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.

About this dataset

Context

The dataset tabulates the United States population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of United States across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of United States was 333,287,557, a 0.38% increase year-by-year from 2021. Previously, in 2021, United States population was 332,031,554, an increase of 0.16% compared to a population of 331,511,512 in 2020. Over the last 20 plus years, between 2000 and 2022, population of United States increased by 51,125,146. In this period, the peak population was 333,287,557 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the United States is shown in this column.
• Year on Year Change: This column displays the change in United States population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for United States Population by Year. You can refer the same here

Four British bumblebee species (Bombus terrestris, Bombus hortorum, Bombus ruderatus and Bombus subterraneus) became established in New Zealand following their introduction at the turn of the last century. Of these, two remain common in the UK (B. terrestris and B. hortorum), whilst two (B. ruderatus and B. subterraneus) have undergone marked declines, the latter being declared extinct in 2000. The presence of these bumblebees in New Zealand provides an unique system in which four related species have been isolated from their source population for over 100 years, providing a rare opportunity to examine the impacts of an initial bottleneck and introduction to a novel environment on their population genetics. We used microsatellite markers to compare modern populations of B. terrestris, B. hortorum and B. ruderatus in the UK and New Zealand and to compare museum specimens of British B. subterraneus with the current New Zealand population. We used Approximate Bayesian Computation (ABC) to estimate demographic parameters of the introduction history, notably to estimate the number of founders used in the initial introduction. Species-specific patterns derived from genetic analysis were consistent with predictions based on the presumed history of these populations; demographic events have left a marked genetic signature on all four species. Approximate Bayesian analyses suggest that the New Zealand population of B. subterraneus may have been founded by as few as two individuals, giving rise to low genetic diversity and marked genetic divergence from the (now extinct) UK population.

About this dataset

Context

The dataset tabulates the Florida population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Florida across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Florida was 22,244,823, a 1.91% increase year-by-year from 2021. Previously, in 2021, Florida population was 21,828,069, an increase of 1.10% compared to a population of 21,589,602 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Florida increased by 6,198,675. In this period, the peak population was 22,244,823 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Florida is shown in this column.
• Year on Year Change: This column displays the change in Florida population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Florida Population by Year. You can refer the same here

This dataset contains demographic data for Cynoglossum officinale L. (Boraginaceae) collected at 3 sites in its native range and 3 sites in the introduced range from 2004 to 2007 (sampled 2 times/year). These data were used to parameterize integral projection models to investigate differences in life history between the native and introduced range (Williams 2009) and to investigate the impacts of native specialist insects and small-scale disturbances on population growth (Williams et al. 2010). Individual fate and size data of marked and mapped individuals in 1 m x 10 m transects were collected at 2 censuses per year (spring and summer), seed production was measured during the summer census; new seedlings were added each spring. These are all the data required to parameterize a population model (matrix model or integral projection model). This dataset includes 3 tables: 1) location of individual (to the nearest decimeter); 2) fate, size and amount of leaf herbivory at each census; 3) seedling fate in each transect (the fate of individuals was not followed). References: Williams, J. L. 2009. Flowering life-history strategies differ between the native and introduced ranges of a monocarpic perennial. American Naturalist 174:660-672; Williams, J. L., H. Auge, and J. L. Maron. 2010. Impacts of herbivore escape and disturbance on exotic plant success. Ecology 91:1355-1366.

We explored possible links between vector activity and genetic diversity in introduced populations of Limnoperna fortunei by characterizing the genetic structure in native and introduced ranges in Asia and South America. We surveyed 24 populations: ten in Asia and 14 in South America using the mitochondrial cytochrome c oxidase subunit I (COI) gene, as well as eight polymorphic microsatellite markers. We performed population genetics and phylogenetic analyses to investigate population genetic structure across native and introduced regions. Introduced populations in Asia exhibit higher genetic diversity (HE = 0.667–0.746) than those in South America (HE = 0.519–0.575), suggesting higher introduction effort for the former populations. We observed pronounced geographical structuring in introduced regions, as indicated by both mitochondrial and nuclear markers based on multiple genetic analyses including pairwise ФST, FST, Bayesian clustering method, and three-dimensional factorial correspondence analyses. Pairwise FST values within both Asia (FST = 0.017–0.126, P = 0.000–0.009) and South America (FST = 0.004–0.107, P = 0.000–0.721) were lower than those between continents (FST = 0.180–0.319, P = 0.000). Fine-scale genetic structuring was also apparent among introduced populations in both Asia and South America, suggesting either multiple introductions of distinct propagules or strong post-introduction selection and demographic stochasticity. Higher genetic diversity in Asia as compared to South America is likely due to more frequent propagule transfers associated with higher shipping activities between source and donor regions within Asia. This study suggests that the intensity of human-mediated introduction vectors influences patterns of genetic diversity in non-indigenous species.

