SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES ANCESTRY - DP02 Universe - Total population. Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Ancestry refers to a person’s ethnic origin, heritage, descent, or “roots,” which may reflect their place of birth or that of previous generations of their family. Some ethnic identities, such as “Egyptian” or “Polish” can be traced to geographic areas outside the United States, while other ethnicities such as “Pennsylvania German” or “Cajun” evolved in the United States.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, for 2020, the 2020 Census provides the official counts of the population and housing units for the nation, states, counties, cities, and towns. For 2016 to 2019, the Population Estimates Program provides estimates of the population for the nation, states, counties, cities, and towns and intercensal housing unit estimates for the nation, states, and counties..Geographic areas are based on the geographic boundaries of the data year. Current year comparisons with past-year estimates are not re-tabulated to the current year's geographies; rather, the comparison is with the existing geography of each data year. Statistically significant change from prior years' estimates could be the result of changes in the geographic boundaries of an area and not necessarily the demographic, social, or economic characteristics. For more information on geographic changes, see: https://www.census.gov/programs-surveys/acs/guidance.html..Since the 5-year data do not benefit from data quality filtering, comparisons are only made for populations of 5,000 or more..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..The definitions of the metropolitan and micropolitan statistical areas for the 2013 American Community Survey are based on the commuting patterns identified in the 2010 Census. Estimates prior to 2013 are based on the results of the 2000 Census. Statistically significant change from prior years' estimates could be the result of changes in the metropolitan geographic definitions and not necessarily the demographic, social or economic characteristic. For more information, see: Metropolitan and Micropolitan Statistical Areas..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for Russian represents the number of people who listed Russian as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because official data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..Methodological changes to citizenship edits may have affected citizenship data for those born in American Samoa. Users should be aware of these changes when using 2018 data or multi-year data containing data from 2018. For more information, see: American Samoa Citizenship User Note..Fertility data are not available for certain geographic areas due to problems with data collection. See census.gov/programs-surveys/acs/technical-documentation/errata/119.html.The Census Bureau introduced a new set of disability questions in the 2008 ACS questionnaire. Accordingly, comparisons of disability data from 2008 or later with data from prior years are not recommended. For more information on these questions and their evaluation in the 2006 ACS Content Test, see the Evaluation Report Covering Disability..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; sa...

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

US Census American Community Survey (ACS) 2020, 5-year estimates of the key social characteristics of ZIP Code Tabulation Areas geographic level in Orange County, California. The data contains 500 fields for the variable groups S01: Households by type (universe: total households, table X11, 17 fields); S02: Relationship (universe: population in households, table X9, 19 fields); S03: Marital status (universe: population 15 years and over, table X12, 13 fields); S04: Fertility (universe: women 15-50 years who had birth in the past 12 months, table X13, 11 fields); S05: Grandparents (universe: grandparents living or responsible for own grandchildren under 18 years, table X10, 18 fields); S06: School enrollment (universe: population 3 years old and over enrolled in school, table X14, 17 fields); S07: Educational attainment (universe: population 25 years and over, table X15, 25 fields); S08: Veteran status (universe: civilian population 18 years and over, table X21, 2 fields); S09: Disability status and type by sex and age (universe: total civilian non-institutionalized population, table X18, 77 fields); S10: Disability status by age and health insurance coverage (universe: civilian non-institutionalized population, table X18, 16 fields); S11: Residence 1 year ago (universe: population 1 year and over, table X7, 6 fields); S12: Place of birth (universe: total population, table X5, 27 fields); S13: Citizenship status by nativity in the US (universe: total population, table X5, 6 fields); S14: Year of entry (universe: population born outside the US, table X5, 21 fields); S15: World region of birth of foreign born population (universe: foreign born population, excluding population born at sea, table X5, 25 fields); S16: Language spoken in households (universe: total households, table X16, 6 fields); S17: Language spoken at home (universe: population 5 years and over, table X16, 67 fields); S18: Ancestry (universe: total population reporting ancestry, table X4, 114 fields), and; S19: Computers and internet use (universe: total population in households and total households, table X28, 13 fields). The US Census geodemographic data are based on the 2020 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project GitHub page (https://github.com/ktalexan/OCACS-Geodemographics).

