4,36 (persons per sq. km) in 2022.

A dataset listing North Dakota counties by population for 2024.

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.

A dataset listing South Dakota zip codes by population for 2024.

Map containing historical census data from 1900 - 2000 throughout the western United States at the county level. Data includes total population, population density, and percent population change by decade for each county. Population data was obtained from the US Census Bureau and joined to 1:2,000,000 scale National Atlas counties shapefile.

4,63 (persons per sq. km) in 2022.

The 2015 cartographic boundary shapefiles 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.

In 2021, around 14 percent of individuals living in the District of Columbia identified as LGBT. Colorado, Arizona, Nevada, and Oregon also had high rates, exceeding ten percent. Mississippi and North Dakota had the lowest rates of LGBT populations, the only states with less than five percent.

description: This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of South Dakota. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of South Dakota. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for South Dakota. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F71834H6; abstract: This shapefile contains landscape factors representing human disturbances summarized to local and network catchments of river reaches for the state of South Dakota. This dataset is the result of clipping the feature class 'NFHAP 2010 HCI Scores and Human Disturbance Data for the Conterminous United States linked to NHDPLUSV1.gdb' to the state boundary of South Dakota. Landscape factors include land uses, population density, roads, dams, mines, and point-source pollution sites. The source datasets that were compiled and attributed to catchments were identified as being: (1) meaningful for assessing fish habitat; (2) consistent across the entire study area in the way that they were assembled; (3) representative of conditions in the past 10 years, and (4) of sufficient spatial resolution that they could be used to make valid comparisons among local catchment units. In this data set, these variables are linked to the catchments of the National Hydrography Dataset Plus Version 1 (NHDPlusV1) using the COMID identifier. They can also be linked to the reaches of the NHDPlusV1 using the COMID identifier. Catchment attributes are available for both local catchments (defined as the land area draining directly to a reach; attributes begin with "L_" prefix) and network catchments (defined by all upstream contributing catchments to the reach's outlet, including the reach's own local catchment; attributes begin with "N_" prefix). This shapefile also includes habitat condition scores created based on responsiveness of biological metrics to anthropogenic landscape disturbances throughout ecoregions. Separate scores were created by considering disturbances within local catchments, network catchments, and a cumulative score that accounted for the most limiting disturbance operating on a given biological metric in either local or network catchments. This assessment only scored reaches representing streams and rivers (see the process section for more details). Please use the following citation: Esselman, P., D.M. Infante, L. Wang, W. Taylor, W. Daniel, R. Tingley, J. Fenner, A. Cooper, D. Wieferich, D. Thornbrugh and J. Ross. (April 2011) National Fish Habitat Action Plan (NFHAP) 2010 HCI Scores and Human Disturbance Data (linked to NHDPLUSV1) for South Dakota. National Fish Habitat Partnership Data System. http://dx.doi.org/doi:10.5066/F71834H6

In 2022, there were, on average, 2.35 hospital beds per 1,000 population in the United States. Hospital bed density varied widely between the states, with South Dakota having 4.61 beds per thousand population, while there were just 1.6 hospital beds per thousand population available in Washington.

