biodiversity. Examples of such designations are Wilderness Areas, Wild and Scenic Rivers, or National Monuments.4. CPAD Superunits and CCED easements were intersected with all designation boundary files to create the operative spatial units for conservation analysis, henceforth 'Conservation Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit. 5. Each Conservation Unit was intersected with the PAD-US dataset in order to determine the management emphasis with respect to biodiversity, i.e., the GAP code. Because PAD-US is national in scope and not specifically parcel aligned with California assessors' surveys, a direct spatial extraction of GAP codes from PAD-US would leave tens of thousands of GAP code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single GAP code was uniformly assigned that code. Additionally, the total area of GAP codes 1 and 2 were summed for the remaining uncoded Conservation Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2. 6. Subsequent to this stage of analysis, certain Conservation Units remained uncoded, either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset. 7. These uncoded Conservation Units were then broken down into their constituent, finer resolution Holdings, which were then analyzed according to the above workflow. 8. Areas remaining uncoded following the two-step process of coding at the Superunit and then Holding levels were assigned a GAP code of 4. This is consistent with the definition of GAP Code 4: areas unknown to have a biodiversity management focus. 9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.Tracking Conserved AreasThe total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing improvements in our understanding of existing biodiversity conservation efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data. CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review. The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

Human activities alter ecosystems everywhere, causing rapid biodiversity loss and biotic homogenization. These losses necessitate coordinated conservation actions guided by biodiversity and species distribution spatial data that cover large areas yet have fine-enough resolution to be management-relevant (i.e., ≤ 5 km). However, most biodiversity products are too coarse for management or are only available for small areas. Furthermore, many maps generated for biodiversity assessment and conservation do not explicitly quantify the inherent tradeoff between resolution and accuracy when predicting biodiversity patterns. Our goals were to 1) generate predictive models of overall breeding bird species richness and species richness of different guilds based on nine functional or life history-based traits across the conterminous US at three resolutions (0.5, 2.5, and 5 km), and 2) quantify the tradeoff between resolution and accuracy, and hence relevance for management, of the resulting biodiversity maps. We summarized eighteen years of North American Breeding Bird Survey data (1992-2019) and modeled species richness using random forests, including 66 predictor variables (describing climate, vegetation, geomorphology, and anthropogenic conditions), 20 of which we newly derived. Among the three spatial resolutions, the percent variance explained ranged from 27% to 60% (median = 54%; mean = 57%) for overall species richness and 12% to 87% (median = 61%; mean = 58%) for our different guilds. Overall species richness and guild-specific species richness were best explained at 5-km resolution using approximately 24 predictor variables based on percent variance explained, symmetric mean absolute percentage error, and root mean squared error values. However, our 2.5-km resolution maps were almost as accurate and provided more spatially detailed information, which is why we recommend them for most management applications. Our results represent the first consistent, occurrence-based, and nationwide maps of breeding bird richness with a thorough accuracy assessment that are also spatially detailed enough to inform local management decisions. More broadly, our findings highlight the importance of explicitly considering tradeoffs between resolution and accuracy to create management-relevant biodiversity products for large areas.

Important Note: This item is in mature support as of June 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.In the United States, areas that are protected from development and managed for biodiversity conservation include Wilderness Areas, National Parks, National Wildlife Refuges, and Wild & Scenic Rivers. Understanding the geographic distribution of these protected areas and their level of protection is an important part of landscape-scale planning. The Protected Areas Database of the United States classifies lands into four GAP Status classes. This layer displays the two highest levels of protection GAP Status 1 and 2. These two classes are commonly referred to as protected areas.Dataset SummaryPhenomenon Mapped: Areas protected from development and managed to maintain biodiversity (GAP Status 1 and 2)Units: MetersCell Size: 30.92208102 metersSource Type: ThematicPixel Type: 8-bit unsigned integerData Coordinate System: WGS 1984Mosaic Projection: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, Guam, Northern Mariana Islands and American Samoa.Source: USGS National Gap Analysis Program PAD-US version 3.0Publication Date: July 2022ArcGIS Server URL: https://landscape10.arcgis.com/arcgis/This layer displays protected areas from the Protected Areas Database of the United States version 3.0 created by the USGS National Gap Analysis Program. This layer displays GAP Status 1, areas managed for biodiversity where natural disturbances are allowed to proceed or are mimicked by management, and GAP Status 2, areas managed for biodiversity where natural disturbance is suppressed. The source data for this layer are available here. A feature layer published from this dataset is also available. The polygon vector layer was converted to raster layers using the Polygon to Raster Tool using the National Elevation Dataset 1 arc second product as a snap raster.The service behind this layer was published with 8 functions allowing the user to select different views of the service. Other layers created from this service using functions include:USA Protected from Land Cover ConversionUSA Unprotected AreasUSA Protected Areas - Gap Status 1-4USA Protected Areas - Gap Status 1USA Protected Areas - Gap Status 2USA Protected Areas - Gap Status 3USA Protected Areas - Gap Status 4What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "Protected Areas" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "Protected Areas" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