The American Community Survey 5-year Data Profile (DP02) of Selected Social Characteristics was downloaded from the U.S. Census Bureau for state, county, place, reservation, house district, senate district and tract geographies in the state of Montana.Selected social characteristics in this data set include: HOUSEHOLDS BY TYPE, RELATIONSHIP, MARITAL STATUS, FERTILITY, GRANDPARENTS, SCHOOL ENROLLMENT, EDUCATION ATTAINMENT, VETERAN STATUS, DISABILITY STATUS, RESIDENCE 1 YEAR AGO, PLACE OF BIRTH, U.S. CITIZENSHIP STATUS, YEAR OF ENTRY, WORLD REGION OF BIRTH OF FOREIGN BORN, LANGUAGE SPOKEN AT HOME, ANCESTRY, COMPUTERS AND INTERNET USE Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates. Downloaded April 2022.Please refer to the American Community Survey section of the U.S. Census Bureau website for detailed information about this data set.

In the U.S., median household income rose from 51,570 U.S. dollars in 1967 to 80,610 dollars in 2023. In terms of broad ethnic groups, Black Americans have consistently had the lowest median income in the given years, while Asian Americans have the highest; median income in Asian American households has typically been around double that of Black Americans.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

The American Community Survey 5-year Data Profile (DP02) of Selected Social Characteristics was downloaded from the U.S. Census Bureau for state, county, place, reservation, house district, senate district and tract geographies in the state of Montana.Selected social characteristics in this data set include: HOUSEHOLDS BY TYPE, RELATIONSHIP, MARITAL STATUS, FERTILITY, GRANDPARENTS, SCHOOL ENROLLMENT, EDUCATION ATTAINMENT, VETERAN STATUS, DISABILITY STATUS, RESIDENCE 1 YEAR AGO, PLACE OF BIRTH, U.S. CITIZENSHIP STATUS, YEAR OF ENTRY, WORLD REGION OF BIRTH OF FOREIGN BORN, LANGUAGE SPOKEN AT HOME, ANCESTRY, COMPUTERS AND INTERNET USE Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-Year Estimates. Downloaded April 2022.Please refer to the American Community Survey section of the U.S. Census Bureau website for detailed information about this data set.

Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2023 American Community Survey 1-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Ancestry listed in this table refers to the total number of people who responded with a particular ancestry; for example, the estimate given for German represents the number of people who listed German as either their first or second ancestry. This table lists only the largest ancestry groups; see the Detailed Tables for more categories. Race and Hispanic origin groups are not included in this table because data for those groups come from the Race and Hispanic origin questions rather than the ancestry question (see Demographic Table)..Data for year of entry of the native population reflect the year of entry into the U.S. by people who were born in Puerto Rico or U.S. Island Areas or born outside the U.S. to a U.S. citizen parent and who subsequently moved to the U.S..The category "with a broadband Internet subscription" refers to those who said "Yes" to at least one of the following types of Internet subscriptions: Broadband such as cable, fiber optic, or DSL; a cellular data plan; satellite; a fixed wireless subscription; or other non-dial up subscription types..An Internet "subscription" refers to a type of service that someone pays for to access the Internet such as a cellular data plan, broadband such as cable, fiber optic or DSL, or other type of service. This will normally refer to a service that someone is billed for directly for Internet alone or sometimes as part of a bundle.."With a computer" includes those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- ...

