In 2023, Washington, D.C. had the highest population density in the United States, with 11,130.69 people per square mile. As a whole, there were about 94.83 residents per square mile in the U.S., and Alaska was the state with the lowest population density, with 1.29 residents per square mile. The problem of population density Simply put, population density is the population of a country divided by the area of the country. While this can be an interesting measure of how many people live in a country and how large the country is, it does not account for the degree of urbanization, or the share of people who live in urban centers. For example, Russia is the largest country in the world and has a comparatively low population, so its population density is very low. However, much of the country is uninhabited, so cities in Russia are much more densely populated than the rest of the country. Urbanization in the United States While the United States is not very densely populated compared to other countries, its population density has increased significantly over the past few decades. The degree of urbanization has also increased, and well over half of the population lives in urban centers.

The 2015 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 boundaries for counties and equivalent entities are as of January 1, 2010.

General and winter distribution of Black Bear. Distribution is not mapped in National Parks and Indian Reservations.

description: The 2016 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.; abstract: The 2016 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.

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.

This form and associated feature layer contain points collected by Glacier National Park (Montana) Citizen Science volunteers and staff to document pika detections, talus habitat and genetic sample collection between 2023 to present. This Citizen Science form enables volunteers and park staff to record pika habitat data and record pellet collection while in the field. It includes questions regarding survey conditions (weather, date, number of people present, etc.), habitat information, pellet collection, contains a feature layer map to mark observer location as well as animal habitat location, and an exit page inquiring about time to complete survey and hiking distance. This survey is intended for use within Glacier National Park, Montana for the 2024 summer field season. This project was created using Survey123 and is managed by the Glacier National Park Citizen Science team in the Crown of the Continent Research Learning Center. The resulting data from submitted surveys is used to compile final reports regarding pika habitat within the park, baseline population estimates, and geographic distribution. Collected pellets are also processed for laboratory genetic analysis. Data is collected by citizen science volunteers and student and service groups. Data is QA/QC’d by Glacier National Park Citizen Science staff and backed up monthly.Basic Purpose: 2024 Glacier National Park Citizen Science Pika Pellet Collection survey form for population, habitat, and distribution estimates as well as genetic exploration.Dataset Format: Form and feature layerTime period: Data collected between 2023 to presentThe corresponding NPS DataStore on Integrated Resource Management Applications (IRMA) reference is Glacier National Park Pika Pellet Citizen Science

This layer contain points collected by Glacier National Park (Montana) Citizen Science volunteers and staff to document pika detections, talus habitat and genetic sample collection between 2023 to present. This Citizen Science WebMap enables volunteers to locate pika sites and determine what has been surveyed and areas that remain untouched. This map and associated survey is intended for use within Glacier National Park, Montana for the 2024 summer field season. This project was created using Survey123 and is managed by the Glacier National Park Citizen Science team in the Crown of the Continent Research Learning Center. The resulting data from submitted surveys is used to compile final reports regarding pika habitat within the park, baseline population estimates, and geographic distribution. Collected pellets are also processed for laboratory genetic analysis. Data is collected by citizen science volunteers and student and service groups. Data is QA/QC’d by Glacier National Park Citizen Science staff and backed up monthly.Basic Purpose: 2024 Glacier National Park Citizen Science Pika Pellet Collection survey form for population, habitat, and distribution estimates as well as genetic exploration.Dataset Format: Form and feature layerTime period: Data collected between 2023 to presentThe corresponding NPS DataStore on Integrated Resource Management Applications (IRMA) reference is Glacier National Park Pika Pellet Citizen Science

