This map of human habitation was developed, following a modification of Schumacher et al. (2000), by incorporating 2000 U.S Census Data and land ownership. The 2000 U.S. Census Block data and ownership map of the western United States were used to correct the population density for uninhabited public lands. All census blocks in the western United States were merged into one shapefile which was then clipped to contain only those areas found on private or indian reservation lands because human habitation on federal land is negligible. The area (ha) for each corrected polygon was calculated and the 2000 census block data table was joined to the shapefile. In a new field, population density (individuals/ha) corrected for public land in census blocks was calculated . SHAPEGRID in ARC/INFO was used to convert population density values to grid with 90m resolution.

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.

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.

2 computer laser optical discs ; 4 3/4 in. Contains housing unit and person records drawn from the full census sample. Contains records for 5 percent of the population; each housing unit and person record contains a weight field (HOUSWGT or PWGT1) which has a value that represents the record's relationship to the entire population. Disc 1: Alabama - Montana Disc 2: Nebraska - Wyoming

description: Greater sandhill cranes of the Rocky Mountain Population (RMP) were counted at fall premigration staging areas in Colorado, Idaho, Montana, Utah, and Wyoming during September 2014. Migrants that had arrived at RMP migration stopover areas near Jensen, Utah and in the San Luis Valley, Colorado were also recorded. The cooperative survey was organized by the Pacific Flyway Subcommittee on RMP of Greater Sandhill Cranes and the U.S. Fish and Wildlife Service (FWS). The FWS, Division of Migratory Bird Management (DMBM), Denver, provided a Cessna 206 for a portion of the survey. Aerial and ground surveys were conducted by personnel from respective state agencies, FWS and volunteers (participants listed in Table 1).; abstract: Greater sandhill cranes of the Rocky Mountain Population (RMP) were counted at fall premigration staging areas in Colorado, Idaho, Montana, Utah, and Wyoming during September 2014. Migrants that had arrived at RMP migration stopover areas near Jensen, Utah and in the San Luis Valley, Colorado were also recorded. The cooperative survey was organized by the Pacific Flyway Subcommittee on RMP of Greater Sandhill Cranes and the U.S. Fish and Wildlife Service (FWS). The FWS, Division of Migratory Bird Management (DMBM), Denver, provided a Cessna 206 for a portion of the survey. Aerial and ground surveys were conducted by personnel from respective state agencies, FWS and volunteers (participants listed in Table 1).

Greater sage-grouse population components devrived using an 18-km maximum connection distance. Analysis was conducted using the CONEFOR SENSINODE 2.2 software package and this dataset was developed from lek data obtained from the state wildlife agencies. Components containing < 5 leks have been removed in order to protect the location of single or small groups of leks.

This data collection contains extracts of the original DUALabs Special Fifth Count ED/BG Summary Tapes. They are comprised of limited demographic and socioeconomic variables for 27 states in the continental United States. Data are provided at the county, minor civil division, enumeration district, and block group levels for total population and Spanish heritage population for the following states: Minnesota, Nevada, Wyoming, Indiana, Kansas, Nebraska, Oklahoma, South Dakota, Colorado, Arizona, Utah, North Dakota, Montana, Idaho, Missouri, Washington, Iowa, Louisiana, Arkansas, Ohio, Michigan, Wisconsin, Illinois, Oregon, Texas, New Mexico, and California. Demographic variables provide information on race, age, sex, country and place of origin, income, and family status and size. The data were obtained by ICPSR from the National Chicano Research Network, Survey Research Center, Institute for Social Research, University of Michigan.