Identifying the specific environmental features and associated density-dependent processes that limit population growth is central to both ecology and conservation. Comparative assessments of sympatric species allow for inference into how ecologically similar species differentially respond to their shared environment, which can be used to inform community-level conservation strategies. Comparative assessments can nevertheless be complicated by interactions and feedback loops among the species in question. We developed an integrated population model based on sixty-one years of ecological data describing the demographic histories of Canvasbacks (Aythya valisineria) and Redheads (Aythya americana), two species of migratory diving ducks that utilize similar breeding habitats and affect each other’s demography through interspecific nest parasitism. We combined this model with a transient life table response experiment to determine the extent that demographic rates, and their contributions to population growth, were similar between these two species. We found that demographic rates and, to a lesser extent, their contributions to population growth covaried between Canvasbacks and Redheads, but the trajectories of population abundances widely diverged between the two species during the end of the 20th century due to inherent differences between the species life-histories and sensitivities to both environmental variation and harvest pressure. We found that annual survival of both species increased during years of restrictive harvest regulations; however, recent harvest pressure on female Canvasbacks may be contributing to population declines. Despite periodic, and often dramatic, increases in breeding abundance during wet years, the number of breeding Canvasbacks declined by 13% whereas the number of breeding Redheads has increased by 37% since 1961. Reductions in harvest pressure and improvements in submerged aquatic vegetation throughout the wintering grounds have mediated the extent to which populations of both species contracted during dry years in the Prairie Pothole Region. However, continued degradation of breeding habitats through climate-related shifts in wetland hydrology and agricultural conversion of surrounding grassland habitats may have exceeded the capacity for demographic compensation during the non-breeding season. Methods DATA COLLECTION We combined a series of long-term data sets into a single integrated population model that provided insights into how variation in seasonal survival (band releases and recoveries) and offspring production (harvest age-ratios) contributed to fluctuations in population growth (breeding survey, harvest estimates) for Canvasbacks and Redheads from 1961–2021. Banding Data – Information regarding the banding and subsequent harvest of ducks was acquired from the GameBirds Database CD (Bird Banding Lab, USGS Patuxent Wildlife Research Center, Laurel MD, USA, version August 2022). Male and female Canvasbacks and Redheads were captured following breeding but prior to the hunting season (Pre-Hunting) as ducklings (Local) or hatch year (HY; fledged juvenile) individuals as well as after hatch year (AHY; adult) individuals or following the hunting season (Post-Hunting) as an undifferentiated mixture of second year (SY) and after second year (ASY) individuals captured and released across North America from 1961–2022. We limited the pre-harvest banding data for both species to include all individuals banded and released alive in areas within the Canadian provinces of Alberta, Manitoba, Saskatchewan, as well as the states of Minnesota, Montana, North Dakota, and South Dakota within the USA (Fig. 1). For the pre-hunting banding group, we retained individuals captured between 1961–2021 during the late summer (Jul 15th – Sep 15th) with a known sex (M or F) and age-class (local, HY or AHY) that were released without any additional markers considered to meaningfully affect survival of an individual (e.g., nasal saddles or dual banding were permissible but telemetered individuals were excluded; Lameris & Kleyheeg, 2017). For post-hunting banding, we limited the spatial boundary of banding efforts to only consider individuals released from the Atlantic, Central, or Mississippi Flyways (Fig. 1). We followed the same data selection procedures, but limited releases to occur between Jan. 1st – March 15th from 1962–2022. Because too few banders differentiated SY from ASY at time of banding, we treated all post-hunting samples as AHY adults. Individuals banded during this period that were reported to be harvested during the winter they were originally banded were censored from the analysis, as the underlying model assumption was that this cohort of individuals had already survived the current hunting season. For both seasonal banding efforts, we only included recoveries of hunter-shot individuals harvested