The founding of New World populations by Asian peoples is the focus of considerable archaeological and genetic research, and there persist important questions on when and how these events occurred. Genetic data offer great potential for the study of human population history, but there are significant challenges in discerning distinct demographic processes. A new method for the study of diverging populations was applied to questions on the founding and history of Amerind-speaking Native American populations. The model permits estimation of founding population sizes, changes in population size, time of population formation, and gene flow. Analyses of data from nine loci are consistent with the general portrait that has emerged from archaeological and other kinds of evidence. The estimated effective size of the founding population for the New World is fewer than 80 individuals, approximately 1% of the effective size of the estimated ancestral Asian population. By adding a splitting parameter to population divergence models it becomes possible to develop detailed portraits of human demographic history. Analyses of Asian and New World data support a model of a recent founding of the New World by a population of quite small effective size.

Colonisation is a fundamental ecological and evolutionary process that drives the distribution and abundance of organisms. The initial ability of colonists to establish is determined largely by the number of founders and their genetic background. We explore the importance of these demographic and genetic properties for longer term persistence and adaptation of populations colonising a novel habitat using experimental populations of Tribolium castaneum. We introduced individuals from three genetic backgrounds (inbred – outbred) into a novel environment at three founding sizes (2–32), and tracked populations for seven generations. Inbreeding had negative effects, whereas outbreeding generally had positive effects on establishment, population growth and long-term persistence. Severe bottlenecks due to small founding sizes reduced genetic variation and fitness but did not prevent adaptation if the founders originated from genetically diverse populations. Thus, we find important and largely independent roles for both demographic and genetic processes in driving colonisation success.

The introduction of non-native species can have long-term effects on native plant and animal communities. Introduced populations are occasionally not well understood and offer opportunities to evaluate changes in genetic structure through time and major population changes such as bottleneck and or founder events. Invasive species can often evolve rapidly in new and novel environments, which could be essential to their long-term success. Sika deer are native to East Asia, and their introduction and establishment to the Delmarva Peninsula, USA is poorly documented, but probably involved ≥1 founder and/or bottleneck events. We quantified neutral genetic diversity in the introduced population and compared genetic differentiation and diversity to the presumed source population from Yakushima Island, Japan, and a captive population of sika deer in Harrington, Delaware, USA. Based on data from 10 microsatellite DNA loci, we observed reduced genetic variation attributable to founder events, support for historic hybridization events, and evidence that the population did originate from Yakushima Island stocks. Estimates of population structure through Bayesian clustering and demographic history derived from Approximate Bayesian Computation (ABC), were consistent with the hypothesized founder history of the introduced population in both timing and effective population size (approximately 5 effective breeding individuals, an estimated 36 generations ago). Our ABC results further supported a single introduction into the wild happening before sika deer spread throughout the Delmarva. We conclude that free-ranging sika deer on Delmarva are descended from ca. 5 individuals introduced about 100 years ago from captive stocks of deer maintained in the United Kingdom. Free-ranging sika deer on Delmarva have lost neutral diversity due to founder and bottleneck events, yet populations have expanded in recent decades and show no evidence of abnormalities associated with inbreeding. We suggest management practices including increasing harvest areas and specifically managing sika deer outside of Maryland.

In 2024, the share of male tech startup founders stood at approximately ** percent. In contrast, the proportion of female founders was around ** percent.