This map displays areas of unprotected biodiversity importance (AUBIs) for species in the lower 48 United States that are protected by the Endangered Species Act and/or considered to be in danger of extinction. It is part of the Map of Biodiversity Importance (MoBI) data collection, a series of maps that identify areas of high importance for protecting species from extinction in the contiguous United States.Building on habitat suitability models for 2,493 of the nation’s most imperiled species, and information on range size and degree of protection derived from those models, the MoBI project provides a series of maps that can help inform conservation efforts. This map depicts areas of unprotected biodiversity importance (AUBIs) - that is, areas that scored highest for summed protection-weighted range-size rarity (PWRSR) for Critically Imperiled (categorized by NatureServe as “G1”), Imperiled (“G2”), and ESA-listed (i.e., species listed as Endangered or Threatened under the Endangered Species Act) species in the following groups:Vertebrates (birds, mammals, amphibians, reptiles, freshwater fishes; 326 species) Freshwater invertebrates (mussels and crayfishes; 233 species) Pollinators (bumblebees, solitary bees, butterflies, and skippers; 63 species) Vascular plants (1,871 species)Values of "1" identify areas where under-protected and range-restricted species are most likely to occur, including areas where the presence of multiple imperiled species contributes to higher scores. These areas are of interest to conservationists due to both the restricted range sizes and need for protection from threats such as habitat loss.Habitat models for most species were generated using the random forest algorithm. Data to train the models came from the NatureServe Network (e.g. state Natural Heritage Programs) supplemented by data from Global Biodiversity Information Facility, and other publicly available sources of population and locality data. Environmental predictors used for the modeling include representations of terrain, climate, land cover, soils, and hydrology. The modeling resolution for terrestrial species was either 30-m (most species) or 330-m (some wide-ranging species). Models for aquatic species used the medium resolution National Hydrography Dataset (NHD) as the modeling unit. For species not amenable to random forest modeling, habitat maps were derived by buffering locality data and/or building simple deductive models based on habitat information. NatureServe converted habitat maps to a 330-m raster to provide a consistent unit of aggregation and avoid revealing the precise location of sensitive species. Range-size rarity for each species in the inverse of the total area mapped as habitat (using the 330-m raster). Protection-weighted range-size rarity (PWRSR) maps combine information on both range-size rarity and the degree to which habitat for the species in protected. Protected habitat was defined as that occurring within protected areas managed for biodiversity (i.e., Gap Status 1 and 2 lands in the USGS Protected Areas Database; PAD-US 4.0). Each species was assigned a PWRSR score equal to the product of range-size rarity and the percent of habitat that is unprotected. The PWRSR raster sums these scores for all species with habitat that overlaps a cell. We delineated AUBIs by then selecting all pixels where summed PWRSR ≥ 0.0005, an inclusive value designed to highlight areas of conservation value. A PWRSR score of 0.0005 corresponds to a single species with a range of 1,000 km2 that is 50% unprotected, a single species with a range of 20 km2 that is 1% unprotected, or multiple co-occurring species with lower PWRSR scores. Not that full protected species do not contribute to PWRSR scores.These data layers are intended to identify areas of high potential value for on-the-ground biodiversity protection efforts. As a synthesis of predictive models, they cannot guarantee either the presence or absence of imperiled species at a given location. For site-specific decision-making, these data should be used in conjunction with field surveys and/or documented occurrence data, such as is available from the NatureServe Network.For more information, see:Hamilton, H., Smyth, R.L., Young, B.E., Howard, T.G., Tracey, C., Breyer, S., Cameron, D.R., Chazal, A., Conley, A.K., Frye, C. and Schloss, C. (2022), Increasing taxonomic diversity and spatial resolution clarifies opportunities for protecting imperiled species in the U.S.. Ecological Applications. Accepted Author Manuscript e2534. https://doi.org/10.1002/eap.2534Note that the above citation is based on the MoBI 2020 product and does not reflect the most current information. Please contact NatureServe for more information.This data supersedes the MoBI 2020 data which can be found here. A summary of changes between MoBI 2020 and 2024:Species included: MoBI 2024 includes 2,493 species, compared to 2,216 in MoBI 2024. Due to a combination of taxonomic updates and global rank/ESA status changes, 177 species from the 2020 product were removed while 454 species were added to this 2020 product. All taxonomic groups included in MoBI 2020 are included in the 2024 product, with the addition of several solitary bee genera.Scale changes: We increased the resolution from 990-m to 330-m for all MoBI products. Due to this resolution increase, we recommend caution conducting direct comparisons between the MoBI 2020 and MoBI 2024 products.To download data as a layer package, navigate here.

