The USGS Protected Areas Database of the United States (PAD-US) is the nation's inventory of protected areas, including public open space and voluntarily provided, private protected areas, identified as an A-16 National Geospatial Data Asset in the Cadastral Theme (http://www.fgdc.gov/ngda-reports/NGDA_Datasets.html). PAD-US is an ongoing project with several published versions of a spatial database of areas dedicated to the preservation of biological diversity, and other natural, recreational or cultural uses, managed for these purposes through legal or other effective means. The geodatabase maps and describes public open space and other protected areas. Most areas are public lands owned in fee; however, long-term easements, leases, and agreements or administrative designations documented in agency management plans may be included. The PAD-US database strives to be a complete “best available” inventory of protected areas (lands and waters) including data provided by managing agencies and organizations. The dataset is built in collaboration with several partners and data providers (http://gapanalysis.usgs.gov/padus/stewards/). See Supplemental Information Section of this metadata record for more information on partnerships and links to major partner organizations. As this dataset is a compilation of many data sets; data completeness, accuracy, and scale may vary. Federal and state data are generally complete, while local government and private protected area coverage is about 50% complete, and depends on data management capacity in the state. For completeness estimates by state: http://www.protectedlands.net/partners. As the federal and state data are reasonably complete; focus is shifting to completing the inventory of local gov and voluntarily provided, private protected areas. The PAD-US geodatabase contains over twenty-five attributes and four feature classes to support data management, queries, web mapping services and analyses: Marine Protected Areas (MPA), Fee, Easements and Combined. The data contained in the MPA Feature class are provided directly by the National Oceanic and Atmospheric Administration (NOAA) Marine Protected Areas Center (MPA, http://marineprotectedareas.noaa.gov ) tracking the National Marine Protected Areas System. The Easements feature class contains data provided directly from the National Conservation Easement Database (NCED, http://conservationeasement.us ) The MPA and Easement feature classes contain some attributes unique to the sole source databases tracking them (e.g. Easement Holder Name from NCED, Protection Level from NOAA MPA Inventory). The "Combined" feature class integrates all fee, easement and MPA features as the best available national inventory of protected areas in the standard PAD-US framework. In addition to geographic boundaries, PAD-US describes the protection mechanism category (e.g. fee, easement, designation, other), owner and managing agency, designation type, unit name, area, public access and state name in a suite of standardized fields. An informative set of references (i.e. Aggregator Source, GIS Source, GIS Source Date) and "local" or source data fields provide a transparent link between standardized PAD-US fields and information from authoritative data sources. The areas in PAD-US are also assigned conservation measures that assess management intent to permanently protect biological diversity: the nationally relevant "GAP Status Code" and global "IUCN Category" standard. A wealth of attributes facilitates a wide variety of data analyses and creates a context for data to be used at local, regional, state, national and international scales. More information about specific updates and changes to this PAD-US version can be found in the Data Quality Information section of this metadata record as well as on the PAD-US website, http://gapanalysis.usgs.gov/padus/data/history/.) Due to the completeness and complexity of these data, it is highly recommended to review the Supplemental Information Section of the metadata record as well as the Data Use Constraints, to better understand data partnerships as well as see tips and ideas of appropriate uses of the data and how to parse out the data that you are looking for. For more information regarding the PAD-US dataset please visit, http://gapanalysis.usgs.gov/padus/. To find more data resources as well as view example analysis performed using PAD-US data visit, http://gapanalysis.usgs.gov/padus/resources/. The PAD-US dataset and data standard are compiled and maintained by the USGS Gap Analysis Program, http://gapanalysis.usgs.gov/ . For more information about data standards and how the data are aggregated please review the “Standards and Methods Manual for PAD-US,” http://gapanalysis.usgs.gov/padus/data/standards/ .

Data available online through the Arkansas Spatial Data Infrastructure (ASDI) at http://gis.arkansas.gov. The subject file represents the Arkansas portion of areas to be submerged derived from 1:100,000-scale (""intermediate-scale"") Digital Line Graph data created by the USGS. Digital Line Graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 1:100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management planimetric maps at a scale of 1:100,000 are used. Intermediate-scale DLG's are broken down into five categories: 1. Public Land survey, 2. boundaries, 3. transportation 4. hydrography, and 5. hypsography.