between September and February in which a known year-of-death could be ascertained. In addition to self-reported recoveries (i.e., reported by the hunter), we included hunter-harvested individuals that were instead reported by federal, state, or provincial entities (e.g., outcomes of hunter check stations or other forms of solicitation). We limited the dataset to only include recoveries of hunter-harvested individuals killed within 15 years of initial banding, which represented > 99% of pre-hunting and post-hunting recoveries. This cut-off was arbitrarily selected but did not meaningfully bias parameter estimation while vastly improving computational efficiency by bypassing the estimation of hundreds of zero-equivalent cell probabilities (personal communication S. Bonner). Harvest Intensity – We used the average number of Canvasbacks or Redheads allowed to be harvested per day (i.e., bag limit; (Appendix S1: Tables S1a-b) across the U.S. portions of the Atlantic, Mississippi, Central, and Pacific flyways during each year of the study as an index of harvest regulatory pressure. Annual harvest restrictions were acquired from the published literature (Péron et al., 2012), the annual release of the Late-Season Migratory Bird Hunting Regulations (e.g., USFWS 2022), and direct requests to the U.S. Fish and Wildlife Service. For these species, liberal harvest regulations were bag limits of two (Canvasbacks) and two to four (Redheads) allowable harvest per day, whereas conservative harvest regulations were either a bag limit of one individual per day or total closure. Harvest Composition – Data describing the age and sex structure of the harvested Canvasback and Redhead populations were derived from the annual Parts Collection surveys conducted by the U.S. Fish and Wildlife Service (USFWS) where a subset of hunters submit a wing from every duck they harvested (Pearse et al. 2014). These data were acquired through a direct request to the U.S. Fish and Wildlife Service. Additionally, estimates of the total number of Canvasbacks and Redheads harvested in the United States and Canada were derived from the Harvest Information Program (Steeg et al., 2002) and Canadian National Harvest Survey (Smith et al., 2022), respectively. Breeding Duck and Pond Densities – The relative number of breeding Canvasbacks and Redheads, as well as the relative amount of their breeding habitat (i.e., flooded ponds) within the Prairies were calculated using count data from the USFWS Waterfowl Breeding Population and Habitat Survey (hereafter BPOP; Smith, 1995), which has conducted an annual survey of breeding waterfowl and their habitats throughout the core part of these species’ breeding ranges (i.e., central Canada and the north-central United States) during the spring from 1961 through 2022 (U.S. Fish and Wildlife Service, 2022). However, BPOP surveys did not occur during 2020 and 2021. For the purposes of this study, we limited the spatial extent of BPOP survey to only include transects flown within Alberta, Manitoba, Saskatchewan, Montana, North Dakota, and South Dakota. Agriculture Development – The amounts of active cropland in the Prairies during each year of the study were estimated from Canada and United States Agriculture Census data (see Buderman et al., 2020). Annual estimates of active cropland acreages were summarized to represent an index of agricultural development during 1961–2021. Although agricultural development is predicted to have greater impact on upland-nesting dabbling ducks (Duncan and Devries 2018), it also impacts the wetland habitats in which Canvasbacks and Redheads forage and nest, as well as the predator communities that can access overwater nesting pochards (Sargeant et al. 1993, Bartzen et al. 2010). Winter Habitat – Winter habitat conditions were assumed to be related to submerged aquatic vegetation (SAV) within the Chesapeake for Canvasbacks and environmental salinity (TDS; total dissolved solids) in the Laguna Madre for Redheads. Although Redheads likely respond to variation in SAV, time series data describing SAV were not available for the Laguna Madre. Therefore, we assumed that annual fluctuations in salinity were an informative proxy of both SAV conditions and osmotic constraints (Quammen and Onuf 1993, Moore 2009), which in turn was representative of winter habitat conditions that simultaneously influenced Redhead food availability and harvest risk (Ballard et al. 2021).. Climate Data – We used the average Pacific/North American (PNA; Leathers et al., 1991) teleconnection pattern from April–July as an index of drought severity or environmental stress during the breeding season throughout the Prairies, and average sea-surface temperatures (SST) from September–March in the Chesapeake and Laguna Madre as an index of winter severity for Canvasbacks and Redheads, respectively (see Data Availability statement).