In the past four centuries, the population of the Thirteen Colonies and United States of America has grown from a recorded 350 people around the Jamestown colony in Virginia in 1610, to an estimated 346 million in 2025. While the fertility rate has now dropped well below replacement level, and the population is on track to go into a natural decline in the 2040s, projected high net immigration rates mean the population will continue growing well into the next century, crossing the 400 million mark in the 2070s. Indigenous population Early population figures for the Thirteen Colonies and United States come with certain caveats. Official records excluded the indigenous population, and they generally remained excluded until the late 1800s. In 1500, in the first decade of European colonization of the Americas, the native population living within the modern U.S. borders was believed to be around 1.9 million people. The spread of Old World diseases, such as smallpox, measles, and influenza, to biologically defenseless populations in the New World then wreaked havoc across the continent, often wiping out large portions of the population in areas that had not yet made contact with Europeans. By the time of Jamestown's founding in 1607, it is believed the native population within current U.S. borders had dropped by almost 60 percent. As the U.S. expanded, indigenous populations were largely still excluded from population figures as they were driven westward, however taxpaying Natives were included in the census from 1870 to 1890, before all were included thereafter. It should be noted that estimates for indigenous populations in the Americas vary significantly by source and time period. Migration and expansion fuels population growth The arrival of European settlers and African slaves was the key driver of population growth in North America in the 17th century. Settlers from Britain were the dominant group in the Thirteen Colonies, before settlers from elsewhere in Europe, particularly Germany and Ireland, made a large impact in the mid-19th century. By the end of the 19th century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. It is also estimated that almost 400,000 African slaves were transported directly across the Atlantic to mainland North America between 1500 and 1866 (although the importation of slaves was abolished in 1808). Blacks made up a much larger share of the population before slavery's abolition. Twentieth and twenty-first century The U.S. population has grown steadily since 1900, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. Since WWII, the U.S. has established itself as the world's foremost superpower, with the world's largest economy, and most powerful military. This growth in prosperity has been accompanied by increases in living standards, particularly through medical advances, infrastructure improvements, clean water accessibility. These have all contributed to higher infant and child survival rates, as well as an increase in life expectancy (doubling from roughly 40 to 80 years in the past 150 years), which have also played a large part in population growth. As fertility rates decline and increases in life expectancy slows, migration remains the largest factor in population growth. Since the 1960s, Latin America has now become the most common origin for migrants in the U.S., while immigration rates from Asia have also increased significantly. It remains to be seen how immigration restrictions of the current administration affect long-term population projections for the United States.

High propagule pressure is arguably the only consistent predictor of colonization success. More individuals enhance colonization success because they aid in overcoming demographic consequences of small population size (e.g. stochasticity and Allee effects). The number of founders can also have direct genetic effects: with fewer individuals, more inbreeding and thus inbreeding depression will occur, whereas more individuals typically harbour greater genetic variation. Thus, the demographic and genetic components of propagule pressure are interrelated, making it difficult to understand which mechanisms are most important in determining colonization success. We experimentally disentangled the demographic and genetic components of propagule pressure by manipulating the number of founders (fewer or more), and genetic background (inbred or outbred) of individuals released in a series of three complementary experiments. We used Bemisia whiteflies and released them onto either their natal host (benign) or a novel host (challenging). Our experiments revealed that having more founding individuals and those individuals being outbred both increased the number of adults produced, but that only genetic background consistently shaped net reproductive rate of experimental populations. Environment was also important and interacted with propagule size to determine the number of adults produced. Quality of the environment interacted also with genetic background to determine establishment success, with a more pronounced effect of inbreeding depression in harsh environments. This interaction did not hold for the net reproductive rate. These data show that the positive effect of propagule pressure on founding success can be driven as much by underlying genetic processes as by demographics. Genetic effects can be immediate and have sizable effects on fitness.

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

Genetic effects are often overlooked in endangered species monitoring, and populations showing positive growth are often assumed to be secure. However, the continued reproductive success of a few individuals may mask issues such as inbreeding depression, especially in long-lived species. Here, we test for inbreeding depression in little spotted kiwi (Apteryx owenii) by comparing a population founded with two birds to one founded with 40 birds, both from the same source population and both showing positive population growth. We used a combination of microsatellite genotypes, nest observations and modelling to examine the consequences of assessing population viability exclusively via population growth. We demonstrate (i) significantly lower hatching success despite significantly higher reproductive effort in the population with two founders; (ii) positive growth in the population with two founders is mainly driven by ongoing chick production of the founding pair; and (iii) a substantial g...

