100+ datasets found
  1. Taxonomic and Geographic Bias in Conservation Biology Research: A Systematic...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    tiff
    Updated Jun 1, 2023
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    Beth E. I. Roberts; W. Edwin Harris; Geoff M. Hilton; Stuart J. Marsden (2023). Taxonomic and Geographic Bias in Conservation Biology Research: A Systematic Review of Wildfowl Demography Studies [Dataset]. http://doi.org/10.1371/journal.pone.0153908
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    tiffAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Beth E. I. Roberts; W. Edwin Harris; Geoff M. Hilton; Stuart J. Marsden
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Demographic data are important to wildlife managers to gauge population health, to allow populations to be utilised sustainably, and to inform conservation efforts. We analysed published demographic data on the world’s wildfowl to examine taxonomic and geographic biases in study, and to identify gaps in knowledge. Wildfowl (order: Anseriformes) are a comparatively well studied bird group which includes 169 species of duck, goose and swan. In all, 1,586 wildfowl research papers published between 1911 and 2010 were found using Web of Knowledge (WoK) and Google Scholar. Over half of the research output involved just 15 species from seven genera. Research output was strongly biased towards ‘high income’ countries, common wildfowl species, and measures of productivity, rather than survival and movement patterns. There were significantly fewer demographic data for the world’s 31 threatened wildfowl species than for non-threatened species. Since 1994, the volume of demographic work on threatened species has increased more than for non-threatened species, but still makes up only 2.7% of total research output. As an aid to research prioritisation, a metric was created to reflect demographic knowledge gaps for each species related to research output for the species, its threat status, and availability of potentially useful surrogate data from congeneric species. According to the metric, the 25 highest priority species include thirteen threatened taxa and nine species each from Asia and South America, and six from Africa.

  2. f

    Demographic data of the study population.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Feb 20, 2013
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    Braun, Armin; Switalla, Simone; Sewald, Katherina; Hohlfeld, Jens M.; Seehase, Sophie; Pfennig, Olaf; Neuhaus, Vanessa; Schlumbohm, Christina; Knauf, Sascha; Bleyer, Martina; Lauenstein, Hans-Dieter; Fuchs, Eberhard; Förster, Christine; Fieguth, Hans-Gerd; Kaup, Franz-Josef (2013). Demographic data of the study population. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001718501
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    Dataset updated
    Feb 20, 2013
    Authors
    Braun, Armin; Switalla, Simone; Sewald, Katherina; Hohlfeld, Jens M.; Seehase, Sophie; Pfennig, Olaf; Neuhaus, Vanessa; Schlumbohm, Christina; Knauf, Sascha; Bleyer, Martina; Lauenstein, Hans-Dieter; Fuchs, Eberhard; Förster, Christine; Fieguth, Hans-Gerd; Kaup, Franz-Josef
    Description

    Animals were randomized in each of the two independent study cycles as indicated (a: first study cycle, b: second study cycle). Before each cycle a baseline BAL was performed 3 weeks before LPS challenge and served as control. Altogether, 3 animals had to be excluded.Data are given as mean ± S.E.M., dxm = dexamethasone, rof = roflumilast.

  3. Population and Demography Dataset

    • kaggle.com
    zip
    Updated Aug 5, 2024
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    Benito Itele Wuver (2024). Population and Demography Dataset [Dataset]. https://www.kaggle.com/datasets/benitoitelewuver/population-and-demography-dataset
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    zip(139294 bytes)Available download formats
    Dataset updated
    Aug 5, 2024
    Authors
    Benito Itele Wuver
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    The dataset contains 18,944 entries with columns for Entity (country/region), Code (ISO code), Year, and Population estimates. Each row represents the population estimate for a specific country and year, spanning from 1950 to recent years, capturing global demographic changes over time.

  4. g

    Data from: Longitudinal Analysis of Historical Demographic Data

    • search.gesis.org
    • openicpsr.org
    • +1more
    Updated May 1, 2021
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    GESIS search (2021). Longitudinal Analysis of Historical Demographic Data [Dataset]. http://doi.org/10.3886/E34554V1
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    Dataset updated
    May 1, 2021
    Dataset provided by
    ICPSR - Interuniversity Consortium for Political and Social Research
    GESIS search
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de452467https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de452467