Many populations are small and isolated with limited genetic variation and high risk of mating with close relatives. Inbreeding depression is suspected to contribute to extinction of wild populations, but the historical and demographic factors that contribute to reduced population viability are often difficult to tease apart. Replicated introduction events in non-native species can offer insights into this problem because they allow us to study how genetic variation and inbreeding depression are affected by demographic events (e.g. bottlenecks), genetic admixture and the extent and duration of isolation. Using detailed knowledge about the introduction history of 21 non-native populations of the wall lizard Podarcis muralis in England, we show greater loss of genetic diversity (estimated from microsatellite loci) in older populations and in populations from native regions of high diversity. Loss of genetic diversity was accompanied by higher embryonic mortality in non-native populations, suggesting that introduced populations are sufficiently inbred to jeopardize long-term viability. However, there was no statistical correlation between population-level genetic diversity and average embryonic mortality. Similarly, at the individual level, there was no correlation between female heterozygosity and clutch size, infertility or hatching success, or between embryo heterozygosity and mortality. We discuss these results in the context of human-mediated introductions and how the history of introductions can play a fundamental role in influencing individual and population fitness in non-native species.

About this dataset

Context

The dataset tabulates the Bellflower population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Bellflower across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Bellflower was 343, a 0.29% decrease year-by-year from 2021. Previously, in 2021, Bellflower population was 344, a decline of 0.29% compared to a population of 345 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Bellflower decreased by 50. In this period, the peak population was 393 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Bellflower is shown in this column.
• Year on Year Change: This column displays the change in Bellflower population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Bellflower Population by Year. You can refer the same here

This table includes information on the size of the Dutch population, as well as births, deaths, international migration, persons who moved within or between municipalities, marriages, registered partnerships, marriage dissolutions and requests for asylum, per month, quarter and year.

Since January 2010, a new production system has become operational to process municipal population data. As from 2010 onwards, with the introduction of the new system the following changes were implemented: - Provisional figures on live births by rank number and marital status of the mother will no longer be available. Definite figures will be added to the table on an annual basis; - Marriages will include registered partnerships; - Data on registered partnerships will be discontinued; - Married persons will include persons who have signed partnership contracts. An extra preceding marital status (married) has been added; - Marriage dissolutions will be presented including registered partnership dissolutions; - Divorced persons will be presented including legally terminated partnerships; - Data on persons who have moved house within the Netherlands will no longer be broken down by place in the household.

Statistics Netherlands will reorganise the tables relating to statistics on population and households. The aim is to reduce the number of tables while striving to preserve (much) needed information. This table will be revised in 2018.

Data available from: 1995

Status of the figures: - All figures on Asylum requests are final. - All figures of 1995 up to and including 2017 are final. - Figures for the 1st of January 2018 are final, the other figures on the population of 2018 are provisional. - The updating of asylum applications in this table is discontinued with effect from 2012.

Changes effective from 28 September 2018: Provisional figures of August 2018 have been added.

When will new figures be published? At the end of each month provisional figures of the most important subjects of the previous month will be added in this publication. Data for previous months may be subject to adjustment.