ABSTRACT This study evaluated the population structure of sheep without wool from the conservation nucleus in Ceará State, Brazil. Population parameters were estimated on genealogical records of Santa Ines (SI), Somali (SO,) and Morada Nova (MN) breeds, that were born between 2001 and 2014. The following estimates were obtained: number of complete generation equivalents (GCE), generation intervals (IEG), number of founders (Nf), effective number of founders (fe), effective number of ancestors (fa), inbreeding coefficient (F), and genetic contribution index (ICG). Average GCE was 1.82, 2.78, and 1.52 for SI, SO, and MN respectively. Mean IEG was similar between breeds, 3.67 years. The Nf was 225, 194, and 153 for SI, SO, and MN respectively. The fe/fa ratios were different to 1, which is an indication of genetic bottleneck, mainly for SO. The average inbreeding coefficients were 1.81%, 0.78%, and 0.78% for SI, SO, and MN respectively. The ICG was 3.32, 5.38, and 2.87 for SI, SO, and MN respectively. Estimated population parameters indicate that part of the genetics of these breeds was lost, mainly in Somalis.

In the past four centuries, the population of the United States has grown from a recorded 350 people around the Jamestown colony of Virginia in 1610, to an estimated 331 million people in 2020. The pre-colonization populations of the indigenous peoples of the Americas have proven difficult for historians to estimate, as their numbers decreased rapidly following the introduction of European diseases (namely smallpox, plague and influenza). Native Americans were also omitted from most censuses conducted before the twentieth century, therefore the actual population of what we now know as the United States would have been much higher than the official census data from before 1800, but it is unclear by how much. Population growth in the colonies throughout the eighteenth century has primarily been attributed to migration from the British Isles and the Transatlantic slave trade; however it is also difficult to assert the ethnic-makeup of the population in these years as accurate migration records were not kept until after the 1820s, at which point the importation of slaves had also been illegalized. Nineteenth century In the year 1800, it is estimated that the population across the present-day United States was around six million people, with the population in the 16 admitted states numbering at 5.3 million. Migration to the United States began to happen on a large scale in the mid-nineteenth century, with the first major waves coming from Ireland, Britain and Germany. In some aspects, this wave of mass migration balanced out the demographic impacts of the American Civil War, which was the deadliest war in U.S. history with approximately 620 thousand fatalities between 1861 and 1865. The civil war also resulted in the emancipation of around four million slaves across the south; many of whose ancestors would take part in the Great Northern Migration in the early 1900s, which saw around six million black Americans migrate away from the south in one of the largest demographic shifts in U.S. history. By the end of the nineteenth century, improvements in transport technology and increasing economic opportunities saw migration to the United States increase further, particularly from southern and Eastern Europe, and in the first decade of the 1900s the number of migrants to the U.S. exceeded one million people in some years. Twentieth and twenty-first century The U.S. population has grown steadily throughout the past 120 years, reaching one hundred million in the 1910s, two hundred million in the 1960s, and three hundred million in 2007. In the past century, the U.S. established itself as a global superpower, with the world's largest economy (by nominal GDP) and most powerful military. Involvement in foreign wars has resulted in over 620,000 further U.S. fatalities since the Civil War, and migration fell drastically during the World Wars and Great Depression; however the population continuously grew in these years as the total fertility rate remained above two births per woman, and life expectancy increased (except during the Spanish Flu pandemic of 1918).

Since the Second World War, Latin America has replaced Europe as the most common point of origin for migrants, with Hispanic populations growing rapidly across the south and border states. Because of this, the proportion of non-Hispanic whites, which has been the most dominant ethnicity in the U.S. since records began, has dropped more rapidly in recent decades. Ethnic minorities also have a much higher birth rate than non-Hispanic whites, further contributing to this decline, and the share of non-Hispanic whites is expected to fall below fifty percent of the U.S. population by the mid-2000s. In 2020, the United States has the third-largest population in the world (after China and India), and the population is expected to reach four hundred million in the 2050s.

his thematic map illustrates the rates of owner occupied housing in DuPage County for 2010. A housing unit is owner occupied if the owner or co-owner lives in the unit. This data variable is included in Esri's Updated Demographics (2010/2015).This map shows Esri's 2010 estimates using Census 2000 geographies. The map is designed to be displayed with 30–50 percent semi-transparency for overlay on other basemaps as noted in the map legend. A basemap with relatively few colors, such as Terrain, works well with this map when transparency is used.A web map that combines this service with the Terrain basemap and a reference overlay for easy viewing is here.The geography depicts States at greater than 25m scale, Counties at 750k to 25m scale, Census Tracts at 150k to 750km scale, and Census Block Groups at less than 150k scale.Esri's Updated Demographics Data (2010/2015) – Population, age, income, sex, and race are among the variables included in the database. Each year, Esri's data development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of geographies. See Updated Demographics for more information.