Idaho:Greater Sage-Grouse Management Areas (habitat) in the Proposed Plan of the Great Basin Region, Idaho-SW Montana Sub-region, Greater Sage-grouse Environmental Impact Statement (EIS) as Priority, Important, and General. Management Areas were delineated by BLM, U.S. Forest Service, State of Idaho and the U.S. Fish and Wildlife Service based on considerations of sage-grouse occupancy, landscape, habitat and land use/adaptive management opportunities.This data was developed as the Administrative Draft Proposed Plan (ADPP) for the Great Basin Region, Idaho-SW Montana Sub-region, Greater Sage-grouse (Centrocercus urophasianus) Environmental Impact Statement (EIS). This layer was edited 5/7/2015 at the WO direction to add three areas of non-habitat in the Sagebrush Focal Areas as PHMA. See procesing steps. UPDATEAs of 09/17/2015, the areas of PHMA that were originally non-habitat in Sagebrush Focal Areas were removed from this dataset if they fell on NFS lands.Priority Habitat Management Areas (PHMA) have the highest conservation value based on various sage-grouse population and habitat considerations and reflect the most restrictive management designed to promote sage-grouse conservation. Important Habitat Management Areas (IHMA) are closely aligned with PHMA, but management is somewhat less restrictive, providing additional management flexibility. The General Habitat Management Areas (GHMA) designation is the least restrictive due to generally lower occupancy of sage-grouse and more marginal habitat conditions.A decision was made in September 2014 by the Washington Office that all sub-regions would use a consistent naming convention for identifying Habitat Management Areas (HMA). These are Priority Habitat Management Area (PHMA) and General Habitat Management Area (GHMA). The Idaho and Southwestern Montana sub-region has an additional HMA identified as Important Habitat Management Area (IHMA). Attributes in this layer were updated 9/26/2014. Core updated to PHMA, Important updated to IHMA, and General updated to GHMA.The layer was renamed from ManagementZones_Alt_G_05272014_Final to ManagementAreas_Alt_G_05272014_final. The field identifying the Management Areas was renamed from Management_Zone to Habitat_Management_Area.ManagementAreas_Alt_G_05272014_final renamed to Habitat_ADPP on 01212015This habitat data provided for Alt G for the IDMT EIS has been clipped to the official IDMT FS GRSG EIS boundaries.Nevada / California:Full description of base data available at: http://www.blm.gov/nv/st/en/prog/more_programs/geographic_sciences/gis/geospatial_data.htmlThis data has been isolated to NFS lands within the official NV/CA FS GRSG EIS boundaries.NW Colorado:This dataset is a combination of the General and Priority habitat component files that were provided to the FS. The following is the metdata associated with that data. This dataset does not include linkages, and has been isolated to NFS lands within the official NWCO FS GRSG EIS boundaries.Greater sage-grouse GIS data set identifying Preliminary Priority Habitat (PPH) and Preliminary General Habitat (PGH) within Colorado. This data is a combination of mapped grouse occupied range, production areas, and modeled habitat (summer, winter, and breeding).PPH is defined as areas of high probability of use (summer or winter, or breeding models) within a 4 mile buffer around leks that have been active within the last 10 years. Isolated areas with low activity were designated as general habitat.PGH is defined as Greater sage-grouse Occupied Range outside of PPH.Datasets used to create PPH and PGH:Summer, winter, and breeding habitat models. Rice, M. B., T. D. Apa, B. L. Walker, M. L. Phillips, J. H. Gammonly, B. Petch, and K. Eichhoff. 