    Description

    Abstract (en): This study contains teaching materials developed over a period of years for a four-week workshop, Longitudinal Analysis of Historical Demographic Data (LAHDD), offered through the ICPSR Summer Program in 2006, 2007, 2009, 2011 and 2013, with one-day alumni workshops in 2010, 2012, and 2014. Instructors in the workshops are listed below. Funding was provided by The Eunice Kennedy Shriver National Institute of Child Health and Human Development, grants R25-HD040525 and R25-HD-049479, the ICPSR Summer Program and the ICPSR Director. The course was designed to teach students the theories, methods, and practices of historical demography and to give them first-hand experience working with historical data. This training is valuable not only to those interested in the analysis historical data. The techniques of historical demography rest on methodological insights that can be applied to many problems in population studies and other social sciences. While historical demography remains a flourishing research area with publications in key journals like Demography, Population Studies, and Population, practitioners were dispersed, and training was not available at any of the population research centers in the U.S. or elsewhere. One hundred and ten participants from around the globe took part in the workshops, and have gone on to establish courses of their own or teach in other workshops. We offer these materials here in the hopes that others will find them useful in developing courses on historical demography and/or longitudinal data analysis. The workshop was organized in three tracks: A brief tour of historical demography, event-history analysis, and data management for longitudinal data using Stata and Microsoft Access. The data management track includes 13 exercises designed for hands-on learning and reinforcement. Included in this project are the syllabii and reading lists for the three tracks, datasets used in the exercises, documents setting out each exercise, a file with the expected results, and for many of the exercises, an explanation. Video tutorials helpful with the Access exercises are accessible from ICPSR's YouTube channel https://www.youtube.com/playlist?list=PLqC9lrhW1Vvb9M1QpQH23z9UlPYxHbUMF. Users are encouraged to use these materials to develop their own courses and workshops in any of the topics covered. Please acknowledge NICHD R25-HD040525 and R25-HD-049479 whenever appropriate. Historical demography instructors: Myron P. Gutmann, University of Colorado Boulder Cameron Campbell, Hong Kong University of Science and Technology J. David Hacker, University of Minnesota Satomi Kurosu, Reitaku University Katherine A. Lynch, Carnegie Mellon University Event history instructors: Cameron Campbell, Hong Kong University of Science and Technology Glenn Deane, State University of New York at Albany Ken R. Smith, Huntsman Cancer Institute and University of Utah Database management instructors: George Alter, University of Michigan Susan Hautaniemi Leonard, University of Michigan Teaching Assistants: Mathew Creighton, University of Massachusetts Boston Emily Merchant, University of Michigan Luciana Quaranta, Lund University Kristine Witkowski, University of Michigan Project Manager: Susan Hautaniemi Leonard, University of Michigan Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. Eunice Kennedy Shriver National Institute of Child Health and Human Development (R25 HD040525).

  5. Global Population Data (1960-2023)

    • kaggle.com
    zip
    Updated Feb 3, 2025
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    Taimoor Khurshid Chughtai (2025). Global Population Data (1960-2023) [Dataset]. https://www.kaggle.com/datasets/taimoor888/global-population-data-1960-2023
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    zip(88213 bytes)Available download formats
    Dataset updated
    Feb 3, 2025
    Authors
    Taimoor Khurshid Chughtai
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    This dataset is sourced from the World Bank’s World Development Indicators and provides annual total population data for various countries from 1960 to 2023. It is useful for demographic analysis, population trend forecasting, and economic research.

    Key Features: Country-wise total population figures from 1960 to 2023. Country codes and indicator details included for easy reference. Can be used for data visualization, trend analysis, and machine learning models related to population studies. This dataset is valuable for researchers, data scientists, and analysts studying global population growth, migration trends, and economic impacts.

  6. m

    Data from: Age dataset: A structured general-purpose dataset on life, work,...

    • data.mendeley.com
    Updated Apr 27, 2022
    + more versions
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    Issa Annamoradnejad (2022). Age dataset: A structured general-purpose dataset on life, work, and death of 1.22 million distinguished people [Dataset]. http://doi.org/10.17632/2sfz4tt88g.1
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    Dataset updated
    Apr 27, 2022
    Authors
    Issa Annamoradnejad
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    We developed a five-step method and inferred birth and death years, binary gender, and occupation from community-submitted data to all language versions of the Wikipedia project. The dataset is the largest on notable deceased people and includes individuals from a variety of social groups, including but not limited to 107k females, 124 non-binary people, and 90k researchers, who are spread across more than 300 contemporary or historical regions.

    Related paper accepted to the ICWSM Workshop on Data for the Wellbeing of Most Vulnerable.