The Founders and Survivors Online Database is a searchable population database of all convicts transported to Tasmania in the 19th century.

Population introductions and reintroductions have become a common tool for conserving threatened species, but oftentimes introduced populations have reduced the genetic diversity compared with the source population they were founded from. Population introductions played an important role in the recovery of the Oregon Chub Oregonichthys crameri, a small floodplain minnow found in western Oregon. Unlike many introduction efforts, introduced populations of Oregon Chub were founded using large numbers of individuals (hundreds in many cases) and each population had a unique introduction history (e.g., number of founders, source populations selected, duration of the introduction effort). We used microsatellite loci to examine 13 introduced populations and their respective sources to evaluate how well the introduction program captured genetic diversity present in the wild populations. Genetic variation was reduced by roughly 25% in one introduced population, and three introduced populations showed evidence of a genetic bottleneck due to heterozygote excess. Populations introduced from multiple sources had greater genetic diversity than populations from a single source. When multiple source populations were used, all source populations contributed genetic material to the introduced population, though the proportional contribution from each source population varied. Using correlation analyses and general linear models, we explored the relationship between introduction history variables and genetic diversity. Our top-ranked models included genetic diversity in the source population, and this variable had the highest variable importance weight (0.999), but the number of founders and the number of source populations were also important. Overall, the Oregon Chub introduction program was highly successful at capturing the genetic variation observed in natural populations. Results of this study will be useful for planning future population introductions for Oregon Chub and other species of conservation concern.

ABSTRACT The objective of this research was to study the population structure of the Cattle Conservation Nucleos Curraleiro Pé Duro of the Instituto Nacional do Semiárido (NCP_INSA) based on pedigree data. Genealogical information from 338 animals registered in the period from 1991 to 2019 was used. The number of founding animals (Nf), the effective number of founders (fe), effective number of ancestors (fa), inbreeding coefficient (F), and average relatedness coefficient (AR), in addition to Fis, Fit and Fst were estimated. It was possible to identify ancestors up to the third generation, with an increase in information over the generations. Of the total pedigree information evaluated, 90.53% had the identification of the father and mother. The effective size of the population was smaller than those proposed by FAO, suggesting the need to redefine the herd management and genetic management plan strategies, promoting gene flow and breed expansion.

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..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..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..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- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

Aim: The biodiversity of the Malay Archipelago is the product of the region's rich biogeographical history with periods of island connectivity and isolation during the Pleistocene glacial cycles. Here, the case of two endemic suid species, the Javan (Sus verrucosus) and Bawean (S. blouchi) warty pigs, was used to illustrate how biogeographic processes and recent anthropogenic pressures can shape demographic histories with significant implications for species conservation.

Location: Malay Archipelago, with focus on Bawean and Java.

Methods: We employed genome-wide single nucleotide polymorphisms from the Porcine SNP60 v2 BeadChip to assess interspecific genetic differentiation, to estimate divergence times, and to perform demographic model selection.

Results: In contrast to the hypothesis of recent divergence during the last glacial maximum, S. blouchi was found to have diverged from S. verrucosus at least 166k years ago following a founder event. The contemporary S. blouchi population was characterised by a recent bottleneck that reduced the effective population size to less than 20. The genomic assessment supports the single species status of S. blouchi, as was previously proposed based on morphometrics. The demographic history of S. verrucosus showed evidence of secondary contact with the sympatric banded pig (S. scrofa vittatus) that colonised Java 70k years ago.

Main conclusions: While the Javan and Bawean warty pigs have persisted throughout the Pleistocene climatic oscillations, contemporary pressures from human activities threaten their survival and immediate action should be taken to grant legal protection to both S. verrucosus and S. blouchi. This study highlighted the use of demographic history modelling using genomic data to identify evolutionary significant units and inform conservation.