Mobile elements are powerful agents of genomic evolution and can be exceptionally informative markers for investigating species and population-level evolutionary history. While several studies have utilized retrotransposon-based insertional polymorphisms to resolve phylogenies, few population studies exist outside of humans. Endogenous retroviruses are LTR-retrotransposons derived from retroviruses that have become stably integrated in the host genome during past infections and transmitted vertically to subsequent generations. They offer valuable insight into host-virus co-evolution and a unique perspective on host evolutionary history because they integrate into the genome at a discrete point in time. We examined the evolutionary history of a cervid endogenous gammaretrovirus (CrERVγ) in mule deer (Odocoileus hemionus). We sequenced 14 CrERV proviruses (CrERV-in1 to -in14), and examined the prevalence and distribution of 13 proviruses in 262 deer among 15 populations from Montana, Wyoming, and Utah. CrERV absence in white-tailed deer (O. virginianus), identical 5′ and 3′ long terminal repeat (LTR) sequences, insertional polymorphism, and CrERV divergence time estimates indicated that most endogenization events occurred within the last 200000 years. Population structure inferred from CrERVs (F ST = 0.008) and microsatellites (θ = 0.01) was low, but significant, with Utah, northwestern Montana, and a Helena herd being particularly differentiated. Clustering analyses indicated regional structuring, and non-contiguous clustering could often be explained by known translocations. Cluster ensemble results indicated spatial localization of viruses, specifically in deer from northeastern and western Montana. This study demonstrates the utility of endogenous retroviruses to elucidate and provide novel insight into both ERV evolutionary history and the history of contemporary host populations.

From 2008 to March 6, 2024, the District of Columbia had the highest rate of school shootings nationwide, totaling around 0.7 school shootings per 100,000 residents. Louisiana, Delaware, Alabama, and Maryland rounded out the top five states with the highest school shooting rates relative to their populations. In contrast, there were no school shootings recorded in Montana, Wyoming, New Hampshire, Vermont, and Rhode Island within the provided time period. In addition to K-12 schools and college campuses, gun-related violence in the United States often occurs at workplaces, places of worship, and restaurants and bars.

The source defines school shootings as incidents of gun violence which occurred on school property, from kindergartens through colleges/universities, and at least one person was shot, not including the shooter. School property includes, but is not limited to, buildings, fields, parking lots, stadiums and buses. Accidental discharges of firearms are included, as long as at least one person is shot, but not if the sole shooter is law enforcement or school security.

1. As public land managers seek to adopt and implement conservation measures aimed at reversing or slowing the negative effects of climate change, they are looking to understand public opinion regarding different management strategies.

2. This study explores drivers of attitudes toward different management strategies (i.e., no management, protection, and restoration) for a low-profile but keystone tree species, the whitebark pine (Pinus albicaulis), in the Greater Yellowstone Ecosystem. Since the whitebark pine species has a range that traverses different federal land designations, we examine whether attitudes toward management strategies differ by jurisdiction (i.e., wilderness or federal lands more generally).

3. We conducted a web and mail survey of residents from Montana, Idaho, and Wyoming, with 1,617 valid responses and a response rate of 16%.

4. We find that active management strategies have substantially higher levels of support than does no management, with relatively little differentiation across protection and restoration activities or across different land designations. We also find that support for management strategies is not influenced by values (political ideology) but is influenced by beliefs (about material vs. post-material environmental orientation, global climate change, and federal spending for public lands) and some measures of experience (e.g., knowledge of threats).

5. This study helps land managers understand that support for active management of the whitebark pine species is considerable and nonpartisan and that beliefs and experience with whitebark pine trees are important for support

Methods Our study employed a cross-sectional design with a survey methodology to test our hypotheses. We distributed the questionnaire initially to 9,000 randomly selected addresses in Montana, Wyoming, and Idaho, proportional to the population in each state. We made multiple efforts to increase response rates (Dillman, Smyth, & Christian, 2014). Two letters were sent in two-week increments to direct potential respondents to a web version of the survey into which they would enter an authentication code to prevent duplicate entries; a hard copy of the survey with a business reply envelope was sent to non-respondents after another two weeks. We then drew another random sample of 1,000 new addresses, again proportional to state population. In this round, we sent only a paper version of the survey, with no web option. For all 10,000 randomly selected residents, we also randomly assigned an incentive value ($0, $1, or $2), with corresponding response rates of 9.9%, 17.3%, and 21.7%.