About this dataset

Context

The dataset tabulates the Conover town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Conover town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Conover town was 1,366, a 1.26% increase year-by-year from 2021. Previously, in 2021, Conover town population was 1,349, an increase of 2.20% compared to a population of 1,320 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Conover town increased by 236. In this period, the peak population was 1,366 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Conover town is shown in this column.
• Year on Year Change: This column displays the change in Conover town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Conover town Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Yonkers population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Yonkers across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Yonkers was 207,657, a 0.36% decrease year-by-year from 2022. Previously, in 2022, Yonkers population was 208,406, a decline of 0.79% compared to a population of 210,075 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Yonkers increased by 11,442. In this period, the peak population was 210,994 in the year 2020. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Yonkers is shown in this column.
• Year on Year Change: This column displays the change in Yonkers population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Yonkers Population by Year. You can refer the same here

Microsatellite genotypes for contemporary invasive (CI), contemporary native (CN) and historical native (HN) populationsMicrosatellite genotypes for smallmouth bass (Micropterus dolomieu) collected in a contemporary invasive range (CI- South Africa) and contemporary and historical native range (CN & HN - USA).Dryad submission_Microsatellite genotypes.xlsxcytb mtDNA sequencescytb mtDNA sequences for Micropterus dolomieu in an invasive (South Africa) and native (USA) rangeSA_USA_cytb.fasControl Region sequences for Micropterus dolomieuCR mtDNA sequences for Micropterus dolomieu in an invasive (South Africa) and native (USA) rangeSA_USA_cr.fas

Abstract

The Thai Demographic and Health Survey (TDHS) was a nationally representative sample survey conducted from March through June 1988 to collect data on fertility, family planning, and child and maternal health. A total of 9,045 households and 6,775 ever-married women aged 15 to 49 were interviewed. Thai Demographic and Health Survey (TDHS) is carried out by the Institute of Population Studies (IPS) of Chulalongkorn University with the financial support from USAID through the Institute for Resource Development (IRD) at Westinghouse. The Institute of Population Studies was responsible for the overall implementation of the survey including sample design, preparation of field work, data collection and processing, and analysis of data. IPS has made available its personnel and office facilities to the project throughout the project duration. It serves as the headquarters for the survey.

The Thai Demographic and Health Survey (TDHS) was undertaken for the main purpose of providing data concerning fertility, family planning and maternal and child health to program managers and policy makers to facilitate their evaluation and planning of programs, and to population and health researchers to assist in their efforts to document and analyze the demographic and health situation. It is intended to provide information both on topics for which comparable data is not available from previous nationally representative surveys as well as to update trends with respect to a number of indicators available from previous surveys, in particular the Longitudinal Study of Social Economic and Demographic Change in 1969-73, the Survey of Fertility in Thailand in 1975, the National Survey of Family Planning Practices, Fertility and Mortality in 1979, and the three Contraceptive Prevalence Surveys in 1978/79, 1981 and 1984.

Geographic coverage

National

Analysis unit

• Household
• Women age 15-49

Universe

The population covered by the 1987 THADHS is defined as the universe of all women Ever-married women in the reproductive ages (i.e., women 15-49). This covered women in private households on the basis of a de facto coverage definition. Visitors and usual residents who were in the household the night before the first visit or before any subsequent visit during the few days the interviewing team was in the area were eligible. Excluded were the small number of married women aged under 15 and women not present in private households.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE AND ALLOCATION

The objective of the survey was to provide reliable estimates for major domains of the country. This consisted of two overlapping sets of reporting domains: (a) Five regions of the country namely Bangkok, north, northeast, central region (excluding Bangkok), and south; (b) Bangkok versus all provincial urban and all rural areas of the country. These requirements could be met by defining six non-overlapping sampling domains (Bangkok, provincial urban, and rural areas of each of the remaining 4 regions), and allocating approximately equal sample sizes to them. On the basis of past experience, available budget and overall reporting requirement, the target sample size was fixed at 7,000 interviews of ever-married women aged 15-49, expected to be found in around 9,000 households. Table A.I shows the actual number of households as well as eligible women selected and interviewed, by sampling domain (see Table i.I for reporting domains).