description: The National Wildlife Refuge System s 150 million acres in over 500 refuges representdiverse landscapes with different capacities to provide ecosystem goods and services to society.Natural processes associated with management of national wildlife refuges provide benefits tolocal communities by sustaining production of specific goods and services that are useful topeople. Estimated economic values of these services, such as those presented in this report, can be used to compare refuges in different locations and under different management, climatic, or socio economic conditions. Our estimates of economic benefits from natural ecosystems serve as complements to economic impact analyses, such as the FWS s Banking on Nature studies (Carver and Caudill 2007). This report presents the methods and results from Phase I of our research project. In this report we compare wetlands on four national wildlife refuges to illustrate how existing data can be used to estimate the average annual economic benefits of specific ecosystem services from different types of wetlands. The four sites are Arrowwood National Wildlife Refuge (NWR), North Dakota; Blackwater NWR, Maryland; Okefenokee NWR, Georgia; and Sevilleta and Bosque del Apache NWRs, New Mexico. These four sites were selected to contrast major types of wetlands in terms of physical and social parameters that influence the values of different ecosystem goods and services. We present multiple approaches to assessing ecosystem services benefits. For each of the four refuges, we first consider a purely qualitative assessment of the relative magnitudes of different ecosystem service benefits provided by each refuge. This approach proves to be the most inclusive in terms of our ability to consider ecological data specific to the refuge, and provides a useful tool for broad assessments and comparisons across refuges. However, it does not lead to quantitative estimates of ecosystem service benefits. For these estimates, we use two different benefit transfer techniques: (1) a meta analysis benefit transfer to estimate the economic values of storm protection, water quality provisioning, and support for nursery and habitat for commercial fishing species; and (2) a point transfer approach to estimate the value of stored carbon. Our results suggest that refuge size and the socio demographic characteristics of the surrounding region are important determinates of the estimated per acre value of wetlands in providing ecosystem services. Consistent with economic theory, larger refuges in areas with lower population density tend to have lower per acre values. However, these interaction effects between wetland size, population size and preferences, and ecosystem service values need to be further studied. Our results are an approximation of consumers aggregate willingness to pay to obtain the service provided by the wetlands of a particular NWR. Decision makers can use these numbers to understand how a population might be impacted by a change in distribution of wetlands across a landscape. The most straightforward application of the method we follow concerns estimating the net economic value of a change in an ecosystem service due to a management action which changes a wetland from one type to another. This report represents Phase I of our efforts to estimate the ecosystem service benefits of the National Wildlife Refuge System. The primary focus of the second phase will be the development of a meta analysis benefit transfer model specifically tailored toward wetlands in National Wildlife Refuges.; abstract: The National Wildlife Refuge System s 150 million acres in over 500 refuges representdiverse landscapes with different capacities to provide ecosystem goods and services to society.Natural processes associated with management of national wildlife refuges provide benefits tolocal communities by sustaining production of specific goods and services that are useful topeople. Estimated economic values of these services, such as those presented in this report, can be used to compare refuges in different locations and under different management, climatic, or socio economic conditions. Our estimates of economic benefits from natural ecosystems serve as complements to economic impact analyses, such as the FWS s Banking on Nature studies (Carver and Caudill 2007). This report presents the methods and results from Phase I of our research project. In this report we compare wetlands on four national wildlife refuges to illustrate how existing data can be used to estimate the average annual economic benefits of specific ecosystem services from different types of wetlands. The four sites are Arrowwood National Wildlife Refuge (NWR), North Dakota; Blackwater NWR, Maryland; Okefenokee NWR, Georgia; and Sevilleta and Bosque del Apache NWRs, New Mexico. These four sites were selected to contrast major types of wetlands in terms of physical and social parameters that influence the values of different ecosystem goods and services. We present multiple approaches to assessing ecosystem services benefits. For each of the four refuges, we first consider a purely qualitative assessment of the relative magnitudes of different ecosystem service benefits provided by each refuge. This approach proves to be the most inclusive in terms of our ability to consider ecological data specific to the refuge, and provides a useful tool for broad assessments and comparisons across refuges. However, it does not lead to quantitative estimates of ecosystem service benefits. For these estimates, we use two different benefit transfer techniques: (1) a meta analysis benefit transfer to estimate the economic values of storm protection, water quality provisioning, and support for nursery and habitat for commercial fishing species; and (2) a point transfer approach to estimate the value of stored carbon. Our results suggest that refuge size and the socio demographic characteristics of the surrounding region are important determinates of the estimated per acre value of wetlands in providing ecosystem services. Consistent with economic theory, larger refuges in areas with lower population density tend to have lower per acre values. However, these interaction effects between wetland size, population size and preferences, and ecosystem service values need to be further studied. Our results are an approximation of consumers aggregate willingness to pay to obtain the service provided by the wetlands of a particular NWR. Decision makers can use these numbers to understand how a population might be impacted by a change in distribution of wetlands across a landscape. The most straightforward application of the method we follow concerns estimating the net economic value of a change in an ecosystem service due to a management action which changes a wetland from one type to another. This report represents Phase I of our efforts to estimate the ecosystem service benefits of the National Wildlife Refuge System. The primary focus of the second phase will be the development of a meta analysis benefit transfer model specifically tailored toward wetlands in National Wildlife Refuges.