We test our hypotheses primarily using Wilcoxon signed-rank tests for matched pairs (Wilcoxon, 1945) and ordered logistic regression analysis. We use the Wilcoxon tests in comparing attitudes across management strategies and land types, as the data for the ordinal variables are matched at the individual respondent level. These tests are appropriate as the hypotheses (H1-H2) deal with comparison of variable distributions rather than association between variables. However, we apply Chi-square tests in a follow-up analysis exploring relationships among the six ordinal management strategy variables in an attempt to clarify the substantive significance of the Wilcoxon signed-rank test findings. We employ ordered logistic regression to account for the ordinal nature of the dependent variables (Long & Freese, 2014) in testing the remainder of the hypotheses, some of which involve continuous independent variables. Ordered logistic regression permits the calculation of post-estimation statistics to assess the marginal influence of one variable on the other. In order to facilitate interpretation of the regression results, we calculate changes in predicted probabilities for the dependent variables taking on particular values as the independent variables change values. Predicted probabilities are a common way to demonstrate marginal effects with ordinal dependent variables, as the regression coefficients can be difficult to interpret otherwise.

Data were cleaned and variables were recoded and relabeled in STATA 14.

As of 2022, the U.S. states with the highest death rates from suicide were Montana, Alaska, and Wyoming. In Wyoming and Montana, there were around 29 and 28 suicide deaths per 100,000 population, respectively. In comparison, in New Jersey, the state with the lowest suicide death rate, there were only around eight suicide deaths per 100,000 population. Differences in suicide rates by gender In the United States, there is a vast difference in suicide rates between men and women, with rates over 3.5 times higher among men. However, rates of suicide for both men and women have increased over the past couple of decades. Among men, those aged 75 years and older have the highest suicide rates, with around 42 deaths per 100,000 population in 2021. Among women, those aged 45 to 64 years have the highest rates of suicide death with 8.2 deaths per 100,000 population. What is the most common method of suicide? In the United States, the most common method of suicide is with firearms, followed by suffocation and then poisoning. In 2022, there were around 27,032 suicide deaths from firearms in the United States, compared to 12,247 deaths from suffocation and 4,894 from drug poisoning. In 2021, firearms accounted for around 60 percent of suicide deaths among men. In comparison, around 35 percent of deaths from suicide among women were due to firearms, while suffocation and poisoning each accounted for 28 percent of such deaths.