SNP Genotype and Phenotype datasets for the NIAB DIVERSE MAGIC wheat population and its founders. The diverse MAGIC wheat population was developed at the National Institute for Applied Botany (NIAB), from whom germplasm is available (contact James Cockram).Summary of the Data Sets available here:(i) Founder_Consensus_Genotypes.calls.adjusted.txt, All_MAGIC_Consensus_Genotypes.calls.adjusted.txt: Tab-delimited genotypes of the 16 founders of the NIAB DIVERSE MAGIC wheat population and for 550 MAGIC lines, obtained using the 35k Wheat Breeders' Array. Calls were made using the Axiom Best Practices Genotyping Analysis workflow with an inbreeding penalty of 4. The released genotypes have consensus calls where multiple samples were genotyped from the same line. In addition, the genotypes at sites with no minor homozygous calls have been adjusted.(ii) FOUNDERS.tar, MAGIC_PLINK.tar: Genotypes in PLINK format of 1.1M imputed SNPs from exome capture in the 16 founders and and low -coverage sequencing in 505 MAGIC lines.(iii) MAGIC_PLINK_PRUNED.tar 55k tagging SNP genotypes of 505 MAGIC lines, suitable for GWAS(iv) MAGIC_PHENOTYPES.txt Phenotypes for the MAGIC lines and founders.(v) BASIC_GWAS.tar contains the genotypes and phenotypes and analysis scripts packaged into one file. We provide a simple pipeline for genetic mapping with these data.Once unpacked, the 'DATA' subdirectory contains the phenotypic data and the tagging set of ~55k SNP sites called in 504 inbred lines. In this directory, we include R functions for association mapping (file mixed.model.functions.r), including a mixed model transformation to remove the inflationary effects of unequal relatedness on genetic associations. Association mapping can be run on the basis of SNPs or the inferred founder haplotype dosages. To run, follow the steps in the R script example.analysis.r (this will run without modification if the downloaded directory is used as the R working directory). We also include a function for plotting the results as a manhattan plot (plot.functions.r).

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, 2019-2023 American Community Survey 5-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..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..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..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- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.

This collection provides a complete list of convict names and sufficient biographical data to enable unambiguous identification of convicts who were disembarked from convict ship "Thames" at Van Diemen's Land on 1829-11-21

This includes, where known, an estimation of the year of birth, place of birth, where and when convicted, the sentence, the date of arrival in the colony and the convict's age on arrival. The brief convict biographical data provided in this collection serves as an index into the far more extensive set of life course events which are recorded in the prosopgraphy database built by the Founders and Survivors project.

Basic details for this ship: * ship name (as known in VDL records): Thames * sailed date : 1829-07-31 from London * arrival date : 1829-11-21 * population (per Bateson's The Convict Ships): Embarked:160 Men ; Deaths:2 Men ; Landed:158(VDL) Men

Data for convicts listed in this collection comes from the source which has been determined by Founders and Survivors to form the "base population" for this ship. Further information as to the methodology and the linkage of multiple sources is detailed in the narrative format of the collection. The matching and linkage of additional sources about Tasmanian convict's is the subject of ongoing research. This collection may be repuplished regularly, and in additional formats and with specific user interfaces, to enable public participation in the quality of convict matching and linkage -- see for example the EXPERIMENTAL linkage.htm format for this collection. Linkage for ships arriving at Norfolk Island and Port Philip is incomplete.

This ship's prosopography index is published in a directory named "360.14" (the ship's project id). Three three different file formats provided: -- (default; suitable for web browsing) HTML: world wide web hypertext markup language format which provides a "narrative" view of the collection (index.htm); and -- (structured prosopgraphy: persons and events) XML / TEIp5 : Text Encoding Initiative (version p5) XML format which provides the underlying XML database for this collection (index.xml); and -- Not yet available simple list of convict names in a flat file, tab delimited, suitable for Excel, Stata, SPSS or database usage (index.tab). See notes below.