2012. Analysis of regional species distribution models based on combined radio-telemetry datasets from multiple small-scale studies. Journal of Applied Ecology in review.Production Areas are defined as 4 mile buffers around leks which have been active within the last 10 years (leks active between 2002-2011).Occupied range was created by mapping efforts of the Colorado Division of Wildlife (now Colorado Parks and Wildlife –CPW) biologists and district officers during the spring of 2004, and further refined in early 2012. Occupied Habitat is defined as areas of suitable habitat known to be used by sage-grouse within the last 10 years from the date of mapping. Areas of suitable habitat contiguous with areas of known use, which do not have effective barriers to sage-grouse movement from known use areas, are mapped as occupied habitat unless specific information exists that documents the lack of sage-grouse use. Mapped from any combination of telemetry locations, sightings of sage grouse or sage grouse sign, local biological expertise, GIS analysis, or other data sources. This information was derived from field personnel. A variety of data capture techniques were used including the SmartBoard Interactive Whiteboard using stand-up, real-time digitizing atvarious scales (Cowardin, M., M. Flenner. March 2003. Maximizing Mapping Resources. GeoWorld 16(3):32-35).Update August 2012: This dataset was modified by the Bureau of Land Management as requested by CPW GIS Specialist, Karin Eichhoff. Eichhoff requested that this dataset, along with the GrSG managment zones (population range zones) dataset, be snapped to county boundaries along the UT-CO border and WY-CO border. The county boundaries dataset was provided by Karin Eichhoff. In addition, a few minor topology errors were corrected where PPH and PGH were overlapping.Update October 10, 2012: NHD water bodies greater than 100 acres were removed from GrSG habitat, as requested by Jim Cagney, BLM CO Northwest District Manager. 6 water bodies in total were removed (Hog Lake, South Delaney, Williams Fork Reservoir, North Delaney, Wolford Mountain Reservoir (2 polygons)). There were two “SwampMarsh” polygons that resulted when selecting polygons greater than 100 acres; these polygons were not included. Only polygons with the attribute “LakePond” were removed from GrSG habitat. Utah:This data set was created to facilitate the BLM Greater Sage-Grouse Land Use Planning Strategy in the Utah Sub-Region. This data was developed and addressed, and used during preparation of an environmental impact statement to consider amendments to 14 BLM land use plans throughout the State of Utah, as well as 6 Forest Service land use plans. This planning process was initiated through issuance of a Notice of Intent published on December 6, 2011. This dataset is associated with the Final Environmental Impact Statement, released to the public via a Notice of Availability on May 29, 2015. The purpose of the planning process is to address protection of greater sage-grouse, in partial response to a March 2010 decision by the U.S. Fish and Wildlife Service (FWS) that found the greater sage-grouse was eligible for listing under the authorities of the Endangered Species Act. The planning process will prepare a draft environmental impact statement (DEIS) and final environmental impact statement (FEIS) in close coordination with the US Forest Service, which is a cooperating agency on this planning effort. The planning effort will address the adequacy of regulatory mechanisms found in the land use plans, and will address the myriad threats to grouse and their habitat that were identified by the FWS.The data include the identification of priority and general habitat management areas, as well as a portion occupied habtiat within the planning area identified as neither priority or general. Definitions of priority and general, as well as the management associated with each, is located in the Final EIS.This dataset has been isolated to NFS lands within the official UT FS GRSG EIS boundaries.Wyoming:This dataset shows the proposed Greater Sage-grouse Prioirity Habitat Management Areas (PHMA) (including Priority-Core and Priority-Connectivity) and General Habitat Management Areas (GHMA) for Alternative E within the Wyoming 9-Plan FS GRSG EIS boundaries. It was built, using the "Preliminary Priority and General Habitat, 2012" dataset ("No Action" data) as a base. Alterations were made to reflect proposed changes under Alternative E in the WY 9-Plan GRSG EIS, which included adding areas of proposed 'Priority-Core' and 'Priority-Connectivity' (both delineations considered as PHMA), predominately within areas previously categorized as 