The Terrestrial 30x30 Conserved Areas map layer was developed by the CA Nature working group, providing a statewide perspective on areas managed for the protection or enhancement of biodiversity. Understanding the spatial distribution and extent of these durably protected and managed areas is a vital aspect of tracking and achieving the “30x30” goal of conserving 30% of California's lands and waters by 2030.

Terrestrial and Freshwater Data
• The California Protected Areas Database (CPAD), developed and managed by GreenInfo Network, is the most comprehensive collection of data on open space in California. CPAD data consists of Holdings, a single parcel or small group of parcels which comprise the spatial features of CPAD, generally corresponding to ownership boundaries.

• The California Conservation Easement Database (CCED), managed by GreenInfo Network, aggregates data on lands with easements. Conservation Easements are legally recorded interests in land in which a landholder sells or relinquishes certain development rights to their land in perpetuity.
Easements are often used to ensure that lands remain as open space, either as working farm or ranch lands, or areas for biodiversity protection. Easement restrictions typically remain with the land through changes in ownership.

•The Protected Areas Database of the United States (PAD-US), hosted by the United States Geological Survey (USGS), is developed in coordination with multiple federal, state, and non-governmental organization (NGO) partners. PAD-US, through the Gap Analysis Project (GAP), uses a numerical coding system in which GAP codes 1 and 2 correspond to management strategies with explicit emphasis on protection and enhancement of biodiversity. PAD-US is not specifically aligned to parcel boundaries and as such,
boundaries represented within it may not align with other data sources.

• Numerous datasets representing designated boundaries for entities such as
National Parks and Monuments, Wild and Scenic Rivers, Wilderness Areas,
and others, were downloaded from publicly available sources, typically
hosted by the managing agency.

Methodology
1.CPAD and CCED represent the most accurate location and ownership information for
parcels in California which contribute to the preservation of open space
and cultural and biological resources.

2. Superunits are collections of parcels (Holdings) within CPAD which share a name,
manager, and access policy. Most Superunits are also managed with a
generally consistent strategy for biodiversity conservation. Examples of
Superunits include Yosemite National Park, Giant Sequoia National
Monument, and Anza-Borrego Desert State Park.

3. Some Superunits, such as those owned and managed by the Bureau of Land
Management, U.S. Forest Service, or National Park Service , are
intersected by one or more designations, each of which may have a
distinct management emphasis with regards to biodiversity. Examples of
such designations are Wilderness Areas, Wild and Scenic Rivers, or
National Monuments.

4. CPAD Superunits and CCED easements were
intersected with all designation boundary files to create the operative
spatial units for conservation analysis, henceforth 'Conservation
Units,' which make up the Terrestrial 30x30 Conserved Areas map layer. Each easement was functionally considered to be a Superunit.

5. Each Conservation Unit was intersected with the PAD-US dataset in order to
determine the management emphasis with respect to biodiversity, i.e.,
the GAP code. Because PAD-US is national in scope and not specifically
parcel aligned with California assessors' surveys, a direct spatial
extraction of GAP codes from PAD-US would leave tens of thousands of GAP
code data slivers within the 30x30 Conserved Areas map. Consequently, a generalizing approach was adopted, such that any Conservation Unit with greater than 80% areal overlap with a single
GAP code was uniformly assigned that code. Additionally, the total area
of GAP codes 1 and 2 were summed for the remaining uncoded Conservation
Units. If this sum was greater than 80% of the unit area, the Conservation Unit was coded as GAP 2.

6.Subsequent to this stage of analysis, certain Conservation Units remained uncoded,
either due to the lack of a single GAP code (or combined GAP codes 1&2) overlapping 80% of the area, or because the area was not sufficiently represented in the PAD-US dataset.

7.These uncoded Conservation Units were then broken down into their
constituent, finer resolution Holdings, which were then analyzed
according to the above workflow.

8. Areas remaining uncoded following the two-step process of coding at the Superunit and
then Holding levels were assigned a GAP code of 4. This is consistent
with the definition of GAP Code 4: areas unknown to have a biodiversity
management focus.

9. Greater than 90% of all areas in the Terrestrial 30x30 Conserved
Areas map layer were GAP coded at the level of CPAD Superunits intersected by designation boundaries, the coarsest land units of analysis. By adopting these coarser analytical units, the Terrestrial 30X30 Conserved Areas map layer avoids hundreds of thousands of spatial slivers that result from intersecting designations with smaller, more numerous parcel records. In most cases, individual parcels reflect the management scenario and GAP status of the umbrella Superunit and other spatially coincident designations.