  7. i

    Demographic and Health Survey 1987 - Thailand

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Mar 29, 2019
    + more versions
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    Institute of Population Studies (IPS) (2019). Demographic and Health Survey 1987 - Thailand [Dataset]. https://catalog.ihsn.org/catalog/2489
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    Dataset updated
    Mar 29, 2019
    Dataset authored and provided by
    Institute of Population Studies (IPS)
    Time period covered
    1987
    Area covered
    Thailand
    Description

    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

  8. f

    Demographics of the study population.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Nov 17, 2014
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    Shimizu, Kimiya; Kobashi, Hidenaga; Kamiya, Kazutaka; Iijima, Ayaka (2014). Demographics of the study population. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001235892
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    Dataset updated
    Nov 17, 2014
    Authors
    Shimizu, Kimiya; Kobashi, Hidenaga; Kamiya, Kazutaka; Iijima, Ayaka
    Description

    D = diopter, logMAR = logMAR = logarithm of the minimal angle of resolution, CDVA = corrected distance visual acuity, HOAs = higher-order aberrations, OSI = objective scattering index.Demographics of the study population.

  9. Prakriti-wise distribution and demography of the study samples.

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Ramesh C. Juyal; Sapna Negi; Preeti Wakhode; Sulekha Bhat; Bheema Bhat; B. K. Thelma (2023). Prakriti-wise distribution and demography of the study samples. [Dataset]. http://doi.org/10.1371/journal.pone.0045752.t001
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ramesh C. Juyal; Sapna Negi; Preeti Wakhode; Sulekha Bhat; Bheema Bhat; B. K. Thelma
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Prakriti-wise distribution and demography of the study samples.

  10. World-Population

    • kaggle.com
    zip
    Updated Jul 18, 2023
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    Allanatrix (2023). World-Population [Dataset]. https://www.kaggle.com/datasets/allanwandia/world-population
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    zip(14887 bytes)Available download formats
    Dataset updated
    Jul 18, 2023
    Authors
    Allanatrix
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    World
    Description

    Demographic analysis examines and measures the dimensions and dynamics of populations; it can cover whole societies or groups defined by criteria such as education, nationality, religion, and ethnicity. Educational institutions usually treat demography as a field of sociology, though there are a number of independent demography departments. These methods have primarily been developed to study human populations, but are extended to a variety of areas where researchers want to know how populations of social actors can change across time through processes of birth, death, and migration. In the context of human biological populations, demographic analysis uses administrative records to develop an independent estimate of the population

  11. u

    A Synthetic Longitudinal Study Dataset for Scotland

    • rdr.ucl.ac.uk
    xlsx
    Updated Mar 21, 2024
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    Adam Dennett; Nicola Shelton (2024). A Synthetic Longitudinal Study Dataset for Scotland [Dataset]. http://doi.org/10.5522/04/25408120.v1
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    xlsxAvailable download formats
    Dataset updated
    Mar 21, 2024
    Dataset provided by
    University College London
    Authors
    Adam Dennett; Nicola Shelton
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Scotland
    Description

    The data are based on the 2011 Census Microdata Teaching File, with the first 18 variables exactly the same as those found in the original file, which can be downloaded from: http://www.scotlandscensus.gov.uk/microdataThe final 10 variables found in the file, highlighted in yellow, are synthetic data. Those variables corresponding to a 2001 state are based on the transitional probabilities taken from the ONS longitudinal study, accurate to 10 year age groups.Details of the synthetic variables can be found in the Synthetic Variables sheet in this file. Details of the original variables can be found in the meta data accompanying the original microdata teaching file.

  12. i

    Population aged 15 and over by year of arrival in Spain, sex, age group,...

    • ine.es
    csv, html, json +4
    Updated Apr 15, 2025
    + more versions
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    INE - Instituto Nacional de Estadística (2025). Population aged 15 and over by year of arrival in Spain, sex, age group, country of birth (Spain/foreign) and level of studies (aggregate) [Dataset]. https://www.ine.es/jaxiT3/Tabla.htm?t=70345&L=1
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    csv, html, txt, xls, json, xlsx, text/pc-axisAvailable download formats
    Dataset updated
    Apr 15, 2025
    Dataset authored and provided by
    INE - Instituto Nacional de Estadística
    License

    https://www.ine.es/aviso_legalhttps://www.ine.es/aviso_legal

    Time period covered
    Jan 1, 2021 - Jan 1, 2023
    Area covered
    Spain
    Variables measured
    Age, Sex, Type of data, Country of birth, Level of studies, Territorial Scope, Demographic concept, Year of arrival in Spain
    Description

    Censo de Población: Population aged 15 and over by year of arrival in Spain, sex, age group, country of birth (Spain/foreign) and level of studies (aggregate). Annual. National.