The White-faced Ibis (Plegadis chihi) in the Great Basin and surrounding area was listed as a Species of Management Concern (Sharp 1985, USFWS 1995) based on its small population size and vulnerability to breeding habitat loss. Traditionally, most Great Basin ibises have bred in Utah and Nevada with peripheral but growing colonies in Idaho, California, and Oregon (Sharp 1985, Ryder and Manry 1994). After apparently declining precipitously in the 1960's and 1970's (Capen 1977), the Great Basin population was estimated at only 7,500 breeding pairs in 1984 (Sharp 1985). In addition to the Great Basin population (as defined here), small numbers of ibises breed locally in Colorado, Wyoming, Montana, North and South Dakota, and southern Alberta, and large numbers breed in Louisiana, Texas, Mexico, and South America (reviewed in Ryder and Manry 1994). Interchange among these sites and Great Basin colonies has not been investigated. In the arid Great Basin region, ibises breed in semi-permanent wetlands which are susceptible to naturally occurring droughts and floods. Local population fluctuations and colony abandonment reflect this vulnerability. The highly nomadic White-faced Ibis apparently compensates for wetland dynamics by moving among breeding colonies and colonizing new wetlands within and between years (e.g., Ryder 1967, Capen 1977, Ivey et al. 1988, Henny and Herron 1989). The nomadic nature of the White-faced Ibis, like that of several other colonial ciconiiforms, suggests that conservation efforts be undertaken at the landscape level and that population dynamics, distribution, and trends be monitored at the regional or population scale (e.g., Frederick et al. 1996). The status of the Great Basin breeding population has not been reviewed since 1984 (Sharp 1985). Increases in breeding numbers in Oregon, Idaho, and California during the 1980's and 1990's suggested either that ibises were increasing regionally or individuals displaced from flooded Great Salt Lake marshes were colonizing elsewhere (e.g., Ivey et al. 1988, Follansbee and Mauser 1994, Trost and GersteIl1994). An increase in wintering numbers also suggested a population increase (Shuford et al. 1989). Recognizing the need for a comprehensive estimate of the breeding population, U.S. Fish and Wildlife Service (USFWS) coordinated a regional survey of all historic, active, and probable colony sites in 1995. To further assess the 1985-1997 population trend, we compiled available annual survey data for all known colonies. Here we report results of the 1995 survey and annual counts for 1985-1997. The objectives of this report are as follows: I. Document changes in the distribution, abundance, and population trend of White-faced Ibis breeding in the Great Basin and surrounding area during 1985-1997. 2. Interpret population-wide changes in ibis distribution and abundance in relation to wetland dynamics throughout the region. 3. Discuss implications for future monitoring, research, and conservation.

This file contains COVID-19 death counts, death rates, and percent of total deaths by jurisdiction of residence. The data is grouped by different time periods including 3-month period, weekly, and total (cumulative since January 1, 2020). United States death counts and rates include the 50 states, plus the District of Columbia and New York City. New York state estimates exclude New York City. Puerto Rico is included in HHS Region 2 estimates. Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file. Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death. Death counts should not be compared across states. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly. The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York, New York City, Puerto Rico; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington. Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf). Rates are based on deaths occurring in the specified week/month and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly/monthly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly/monthly) rate prevailed for a full year. Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

SWE = Sweden; NOR = Norway; MNG = Mongolia; RUS = Russia; AK = Alaska; YT = Yukon; NT = Northwest Territories; NU = Nunavut; BC = British Columbia; AB = Alberta; SK = Saskatchewan; MB = Manitoba; ON = Ontario; QC/NL = Quebec-Labrador; MT = Montana; WY = Wyoming; ID = Idaho; CA = California.

This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia.

Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file.

Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death.

Death counts should not be compared across jurisdictions. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly.

The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.

Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf).

Rate are based on deaths occurring in the specified week and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly) rate prevailed for a full year.

Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

SWE = Sweden; NOR = Norway; MNG = Mongolia; RUS = Russia; AK = Alaska; YT = Yukon; NT = Northwest Territories; NU = Nunavut; BC = British Columbia; AB = Alberta; SK = Saskatchewan; MB = Manitoba; ON = Ontario; QC/NL = Quebec-Labrador; MT = Montana; WY = Wyoming; ID = Idaho; CA = California; C = Contemporary; H = Historic.