10. PAD-US is a principal data source for understanding the spatial distribution of GAP coded lands, but it is national in scope, and may not always be the most current source of data with respect to California holdings. GreenInfo Network, which develops and maintains the CPAD and CCED datasets, has taken a lead role in establishing communication with land stewards across California in order to make GAP attribution of these lands as current and accurate as possible. The tabular attribution of these datasets is analyzed in addition to PAD-US in order to understand whether a holding may be considered conserved.

Tracking Conserved Areas
The total acreage of conserved areas will increase as California works towards its 30x30 goal. Some changes will be due to shifts in legal protection designations or management status of specific lands and waters. However, shifts may also result from new data representing
improvements in our understanding of existing biodiversity conservation
efforts. The California Nature Project is expected to generate a great deal of excitement regarding the state's trajectory towards achieving the 30x30 goal. We also expect it to spark discussion about how to shape that trajectory, and how to strategize and optimize outcomes. We encourage landowners, managers, and stakeholders to investigate how their lands are represented in the Terrestrial 30X30 Conserved Areas Map Layer. This can be accomplished by using the Conserved Areas Explorer web application, developed by the CA Nature working group. Users can zoom into the locations they understand best and share their expertise with us to improve the data representing the status of conservation efforts at these sites. The Conserved Areas Explorer presents a tremendous opportunity to strengthen our existing data infrastructure and the channels of communication between land stewards and data curators, encouraging the transfer of knowledge and improving the quality of data.

CPAD, CCED, and PAD-US are built from the ground up. Data is derived from available parcel information and submissions from those who own and manage the land. So better data starts with you. Do boundary lines require updating? Is the GAP code inconsistent with a Holding’s conservation status? If land under your care can be better represented in the Terrestrial 30X30 Conserved Areas map layer, please use this link to initiate a review.The results of these reviews will inform updates to the California Protected Areas Database, California Conservation Easement Database, and PAD-US as appropriate for incorporation into future updates to CA Nature and tracking progress to 30x30.

A map showing the Ecological Drainage Units (EDUs) of Missouri.

GAP distribution models represent the areas where species are predicted to occur based on habitat associations. GAP distribution models are the spatial arrangement of environments suitable for occupation by a species. In other words, a species distribution is created using a deductive model to predict areas suitable for occupation within a species range. To represent these suitable environments, GAP compiled existing GAP data, where available, and compiled additional data where needed. Existing data sources were the Southwest Regional Gap Analysis Project (SWReGAP) and the Southeast Gap Analysis Project (SEGAP) as well as a data compiled by Sanborn Solutions and Mason, Bruce and Girard. Habitat associations were based on land cover data of ecological systems and--when applicable for the given taxon--on ancillary variables such as elevation, hydrologic characteristics, human avoidance characteristics, forest edge, ecotone widths, etc. Distribution models were generated using a python script that selects model variables based on literature cited information stored in a wildlife habitat relationship database (WHRdb); literature used includes primary and gray publications. Distribution models are 30 meter raster data and delimited by GAP species ranges. Distribution model data were attributed with information regarding seasonal use based on GAP regional projects (NWGAP, SWReGAP, SEGAP, AKGAP, HIGAP, PRGAP, and USVIGAP), NatureServe data, and IUCN data. A full report documenting the parameters used in each species model can be found via: http://gis1.usgs.gov/csas/gap/viewer/species/Map.aspx Web map services for species distribution models can be accessed from: http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Birds http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Mammals http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Amphibians http://gis1.usgs.gov/arcgis/rest/services/NAT_Species_Reptiles A table listing all of GAP's available web map services can be found here: http://gapanalysis.usgs.gov/species/data/web-map-services/ GAP used the best information available to create these species distribution models; however GAP seeks to improve and update these data as new information becomes available. Recommended citation: U.S. Geological Survey Gap Analysis Program (USGS-GAP). [Year]. National Species Distribution Models. Available: http://gapanalysis.usgs.gov. Accessed [date].

The "Distribution of EMAP Grid Hexagons and Points for Biodiversity Research" data sets are available at:

'http://www.nr.usu.edu/docs/archive/archive.html'

Three README files of documentation are available in this directory describing the coverage, projection, and content of the data sets. The following was abstracted from the first README file included in the directory:

"This is the first of five files for distribution of the EMAP 635 square kilometer grid hexagons and points for application in biodiversity research. Two additional README files explain various aspects of the grid and its distribution. The file 'ushexes.geo' contains the set of tessellation hexagon boundaries for the conterminous United States. The file 'uspoints.geo' contains the center points of the hexagons. As we have proposed for the national biodiversity and landscape assessment, these hexagons (and the point grid from which they are derived) are taken from the so-called "unrandomized" version of the EMAP grid."

A map showing number and percentage of native fish, mussel, and crayfish species that have less than two distinct occurrences with the GAP management-status 1 or 2 lands of each Ecological Drainage Unit (EDU).