Data available online through the Arkansas Spatial Data Infrastructure (ASDI) at http://gis.arkansas.gov. The subject file represents the Arkansas portion of power line routes derived from 1:100,000-scale (""intermediate-scale"") Digital Line Graph data created by the USGS. Digital Line Graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 1:100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management planimetric maps at a scale of 1:100,000 are used. Intermediate-scale DLG's are broken down into five categories: 1. Public Land survey, 2. boundaries, 3. transportation 4. hydrography, and 5. hypsography.

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe's Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe's Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Raster data in both ArcGIS Grid and ERDAS Imagine format is available for download at http://gis1.usgs.gov/csas/gap/viewer/land_cover/Map.aspx Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS. In adition to the raster datasets the data is available in Web Mapping Services (WMS) format for each of the six NVC classification levels (Class, Subclass, Formation, Division, Macrogroup, Ecological System) at the following links. http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Class_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Subclass_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Formation_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Division_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_NVC_Macrogroup_Landuse/MapServer http://gis1.usgs.gov/arcgis/rest/services/gap/GAP_Land_Cover_Ecological_Systems_Landuse/MapServer

Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

The county boundary is a publication of polygons of all counties in Arkansas. It represents the contemporary boundary of each county as established or altered by various Acts of the Arkansas Legislature. The database provides location, and population information for use in local and regional cartographic and spatial analysis applications.When necessary the data were adjusted to conform to known physical features recited in the Acts. This dataset does not represent exact legal boundaries as per surveyed description, but, rather a set of boundaries used for the administrative purposes that conforms to logical & administrative rules. These polygons may be edited for the purpose of small spatial alignment changes based on new, enhanced or improved supporting base map data, such as orthoimagery, public land survey system (PLSS), or precision PLSS corner control data that improves the spatial accuracy of the existing geometry.

FOR non-AGOL ACCOUNT HOLDERS, DOWNLOAD THIS GEOSPATIAL DATA HERE: https://gis-fws.opendata.arcgis.com/search?tags=lmvjvThese boundaries are simplified from the U.S. Fish and Wildlife Service Real Estate Interest data layer containing polygons representing tracts of land (parcels) in which the Service has a real estate interest. Interior boundaries between parcels were dissolved to produce a single set of simplified external boundaries for each feature. These are resource grade mapping representations of the U.S. Fish and Wildlife Service boundaries. For legal descriptions of the land represented here, contact the USFWS Realty Office. This map layer was compiled by the U.S. Fish and Wildlife Service. Although these boundaries represent lands administered by the U.S. Fish and Wildlife Service, not all areas are open to the public. Some fragile habitats need to be protected from human traffic and some management areas are closed. The public is urged to contact specific Refuges or other conservation areas before visiting.

The 2019 cartographic boundary KMLs are simplified representations of selected geographic areas from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). These boundary files are specifically designed for small-scale thematic mapping. When possible, generalization is performed with the intent to maintain the hierarchical relationships among geographies and to maintain the alignment of geographies within a file set for a given year. Geographic areas may not align with the same areas from another year. Some geographies are available as nation-based files while others are available only as state-based files. The records in this file allow users to map the parts of Urban Areas that overlap a particular county. After each decennial census, the Census Bureau delineates urban areas that represent densely developed territory, encompassing residential, commercial, and other nonresidential urban land uses. In general, this territory consists of areas of high population density and urban land use resulting in a representation of the ""urban footprint."" There are two types of urban areas: urbanized areas (UAs) that contain 50,000 or more people and urban clusters (UCs) that contain at least 2,500 people, but fewer than 50,000 people (except in the U.S. Virgin Islands and Guam which each contain urban clusters with populations greater than 50,000). Each urban area is identified by a 5-character numeric census code that may contain leading zeroes. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The generalized boundaries for counties and equivalent entities are as of January 1, 2010.

These data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 500,000-plus point and polygon mine symbols from approximately 67,000 maps of 22 western states has been completed: Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Idaho (ID), Iowa (IA), Kansas (KS), Louisiana (LA), Minnesota (MN), Missouri (MO), Montana (MT), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Oregon (OR), South Dakota (SD), Texas (TX), Utah (UT), Washington (WA), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the western U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done.