Density dependence in reproduction plays an important role in stabilising population dynamics via immediate negative feedback from population density to reproductive output. Although previous studies have shown that negative density-dependent reproduction is associated with strong spacing behaviour and social interaction between individuals, the proximal mechanism for generating negative density-dependent reproduction remains unclear. In this study, we investigated the effects of density-induced stress on reproduction in root voles. Enclosed Founder populations were established by introducing six (low density) and 30 (high density) adults per sex into per enclosure (four enclosures per density in total) during the breeding season from April to July 2012 and from May to August 2015. Faecal corticosterone metabolite (FCM) levels, reproductive traits (recruitment rate and the proportion of reproductively active indivuduals), and founder population numbers were measured following repeated live-trapping in both years. The number of founders was negatively associated with recruitment rates and the proportion of reproductively active indivuduals, displaying a negative density-dependent reproduction. FCM level was positively associated with the number of founders. The number of founder females directly affected the proportion of reproductive females , and directly and indirectly through their FCM levels affected the recruitment rate; the effect of the number of male founders on the proportion of reproductive males was mediated by their FCM level. Our results showed that density-induced stress negatively affected reproductive traits and that density-induced stress is one ecological factor generating negative density-dependent reproduction. Methods Root voles in the study area Our study was conducted at Haibei Alpine Meadow Ecosystem Research Station, Menyuan County, approximately 155 km north of Xining, the capital city of Qinghai province, People’s Republic of China (37°370´N, 101°120´E). The area is a secondary vegetation type meadow with a dense leaf layer. The major plant species include Elymus nutans, Poa sp., Kobresia humilis, and Potentila fruticosa. The root vole is the most common rodent in the study area. Root-vole populations in this area fluctuate only seasonally, with the lowest levels occurring in early spring; multiyear cycles are weak or absent (Jiang et al., 1991). Root voles have a preference for dense vegetation (mainly E. nutans) (Liu et al., 1991; Bian et al., 1994). The average population size across the study sites ranged from 70 to 170 voles ha-1 during the past 20 years, while in certain dense grassland sites, where grazing activities were limited and vegetation consisted mainly of E. nutans, the density reached to c. 400 voles ha-1 in late autumn (high level season, Jiang et al.,1991; Bian et al., 1994; Sun et al., 2002). The breeding season typically lasts from April to late October. Females have exclusive territoriality during the breeding season; males, conversely, have large area ranges that extensively overlap with those of other males (Sun et al., 1982). The lifetime of free-ranging individuals is < 1 year. Spring-born individuals attain sexual maturity in the year they are born; fall-born voles remain reproductively inactive during winter (Bian et al., 2015). Experimental facility The experiment was undertaken in eight 0.15-ha (50 × 30 m) outdoor enclosures in 2012 and 2015. The enclosures were constructed using galvanised steel panels (1.5 m aboveground and 0.5 m belowground), which prevented mammalian predators from gaining entry. Avian predators were excluded by a 3 × 3 cm grid wire mesh held aloft by a central pillar (10 × 250 cm) in each enclosure. Each enclosure was equipped with 60 laboratory-made wooden traps (Bian et al., 2015), spaced in a 5 × 5 m grid. Each trap was covered with a wooden sheet to protect it from exposure to precipitation and temperature extremes. Establishment of populations and live-trapping A total of 288 voles of each sex, 6 months of age or older, were separately used to establish the enclosure populations in 2012 and 2015. They were either F2 generations born in the laboratory or captured as juveniles in the previous year. All individuals were tagged in the ear with identifying metal tags. The populations were introduced into the enclosures in April 2012 and May 2015 at two density conditions. According to the the low- and high- density levels observed in nature (Jiang et al.,1991; Bian et al., 1994; Sun et al., 2002), the low-density condition consisted of six adults per sex in each of the four enclosures, and the high-density condition consisted of 30 adults per sex in each of the other four enclosures in 2012 and 2015. The initial body weights did not differ among the voles in the different enclosures (F7,280 = 1.72, P = 0.103 in 2012, F7,280 = 0.192, and P = 0.987 in 2015). Live-trapping started after allowing the animals to acclimate