THE FRAME AND SAMPLE SELECTION

The frame for selecting the sample for urban areas, was provided by the National Statistical Office of Thailand and by the Ministry of the Interior for rural areas. It consisted of information on population size of various levels of administrative and census units, down to blocks in urban areas and villages in rural areas. The frame also included adequate maps and descriptions to identify these units. The extent to which the data were up-to-date as well as the quality of the data varied somewhat in different parts of the frame. Basically, the multi-stage stratified sampling design involved the following procedure. A specified number of sample areas were selected systematically from geographically/administratively ordered lists with probabilities proportional to the best available measure of size (PPS). Within selected areas (blocks or villages) new lists of households were prepared and systematic samples of households were selected. In principle, the sampling interval for the selection of households from lists was determined so as to yield a self weighting sample of households within each domain. However, in the absence of good measures of population size for all areas, these sampling intervals often required adjustments in the interest of controlling the size of the resulting sample. Variations in selection probabilities introduced due to such adjustment, where required, were compensated for by appropriate weighting of sample cases at the tabulation stage.

SAMPLE OUTCOME

The final sample of households was selected from lists prepared in the sample areas. The time interval between household listing and enumeration was generally very short, except to some extent in Bangkok where the listing itself took more time. In principle, the units of listing were the same as the ultimate units of sampling, namely households. However in a small proportion of cases, the former differed from the latter in several respects, identified at the stage of final enumeration: a) Some units listed actually contained more than one household each b) Some units were "blanks", that is, were demolished or not found to contain any eligible households at the time of enumeration. c) Some units were doubtful cases in as much as the household was reported as "not found" by the interviewer, but may in fact have existed.

Mode of data collection

Face-to-face

Research instrument

The DHS core questionnaires (Household, Eligible Women Respondent, and Community) were translated into Thai. A number of modifications were made largely to adapt them for use with an ever- married woman sample and to add a number of questions in areas that are of special interest to the Thai investigators but which were not covered in the standard core. Examples of such modifications included adding marital status and educational attainment to the household schedule, elaboration on questions in the individual questionnaire on educational attainment to take account of changes in the educational system during recent years, elaboration on questions on postnuptial residence, and adaptation of the questionnaire to take into account that only ever-married women are being interviewed rather than all women. More generally, attention was given to the wording of questions in Thai to ensure that the intent of the original English-language version was preserved.

a) Household questionnaire

The household questionnaire was used to list every member of the household who usually lives in the household and as well as visitors who slept in the household the night before the interviewer's visit. Information contained in the household questionnaire are age, sex, marital status, and education for each member (the last two items were asked only to members aged 13 and over). The head of the household or the spouse of the head of the household was the preferred respondent for the household questionnaire. However, if neither was available for interview, any adult member of the household was accepted as the respondent. Information from the household questionnaire was used to identify eligible women for the individual interview. To be eligible, a respondent had to be an ever-married woman aged 15-49 years old who had slept in the household 'the previous night'.

Prior evidence has indicated that when asked about current age, Thais are as likely to report age at next birthday as age at last birthday (the usual demographic definition of age). Since the birth date of each household number was not asked in the household questionnaire, it was not possible to calculate age at last birthday from the birthdate. Therefore a special procedure was followed to ensure that eligible women just under the higher boundary for eligible ages (i.e. 49 years old) were not mistakenly excluded from the eligible woman sample because of an overstated age. Ever-married women whose reported age was between 50-52 years old and who slept in the household the night before birthdate of the woman, it was discovered that these women (or any others being interviewed) were not actually within the eligible age range of 15-49, the interview was terminated and the case disqualified. This attempt recovered 69 eligible women who otherwise would have been missed because their reported age was over 50 years old or over.

b) Individual questionnaire

The questionnaire administered to eligible women was based on the DHS Model A Questionnaire for high contraceptive prevalence countries. The individual questionnaire has 8 sections: - Respondent's background - Reproduction - Contraception - Health and breastfeeding - Marriage - Fertility preference - Husband's background and woman's work - Heights and weights of children and mothers

The questionnaire was modified to suit the Thai context. As noted above, several questions were added to the standard DHS core questionnaire not only to meet the interest of IPS researchers hut also because of their relevance to the current demographic situation in Thailand. The supplemental questions are marked with an asterisk in the individual questionnaire. Questions concerning the following items were added in the individual questionnaire: - Did the respondent ever

Demographic information for the student population of Introductory Psychology at Indiana University Bloomington.