  13. i

    Demographic and Health Survey 1993 - Turkey

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Mar 29, 2019
    + more versions
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    Institute of Population Studies (2019). Demographic and Health Survey 1993 - Turkey [Dataset]. https://catalog.ihsn.org/index.php/catalog/2501/study-description
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    Dataset updated
    Mar 29, 2019
    Dataset provided by
    Institute of Population Studies
    General Directorate of Mother and Child Health and Family Planning
    Time period covered
    1993
    Area covered
    Turkey
    Description

    Abstract

    The 1993 Turkish Demographic and Health Survey (TDHS) is a nationally representative survey of ever-married women less than 50 years old. The survey was designed to provide information on fertility levels and trends, infant and child mortality, family planning, and maternal and child health. The TDHS was conducted by the Hacettepe University Institute of Population Studies under a subcontract through an agreement between the General Directorate of Mother and Child Health and Family Planning, Ministry of Health and Macro International Inc. of Calverton, Maryland. Fieldwork was conducted from August to October 1993. Interviews were carried out in 8,619 households and with 6,519 women.

    The Turkish Demographic and Health Survey (TDHS) is a national sample survey of ever-married women of reproductive ages, designed to collect data on fertility, marriage patterns, family planning, early age mortality, socioeconomic characteristics, breastfeeding, immunisation of children, treatment of children during episodes of illness, and nutritional status of women and children. The TDHS, as part of the international DHS project, is also the latest survey in a series of national-level population and health surveys in Turkey, which have been conducted by the Institute of Population Studies, Haeettepe University (HIPS).

    More specifically, the objectives of the TDHS are to:

    Collect data at the national level that will allow the calculation of demographic rates, particularly fertility and childhood mortality rates; Analyse the direct and indirect factors that determine levels and trends in fertility and childhood mortality; Measure the level of contraceptive knowledge and practice by method, region, and urban- rural residence; Collect data on mother and child health, including immunisations, prevalence and treatment of diarrhoea, acute respiratory infections among children under five, antenatal care, assistance at delivery, and breastfeeding; Measure the nutritional status of children under five and of their mothers using anthropometric measurements.

    The TDHS information is intended to assist policy makers and administrators in evaluating existing programs and in designing new strategies for improving family planning and health services in Turkey.

    MAIN RESULTS

    Fertility in Turkey is continuing to decline. If Turkish women maintain current fertility rates during their reproductive years, they can expect to have all average of 2.7 children by the end of their reproductive years. The highest fertility rate is observed for the age group 20-24. There are marked regional differences in fertility rates, ranging from 4.4 children per woman in the East to 2.0 children per woman in the West. Fertility also varies widely by urban-rural residence and by education level. A woman living in rural areas will have almost one child more than a woman living in an urban area. Women who have no education have almost one child more than women who have a primary-level education and 2.5 children more than women with secondary-level education.

    The first requirement of success ill family planning is the knowledge of family planning methods. Knowledge of any method is almost universal among Turkish women and almost all those who know a method also know the source of the method. Eighty percent of currently married women have used a method sometime in their life. One third of currently married women report ever using the IUD. Overall, 63 percent of currently married women are currently using a method. The majority of these women are modern method users (35 percent), but a very substantial proportion use traditional methods (28 percent). the IUD is the most commonly used modern method (I 9 percent), allowed by the condom (7 percent) and the pill (5 percent). Regional differences are substantial. The level of current use is 42 percent in tile East, 72 percent in tile West and more than 60 percent in tile other three regions. "File common complaints about tile methods are side effects and health concerns; these are especially prevalent for the pill and IUD.

    One of the major child health indicators is immunisation coverage. Among children age 12-23 months, the coverage rates for BCG and the first two doses of DPT and polio were about 90 percent, with most of the children receiving those vaccines before age one. The results indicate that 65 percent of the children had received all vaccinations at some time before the survey. On a regional basis, coverage is significantly lower in the Eastern region (41 percent), followed by the Northern and Central regions (61 percent and 65 percent, respectively). Acute respiratory infections (ARI) and diarrhea are the two most prevalent diseases of children under age five in Turkey. In the two weeks preceding the survey, the prevalence of ARI was 12 percent and the prevalence of diarrhea was 25 percent for children under age five. Among children with diarrhea 56 percent were given more fluids than usual.

    Breastfeeding in Turkey is widespread. Almost all Turkish children (95 percent) are breastfed for some period of time. The median duration of breastfeeding is 12 months, but supplementary foods and liquids are introduced at an early age. One-third of children are being given supplementary food as early as one month of age and by the age of 2-3 months, half of the children are already being given supplementary foods or liquids.