'General' habitat.Please refer to the bottom of this section for more details on the data and workflow used in altering the 'No Action' data for Alternative E. This layer was initially completed on 08/27/2014, and later finalized for publication and distribution on 10/01/2015.The metadata associated with the Wyoming portion of the "Preliminary Priority and General Habitat, 2012" dataset is listed below:Wyoming –PPHand PGH: FINAL DRAFT; Developed by the Wyoming Governor’s Sage-Grouse Implementation Team and Wyoming Game and Fish Department in cooperation with Wyoming BLM (PGH modified from Distribution of Sage-Grouse in North America. Schroeder et al., 2004).Alterations were only made to areas on the Bridger-Teton NF and the Thunder Basin NG. The following data was supplied:From the BTNF: (1) BT_added_occupied.shp; (2) BTProposedCoreSG_April2014.shpFrom TBNG: (1) ProposedSageGrouseCore.shpThe following general steps were taken to complete this dataset:1. The 'BT_added_occupied' dataset was merged with the existing PGH data from the "Preliminary Priority and General Habitat, 2012" dataset. In places where the 'BT_added_occupied' data intersected exiting PPH or the proposed core or connectivity data, the PPH/core/connectivity delineation was maintained. 2. The 'BTProposedCoreSG_April2014' and 'ProposedSageGrouseCore' datasets were added to the existing PPH data from the "Preliminary Priority and General Habitat, 2012" dataset. Any overlap in the proposed core or connectivity data with existing

Map of gray wolf and red wolf current and historic range and suitable habitat across the U.S. and Mexico. Produced by Defenders of Wildlife (2021). All data sources listed below:Gray Wolf:Historic Range: The historic range for the gray wolf was delineated with the help of peer reviewed sources: Rutledge et al. 2010. Genetic and morphometric analysis of sixteenth century Canis skull fragments: implications for historic eastern and gray wolf distribution in North America.Current Range: Range delineation was based on range data from IUCN and USFWS, expert knowledge, and personal communications from Defenders of Wildlife field teams, academia, and federal agencies. Details of delineations focused mostly on the United States and Mexico as ranges north of that couldn’t be confirmed due to controversies.Suitable Habitat:Bennett, L.E. 1994. Colorado Gray Wolf Recovery: A biological feasibility study. Final Report. U.S. Fish and Wildlife Service and University of Wyoming Fish and Wildlife Cooperative research unit, Laramie, Wyoming, USA. Available at: https://babel.hathitrust.org/cgi/pt?id=umn.31951p00672031a;view=1up;seq=146California Department of Fish and Wildlife. 2016b. Potential Suitable Habitat in California. Pages 153-160 in Conservation Plan for Gray Wolves in California Part 2. Carroll, C., Phillips, M.K., Lopez-Gonzalez, C.A., and Schumaker, N.H. 2006. Defining Recovery Goals and Strategies for Endangered Species: The Wolf as a Case Study. BioScience 56(1): 25–37, https://doi.org/10.1641/0006-3568(2006)056[0025:DRGASF]2.0.CO;2Carroll, C. 2003. Impacts of Landscape Change on Wolf Viability in the Northeastern U.S. and Southeastern Canada. Wildlands Project Special Paper No. 5, available at https://www.klamathconservation.org/docs/wolfviabilitypaper.pdf.Carroll, C. 2007. Application of habitat models to wolf recovery planning in Washington. Unpublished report.Defendersof Wildlife. 2006. Places for Wolves: A Blueprint for Restoration and Recovery in the Lower 48 StatesDefenders of Wildlife. 2013. Places for WolvesHarrison, D. J., and T. G. Chapin. 1998. An assessment of potential habitat for eastern timber wolves in the northeastern United States and connectivity with occupied habitat in southeastern Canada. Wildlife Conservation Society, Working Paper Number 7.Harrison, D. J., and T. G. Chapin. 1998. Extent and connectivity of habitat for wolves in eastern North America. Wildlife Society Bulletin 26: 767-775, available at https://wolfology1.tripod.com/id207.htmHearne D., Lewis K., Martin M., Mitton E., and Rocklen C. 2003. Assessing the Landscape: Toward a Viable Gray Wolf Population in Michigan and Wisconsin. Hendricks, S.A., Schweizer, R.M., Harrigan, R.J., Pollinger, J.P., Paquet, P.C., Darimont, C.T., Adams, J.R., Waits, L.P., vonHoldt, B.M., Hohenlohe1, P.A. and R.K. Wayne. 