The groundwater-level change maps for the Sparta-Memphis aquifer are constructed as a point-to-point comparison between wells measured in both 2013 and 2015. Wells not measured in both 2013 and 2015 were not included in the change maps construction. The 2013-2015 change map contains 241 corresponding wells. Groundwater-level differences were calculated by subtracting 2013 groundwater-level measurements, in feet below land surface from the 2015 groundwater-level measurements, in feet below land surface.

These polygons represents areas .5 acres and greater where edits to the County Boundary were made for the purpose of small spatial alignment changes based on new, enhanced or improved supporting base map data, such as orthoimagery, public land survey system (PLSS), or precision PLSS corner control data that improves the spatial accuracy of the existing geometry.

This mapping project is a collaboration among the U.S. Fish and Wildlife Service (Service) and staff from the Arkansas Game and Fish and Natural Heritage Commissions. It provides general information on the potential environmental risk to species of concern and sensitive habitats from proposed wind energy projects in Arkansas. The purpose of the map is to assist wind energy developers with appropriate siting of proposed wind energy projects as described in the Service’s 2012 Land-Based Wind Energy Guidelines (Land-Based Wind Energy Guidelines | FWS.gov), particularly during Tiers 1 (Preliminary Site Evaluation) and 2 (Site Characterization) of the decision framework. The map provides general guidance and should not be used for final decision-making. According to the Land-Based Wind Energy Guidelines, environmental risks include direct impacts e.g., collisions with turbines and associated infrastructure, habitat loss or degradation from turbines and infrastructure, habitat fragmentation, displacement or behavioral changes, and indirect impacts e.g., reduced nesting and breeding densities and the social ramifications of those reductions, loss or modification of foraging habitat, loss of population vigor and overall population density, increased isolation between habitat patches, loss of habitat refugia; attraction to modified habitats, effects on behavior, physiological disturbance, and habitat unsuitability. The assigned environmental risk categories and corresponding colors presented in the map represent the Service’s estimation of the relative environmental risk to species of concern and sensitive habitats within an area. Regardless of the environmental risk associated with a particular area, wind energy developers should coordinate with the Service and other appropriate Federal and State agencies and follow the Land-Based Wind Energy Guidelines to inform the siting and development of any proposed wind energy project. The boundaries of various layers on the map do not necessarily reflect the mobility of a species of concern, or the potential for interaction with a wind project. In all cases, Tiers 1 and 2 of the decision framework are recommended to ensure that no known species of concern or sensitive habitats will be impacted by the proposed project. If Tier 1 or 2 reveal potential impacts to species of concern or sensitive habitats, then Tier 3 (Field Studies to Document Site Wildlife and Habitat and Predict Project Impacts) of the decision framework may be needed. For the purpose of this project, species of concern include the following: Federally listed species, migratory birds including areas with high densities of migratory waterfowl, Bald and Golden Eagles, state wildlife action plan terrestrial species, and G1–3 plant species. Other areas identified as having environmental risk include Arkansas Natural Heritage Commission Natural Areas, glades, and areas designated as critical habitat for Federally listed species.

The dataset is comprised of three geojson files containing: (1) training points for a Land Use/Land Cover (LULC) classification with 8 LULC classes, (2) test points for a LULC classification LULC classes, and (3) evaluation points for a Wetland map derived from the LULC classifications, with 5 classes. The methodology to which this points were generated is described on a paper pending to be published.