description: This plan sets forth guidelines for the cooperative management of the Mid-continent Population of sandhill cranes (hereafter MCP). The range of the MCP is extensive (Figure 1). During the breeding season, these cranes are widely scattered throughout central, northern, and southeast Canada (Appendix A and B); Alaska; northeastern Siberia; and northwestern Minnesota. Fall migration routes include areas where large numbers of MCP cranes stage in Alberta, Saskatchewan, Manitoba, North Dakota, and in recent years, Kansas (Appendix B). Other fall staging areas are located in northwestern Minnesota, Montana, Wyoming, South Dakota, Colorado, and Oklahoma. During autumn and winter, MCP cranes are in Oklahoma, Texas, New Mexico, Arizona, and also northern and central Mexico, primarily in the Interior Highlands in the states of Chihuahua and Durango. At some time during late February to early April each year, the majority of individuals in the MCP are among the spectacular numbers of migratory birds which stage in the central Platte Valley of Nebraska.; abstract: This plan sets forth guidelines for the cooperative management of the Mid-continent Population of sandhill cranes (hereafter MCP). The range of the MCP is extensive (Figure 1). During the breeding season, these cranes are widely scattered throughout central, northern, and southeast Canada (Appendix A and B); Alaska; northeastern Siberia; and northwestern Minnesota. Fall migration routes include areas where large numbers of MCP cranes stage in Alberta, Saskatchewan, Manitoba, North Dakota, and in recent years, Kansas (Appendix B). Other fall staging areas are located in northwestern Minnesota, Montana, Wyoming, South Dakota, Colorado, and Oklahoma. During autumn and winter, MCP cranes are in Oklahoma, Texas, New Mexico, Arizona, and also northern and central Mexico, primarily in the Interior Highlands in the states of Chihuahua and Durango. At some time during late February to early April each year, the majority of individuals in the MCP are among the spectacular numbers of migratory birds which stage in the central Platte Valley of Nebraska.

Model of habitat utilization by synanthropic avian predators: common ravens (Corvus corax), American crows (Corvus brachyrhynchos), and black-billed magpies (Pica hudsonia). The former two species show increasing nation-wide population trends, and common ravens in the Mojave desert have been shown to have detrimental effects on threatened desert tortoise (Gopherus agassizii) populations. Power lines are used by common ravens and other raptors for nesting and as hunting perches. Linear features such as railroads, primary and secondary roads, and irrigation channels often serve as travel routes for these predators, and expand their movements into previously unused regions. Numbers of synanthropic avian predators increase in areas surrounding rural human developments, campgrounds, landfills, roads, rest stops, and agricultural lands because they provide reliable and often highly abundant food sources. Using daily movement patterns, we developed a decaying probability function (P=100-100/1+e^5-0.3*Distance) which weighs areas near anthropogenic features more heavily (probability of occurrence equals 0.90 at 8km) than far (probability of occurrence less than 0.001 at 30km). We modeled the utilization of sagebrush landscapes by synanthropic avian predators using five spatial data sets: 1) populated areas, 2) campgrounds, 3) rest stops, 4) agricultural land, and 5) landfills; and one input layer: density of liner features. All spatial data sets and the one input layer were converted to distance input layers. Each GIS layer was buffered with a probability function derived from the daily movement patterns of corvid species.
Using each of the five-buffered layers, we created a composite layer by adding the probabilities of occurrence of each layer. This composite layer, therefore, is a measure of synergistic effects that enhance synanthropic predator dispersal in relation to the spatial distribution of anthropogenic resources.

description: The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces. Within these provinces, Total Petroleum Systems are defined and Assessment Units are defined and assessed. Each of these provinces is defined geologically, and most province boundaries are defined by major geologic changes. The Bighorn Basin Province is located in Wyoming and south central Montana. The main population centers within the study area are Cody and Thermopolis, Wyoming. The main highways, I-70 and I-90, generally traverse the area from north to south. The Bighorn River and its tributaries drain the area. The province boundary was drawn to include the geologic structures generally considered to be in or bounding the Bighorn Basin.; abstract: The USGS Central Region Energy Team assesses oil and gas resources of the United States. The onshore and State water areas of the United States comprise 71 provinces. Within these provinces, Total Petroleum Systems are defined and Assessment Units are defined and assessed. Each of these provinces is defined geologically, and most province boundaries are defined by major geologic changes. The Bighorn Basin Province is located in Wyoming and south central Montana. The main population centers within the study area are Cody and Thermopolis, Wyoming. The main highways, I-70 and I-90, generally traverse the area from north to south. The Bighorn River and its tributaries drain the area. The province boundary was drawn to include the geologic structures generally considered to be in or bounding the Bighorn Basin.