Globalization has led to the frequent movement of species out of their native habitat. Some of these species become highly invasive and capable of profoundly altering invaded ecosystems. Feral swine (Sus scrofa × domesticus) are recognized as being among the most destructive invasive species, with populations established on all continents except Antarctica. Within the United States (US), feral swine are responsible for extensive crop damage, the destruction of native ecosystems, and the spread of disease. Purposeful human-mediated movement of feral swine has contributed to their rapid range expansion over the past 30 years. Patterns of deliberate introduction of feral swine have not been well described as populations may be established or augmented through small, undocumented releases. By leveraging an extensive genomic database of 18,789 samples genotyped at 35,141 single nucleotide polymorphisms (SNPs), we used deep neural networks to identify translocated feral swine across the contiguous US. We classified 20% (3,364/16,774) of sampled animals as having been translocated and described general patterns of translocation using measures of centrality in a network analysis. These findings unveil extensive movement of feral swine well beyond their dispersal capabilities, including individuals with predicted origins >1,000 km away from their sampling locations. Our study provides insight into the patterns of human-mediated movement of feral swine across the US and from Canada to the northern areas of the US. Further, our study validates the use of neural networks to study the spread of invasive species. Methods Biological samples (n = 18,789) were collected from feral swine throughout their invaded range within the US as an extension of damage management and disease surveillance efforts led by the USDA along with cooperative agencies. Overwhelmingly, samples were collected by USDA‐Animal and Plant Health Inspection Service-Wildlife Services personnel. Feral swine were lethally removed through trapping or targeted sharpshooting from 2001-2022 as an extension of control efforts to reduce threats to agriculture, natural resources, property, and the health of humans and livestock. To identify potential translocations from Canada to the US, biological samples were collected from feral swine in Alberta (n = 13) and Saskatchewan (n = 14), Canada by the University of Saskatchewan under Animal Use Protocol Number 21050024. DNA extraction was performed by GeneSeek (Neogen Corporation [Lincoln, Nebraska, USA]) using various biological sample types (hair, pinna, and kidney) and the MagMaxTM DNA Multi-Sample Ultra Kit (Thermo Fisher Scientific Inc. [Walthan, MA, USA]). Genetic samples were genotyped using GeneSeek’s Genomic Profiler (GGP) for the Porcine 80k array (68,516 loci; Illumina BeadChip microarray [San Diego, California] licensed exclusively to GeneSeek, a Neogen Corporation, [Lincoln, Nebraska]) and aligned to the Sscrofa 11.1 genome assembly (Warr et al. 2020). As part of our quality control process, we removed individuals presumed to have escaped or released domestic pigs from production farms or the pet trade (i.e., Vietnamese potbellied pigs). To distinguish domestic pigs from genetically typical feral swine, we estimated the ancestry profiles of individuals based on the methods described in Smyser et al. (2020) and removed any individual with a combined ancestry of >0.4 from domestic pig breeds (Berkshire, Hampshire, Chester White, Duroc, Landrace, Yorkshire/Large White, Meishan, and miniature Siberian). Once individuals presumed to be escaped or released domestic pigs were removed, we conducted standard genotype quality control filters using PLINK 2.0 (Chang et al. 2015). First, we removed loci that were unmapped or non-autosomal based on the Sscrofa11.1 reference genome assembly (Warr et al., 2020). We then removed loci with call rates <0.95 or minor allele frequencies <0.05. Individuals were removed for downstream analyses if they were missing >5% of their genotype data. The resulting set of individual genotypes was considered the ‘master’ dataset.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.

The layer was derived and compiled from the U.S. Census Bureau’s 2013 – 2017 American Community Survey (ACS) 5-Year Estimates in order to assist 2020 Census planning purposes.

Source: U.S. Census Bureau, Table B04006 PEOPLE REPORTING ANCESTRY, 2013 – 2017 ACS 5-Year Estimates

Effective Date: December 2018

Last Update: December 2019

Update Cycle: ACS 5-Year Estimates update annually each December. Vintage used for 2020 Census planning purposes by Broward County.