2018. Natural recolonization and admixture of wolves (Canis lupus) in the US Pacific Northwest: challenges for the protection and management of rare and endangered taxa. The Genetics Society. Heredity. https://doi.org/10.1038/s41437-018-0094-x.Jimenez, M.D. et al. 2017. Wolf Dispersal in the Rocky Mountains, Western United States: 1993–2008. The Journal of Wildlife Management 81(4):581–592.Larson, T. and W.J. Ripple. 2006. Modeling Gray Wolf (Canis lupus) habitat in the Pacific Northwest, U.S.A. Journal of Conservation Planning 2:17-33.Maletzke, B.T. and R.B. Wielgus. 2011. Development of wolf population models for RAMAS© analysis by the Washington Department of Fish and Wildlife.Martinez-Meyer E., Gonzalez-Bernal A., Velasco J.A., Swetnam T.L., Gonzalez-Saucedo Z.Y., Servin J., Lopez-Gonzalez C.A., Oakleaf, J.A., Liley S., and Heffelfinger J.R. 2020. Rangewide habitat suitability analysis for the Mexican wolf (Canis lupus baileyi) to identify recovery areas in its historical distribution. Diversity and Distributions 00:1-13.McNab, W.H., Cleland, D.T., Freeouf, J.A., Keys, Jr., J.E., Nowacki, G.J., Carpenter, C.A., comps. 2007. Description of ecological subregions: sections of the conterminous United States [CD-ROM]. Gen. Tech. Report WO-76B. Washington, DC: U.S. Department of Agriculture, Forest Service. 80 p.McNab, W.H. and P.E. Avers. 1995. Ecological subregions of the United States. Washington, DC: U.S. Department of Agriculture, Forest Service, available at https://www.fs.fed.us/land/pubs/ecoregions/.Mladenoff, D.J., Sickley, T.A., Haight, R.G. and Wydeven, A.P. 1995. A Regional Landscape Analysis and Prediction of Favorable Gray Wolf Habitat in the Northern Great Lakes RegionMladenoff, D.J. and T.A. Sickley. 1998. Assessing Potential Gray Wolf Restoration in the Northeastern United States: A Spatial Source. Journal of Wildlife Management 62(1): 1-10.Minnesota Dept. of Natural Resources. 2001. Minnesota Wolf Management Plan. Minnesota Dept. Natural Resources. 2017a. Gray Wolf, available at https://www.dnr.state.mn.us/mammals/wolves/mgmt.html.Montana Fish Wildlife & Parks. 2004. Montana Gray Wolf Conservation and Management Plan.Montana Fish,Wildlife & Parks. 2018. Montana Annual Report 2018: Wolf Conservation and Management.Oakleaf J.K., Murray D.L., Oakleaf J.R., Bangs E.E., Mack C.M., Smith D.W., Fontaine J.A., Jimenez M.D., Meier T.J., and C.C. Niemeyer. 2006. Habitat Selection by Recolonizing Wolves in the Northern Rocky Mountains of the United States. Journal of Wildlife Management 70(2):554-563.Oregon Department of Fish and Wildlife. 2015. Updated mapping potential gray wolf range in Oregon.Potvin M.J., Drummer T.D., Vucetich J.A., Beyer E. Jr., and J.H. Hammill. 2005. Monitoring and Habitat Analysis for Wolves in Upper Michigan. Journal of Wildlife Management 69(4):1660-1669.Treves A., Martin K.A., Wiedenhoeft J.E., Wydeven A.P. (2009) Dispersal of Gray Wolves in the Great Lakes Region. In: Wydeven A.P., Van Deelen T.R., Heske E.J. (eds) Recovery of Gray Wolves in the Great Lakes Region of the United States. Springer, New York, NY. https://doi.org/10.1007/978-0-387-85952-1_12USGS Gap Analysis Project Species Range and Predicted Habitat: Gray wolf: https://gapanalysis.usgs.gov/apps/species-data-download/Washington Dept. of Fish and Wildlife (WDFW). 2017. Washington Gray Wolf Conservation and Management 2017 Annual Report.Wiles, G. J., H. L. Allen, and G. E. Hayes. 2011. Wolf conservation and management plan for Washington. Washington Department of Fish and Wildlife, Olympia, Washington. 297 pp.Red Wolf:Historic Range:Red wolf historic range established by USFWS based on information provided by the 2016 Wildlife Management Institute report [ Wildlife Management Institute: A Review and Evaluation of the Red Wolf (Canis rufus) Historic Range, Final Report – 5/25/2016]. The historic range layer is a combination of the following Level II EPA Ecoregions: 1) Mississippi Alluvial and Southeast USA Coastal Plains, 2) Ozark/Ouachita-Appalachian Forests, 3) South Central Semi-Arid Prairies, 4) Southeastern USA Plains, and 5) Texas-Louisiana Coastal PlainsCurrent Range (Recovery Area):Red wolf recovery area adapted from the USFWS current range information.Suitable Habitat:Toivonen L.K. (2018) Assessing red wolf conservation based on analyses of habitat suitability and human perception of carnivores.Karlin M., Vaclavik T., Chadwick J., and R. Meentemeyer. (2016) Habitat use by adult red wolves, Canis rufus, in an agricultural landscape, North Carolina, USA. Mammal Study 41:87-95.