Yearly trendGrassland and savanna area declined by 0.31% per year from 2011-2021. Area declined in most counties (76%). Increases typically occurred in counties with major ecosystem-based restoration efforts (e.g., range-wide longleaf pine, woodlands in Missouri and Arkansas.)On track to meet SECAS goalNo. The decline of about 1.24% every 4 years is not enough to reach the SECAS goal of a 1% increase every 4 years.Data sourceModeled indicator based on National Land Cover Database (NLCD) land cover and canopy cover, LANDFIRE Biophysical Settings, Texas Ecological Mapping Systems, Oklahoma Ecological Systems Map. The model starts with areas that were historically grassland or savanna based on LANDFIRE. It then uses landcover and canopy cover to identify current area for each year. For areas of historic grassland, it uses a canopy cover threshold of 0%. For areas of historic savanna, it uses a canopy cover threshold of 60%. In Texas and Oklahoma, we further reduced the estimate by removing mesquite-invaded areas that weren’t currently functioning as grassland or savanna. This approach is similar to parts of the grasslands and savannas Blueprint indicator, but includes a number of changes more focused on trend estimation.Confidence in trendHigh. Trend is statistically significant and shows consistent declines across all five years with data (2011, 2013, 2016, 2019, 2021).InterpretationThis is a coarse indicator of the overall extent of grassland and savanna. It includes a wide range of quality, from restored areas and remnants, to temporary grasslands created by forestry, to highly altered areas of pasture. The steep declines mirror large declines seen in species that depend on grasslands and savannas, like pollinators and grassland birds. Grassland declines throughout the SECAS region are occurring on both public and private lands.For most SECAS states, the major source of grassland and savanna loss was excess tree growth. The exceptions to this were: 1) Missouri, where the biggest loss was to row crop, and 2) Texas and Florida, where the biggest loss was to urban growth. Despite steep declines, improvements in places like the longleaf pine range, historic woodlands in Missouri and Arkansas, and tallgrass prairie in Northeast Oklahoma show that focused conservation attention can reverse declines in specific places.Other information availableTabular data associated with the chart above are available in Appendix I of the pdf report: https://secassoutheast.org/pdf/SECAS-goal-report-2024.pdf.

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Citation: Horton, John D., and San Juan, Carma A., 2019, Prospect- and Mine-Related Features from U.S. Geological Survey 7.5- and 15-Minute Topographic Quadrangle Maps of the United States (ver. 4.0, November 2019): U.S. Geological Survey data release, https://doi.org/10.5066/F78W3CHG.Version 4.0 of these data are part of a larger USGS project to develop an updated geospatial database of mines, mineral deposits and mineral regions in the United States. Mine and prospect-related symbols, such as those used to represent prospect pits, mines, adits, dumps, tailings, etc., hereafter referred to as “mine” symbols or features, are currently being digitized on a state-by-state basis from the 7.5-minute (1:24,000-scale) and the 15-minute (1:48,000 and 1:62,500-scale) archive of the USGS Historical Topographic Maps Collection, or acquired from available databases (California and Nevada, 1:24,000-scale only). Compilation of these features is the first phase in capturing accurate locations and general information about features related to mineral resource exploration and extraction across the U.S. To date, the compilation of 637,000-plus point and polygon mine symbols from approximately 88,000 maps across 35 states has been completed: Alabama (AL), Arizona (AZ), Arkansas (AR), California (CA), Colorado (CO), Florida (FL), Georgia (GA), Idaho (ID), Iowa (IA), Illinois (IL), Indiana (IN), Kansas (KS), Kentucky (KY), Louisiana (LA), Michigan (MI), Minnesota (MN), Mississippi (MS), Missouri (MO), Montana (MT), North Carolina (NC), North Dakota (ND), Nebraska (NE), New Mexico (NM), Nevada (NV), Oklahoma (OK), Ohio (OH), Oregon (OR), South Carolina (SC), South Dakota (SD), Tennessee (TN), Texas (TX), Utah (UT), Washington (WA), Wisconsin (WI), and Wyoming (WY). The process renders not only a more complete picture of exploration and mining in the U.S., but an approximate time line of when these activities occurred. The data may be used for land use planning, assessing abandoned mine lands and mine-related environmental impacts, assessing the value of mineral resources from Federal, State and private lands, and mapping mineralized areas and systems for input into the land management process. The data are presented as three groups of layers based on the scale of the source maps. No reconciliation between the data groups was done. Datasets were developed by the U.S. Geological Survey Geology, Geophysics, and Geochemistry Science Center (GGGSC). Compilation work was completed by USGS student contractors: Germán Schmeda, Patrick C. Scott, William Gnesda, Margaret Hammond, Tyler Reyes, Morgan Mullins, Thomas Carroll, Margaret Brantley, and Logan Barrett; and by USGS personnel Damon Bickerstaff, Stuart A. Giles and E.G. Boyce. First release: August 4, 2016 Revised: December 1, 2017 (ver. 1.0) Revised: April 30, 2018 (ver. 2.0) Revised: April 10, 2019 (ver. 3.0) Revised: November 25, 2019 (ver.4.0)