Biological invasions are recognized as a major threat to both natural and managed ecosystems. Phylogeographic and population genetic analyses can provide information about the geographical origins and patterns of introduction and explain the causes and mechanisms by which introduced species have become successful invaders. Reticulitermes flavipes is a North American subterranean termite that has been introduced into several areas, including France where introduced populations have become invasive. To identify likely source populations in the USA and to compare the genetic diversity of both native and introduced populations, an extensive molecular genetic study was undertaken using the COII region of mtDNA and 15 microsatellite loci. Our results showed that native northern US populations appeared well differentiated from those of the southern part of the US range. Phylogenetic analysis of both mitochondrial and nuclear markers showed that French populations probably originated from southeastern US populations, and more specifically from Louisiana. All of the mtDNA haplotypes shared between the United States and France were found in Louisiana. Compared to native populations in Louisiana, French populations show lower genetic diversity at both mtDNA and microsatellite markers. These findings are discussed along with the invasion routes of R. flavipes as well as the possible mechanisms by which French populations have evolved after their introduction.

Observed and expected heterozygosity values for each of the sampling sites. (XLSX)

Biological invasion is a global problem with large negative impacts on ecosystems and human societies. When a species is introduced, individuals will first have to pass through the invasion stages of uptake and transport, before actual introduction in a non-native range. Selection is predicted to act during these earliest stages of biological invasion, potentially influencing the invasiveness and/or impact of introduced populations. Despite this potential impact of pre-introduction selection, empirical tests are virtually lacking. To test the hypothesis of pre-introduction selection, we followed the fate of individuals during capture, initial acclimation, and captivity in two bird species with several invasive populations originating from the international trade in wild-caught pets (the weavers Ploceus melanocephalus and Euplectes afer). We confirm that pre-introduction selection acts on a wide range of physiological, morphological, behavioral and demographic traits (incl. sex, age, size of body/brain/bill, bill shape, body mass, corticosterone levels, and escape behavior); these are all traits which likely affect invasion success. Our study thus comprehensively demonstrates the existence of hitherto ignored selection acting before the actual introduction into non-native ranges. This could ultimately change the composition and functioning of introduced populations, and therefore warrants greater attention. More knowledge on pre-introduction selection also might provide novel targets for the management of invasive species, if pre-introduction filters can be adjusted to change the quality and/or quantity of individuals passing through such that invasion probability and/or impacts are reduced.

aAkaike weight [41] for second best model was

Much of our understanding of natural invasions is retrospective, based on data acquired after invaders become established. As a consequence, we know little about the characteristics of the early population growth and habitat use of the invaders during establishment. Here we report on experimental introductions of guppies into natural streams in which we conducted monthly censuses of each population. Two of the four introductions were in streams with thinned canopies, which mimics a common form of habitat disturbance. We conducted similar censuses of natural populations to characterize natural population densities and generate a null distribution against which we could test a priori hypotheses about the establishment of the experimental invaders. We constructed a pedigree for one population, which enabled us to quantify lifetime reproductive success. Population simulations predict that the nature of the introduced population’s life history, in combination with reduced risk of predation in the introduction sites, will result in explosive population growth; however, populations of introduced invaders instead grew to match densities observed in natural streams with intact canopies. Experimental populations in streams with thinned canopies grew to densities that often exceeded those of natural streams with intact canopies. High population densities were associated with the increased use of marginal habitat. Adult females and males that moved into marginal habitat suffered no apparent fitness loss, suggesting lower population densities found there compensated for lower habitat quality. Our results suggest that the ecological setting in which invasions occur plays a role at least comparable in importance to that of the invader’s inherent characteristics in shaping early population growth and habitat use.

About this dataset

Context

The dataset tabulates the Burdett population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Burdett across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Burdett was 338, a 1.46% decrease year-by-year from 2021. Previously, in 2021, Burdett population was 343, a decline of 0.87% compared to a population of 346 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Burdett decreased by 18. In this period, the peak population was 356 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Burdett is shown in this column.
• Year on Year Change: This column displays the change in Burdett population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Burdett Population by Year. You can refer the same here