to their new environments for two weeks and lasted until late July 2012 and August 2015, respectively. Standard capture–mark–recapture methods were used throughout the study. Six trapping sessions were conducted in 2012 and seven in 2015; each consisted of three trapping days. The time interval between any two trapping sessions was one week. The traps were set between 7 AM and 7 PM, baited with a bit of carrot, checked every 2 h, and locked closed when trapping did not occur. Following each capture, we recorded animal identification, sex, and body mass. Females were considered reproductive if they had enlarged nipples and teats barren of hair. Males were considered in breeding conditions if their testes were scrotal rather than abdominal. The animal was, then, released at the point of capture after handling. The F1 offspring born in the enclosures were captured at 20–30 days of age and permanently moved to the laboratory for use in subsequent experiments (Bian et al., 2015; Yang et al., 2018). Fecal corticosterone metabolite (FCM) measurement FCM levels reflect the level of circulating corticosterone that occurred 10–12 h previously in root voles (He et al., 2013), and FCM is derived primarily from plasma-free corticosterone in rodents (Sheriff et al., 2010). Faecal samples for the FCM analysis were collected during the first 2 h of trapping (09:00–11:00 AM), and each captured animal was sampled once within a 3-day trapping session; thus, all animals provided only a single sample in each trapping session. Meanwhile, each trap was cleaned with water before collecting the faecal sample, ensuring that the samples were not influenced by the previous trapping or time of day. Traps used to sample faeces only had a few carrots. Faecal samples from pregnant females were not collected to avoid confounding effects of reproduction states on FCM levels (McDonald, 1998; Edwards & Boonstra, 2018). The total number of faecal samples was 546 and 832 in 2012 and 2015, respectively, throughout each experiment, and they accounted for 59% and 67% of the sum of minimum number known alive in each trapping session throughout the duration of experiments in both years (excluding reproductive females). The collected samples were, then, frozen in ice, transported to the laboratory, and stored in a −20°C freezer until analysis. FCM was measured following the methods outlined by Yang et al. (2018), previously validated for root voles. First, the collected faecal samples were lyophilised (Labconco, Kansas City, MO, USA) for 14–18 h, ground into particles, and homogenised in 0.5 mL NaOH solution (0.04 M). The extraction of FCM was performed by adding 5 mL of CH2Cl2 to the sample (0.1 g), followed by sonication for 15 min (Pihl & Hau, 2003) and centrifugation for 15 min at 3,000 g. After centrifugation, 1 mL of the solution was taken from the organic layer, diluted with 3 mL CH2Cl2, and then mixed with 4 mL of a mixed solution of sulfuric acid and ethanol (7:3, v:v). The samples were, then, shaken for 2 min and rested for 30 min before separation of the sulfuric acid layer for fluorescence detection. The fluorescence density in each sample was measured using an RF-540 IPC Fluorometer (Shimadzu, Japan) at excitation and emission wavelengths of 470 and 520 nm, respectively, and the FCM concentration in each sample was calculated based on the fluorescence densities produced by varying concentrations of the standard (Chen et al., 2012). Statistical analysis We used the minimum number known alive (MNKA) method to estimate the founder numbers. The recruitment rate was calculated as the recruits captured in a trapping session divided by the adult females captured in the second preceding session in each enclosure.. The proportion of the reproductively active individuals was evaluated using the numbers of reproductively active voles divided by the total numbers of adults captured for each sex in a trapping session. Recapture rate was calculated as the numbers of captured individual divided by MNKA in a trapping session. We used generalized linear mixed models (GLMMs) in SPSS v.19 (IBM, Armonk, NY, USA) to test the effects of population density on founder number, reproduction and recapture rate. We combined the both years data to increase the statistical power. Founder number, proportion of reproductively active individual, recruitment rate and recapture rate as response variables, the treatment, sex and time as predictor variables for founder numbers analyses and treatment, time as predictor variables for other data analyses, predictor variables were entered in all the models to test separately the main and interactive effects. In all data analyses, fence and year were both specified as random effects, which allowed for correlated responses within years and fences. Factor fence was nested within factor year. Because founder number is subject to poisson distribution, response variables were analysed using poisson distribution and