    By age five, almost one-filth of children arc stunted (short for their age), compared to an international reference population. Stunting is more prevalent in rural areas, in the East, among children of mothers with little or no education, among children who are of higher birth order, and among those born less than 24 months after a prior birth. Overall, wasting is not a problem. Two percent of children are wasted (thin for their height), and I I percent of children under five are underweight for their age. The survey results show that obesity is d problem among mothers. According to Body Mass Index (BMI) calculations, 51 percent of mothers are overweight, of which 19 percent are obese.

    Geographic coverage

    The Turkish Demographic and Health Survey (TDHS) is a national sample survey.

    Analysis unit

    • Household
    • Women age 12-49
    • Children under five

    Universe

    The population covered by the 1993 DHS is defined as the universe of all ever-married women age 12-49 who were present in the household on the night before the interview were eligible for the survey.

    Kind of data

    Sample survey data

    Sampling procedure

    The sample for the TDHS was designed to provide estimates of population and health indicators, including fertility and mortality rates for the nation as a whole, fOr urban and rural areas, and for the five major regions of the country. A weighted, multistage, stratified cluster sampling approach was used in the selection of the TDHS sample.

    Sample selection was undertaken in three stages. The sampling units at the first stage were settlements that differed in population size. The frame for the selection of the primary sampling units (PSUs) was prepared using the results of the 1990 Population Census. The urban frame included provinces and district centres and settlements with populations of more than 10,000; the rural frame included subdistricts and villages with populations of less than 10,000. Adjustments were made to consider the growth in some areas right up to survey time. In addition to the rural-urban and regional stratifications, settlements were classified in seven groups according to population size.

    The second stage of selection involved the list of quarters (administrative divisions of varying size) for each urban settlement, provided by the State Institute of Statistics (SIS). Every selected quarter was subdivided according tothe number of divisions(approximately 100 households)assigned to it. In rural areas, a selected village was taken as a single quarter, and wherever necessary, it was divided into subdivisions of approximately 100 households. In cases where the number of households in a selected village was less than 100 households, the nearest village was selected to complete the 100 households during the listing activity, which is described below.

    After the selection of the secondary sampling units (SSUs), a household listing was obtained for each by the TDHS listing teams. The listing activity was carried out in May and June. From the household lists, a systematic random sample of households was chosen for the TDHS. All ever-married women age 12-49 who were present in the household on the night before the interview were eligible for the survey.

    Mode of data collection

    Face-to-face

    Research instrument

    Two questionnaires were used in the main fieldwork for the TDHS: the Household Questionnaire and the Individual Questionnaire for ever-married women of reproductive age. The questionnaires were based on the model survey instruments developed in the DHS program and on the questionnaires that had been employed in previous Turkish population and health surveys. The questionnaires were adapted to obtain data needed for program planning in Turkey during consultations with population and health agencies. Both questionnaires were developed in English and translated into Turkish.

    a) The Household Questionnaire was used to enumerate all usual members of and visitors to the selected households and to collect information relating to the socioeconomic position of the households. In the first part of the Household Questionnaire, basic information was collected on the age, sex, educational attainment, marital status and relationship to the head of household for each person listed as a household member

  14. Number of countries or areas and percentage of population covered in the...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Cheryl Chriss Sawyer (2023). Number of countries or areas and percentage of population covered in the study. [Dataset]. http://doi.org/10.1371/journal.pmed.1001287.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Cheryl Chriss Sawyer
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Number of countries or areas and percentage of population covered in the study.

  15. Global Demographic Dynamics: Population Trends

    • kaggle.com
    zip
    Updated May 20, 2024
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    hrterhrter (2024). Global Demographic Dynamics: Population Trends [Dataset]. https://www.kaggle.com/datasets/programmerrdai/global-demographic-dynamics-population-trends
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    zip(16980583 bytes)Available download formats
    Dataset updated
    May 20, 2024
    Authors
    hrterhrter
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    This dataset provides an in-depth look at global demographic trends spanning a century, offering detailed insights into population growth, age-gender structure, and dependency changes over time. It is designed to support a wide range of analytical applications, from academic research in demographics to policy-making and socio-economic planning.

  16. f

    Demographic distribution of the target population and the study sample.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    • +1more
    Updated Feb 20, 2012
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    Kungu, Stella; Musyimi, Robert; Tigoi, Caroline C.; Scott, J. Anthony G.; Abdullahi, Osman; Mugo, Daisy; Karani, Angela; Jomo, Jane; Wanjiru, Eva; Lipsitch, Marc (2012). Demographic distribution of the target population and the study sample. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001156064
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    Dataset updated
    Feb 20, 2012
    Authors
    Kungu, Stella; Musyimi, Robert; Tigoi, Caroline C.; Scott, J. Anthony G.; Abdullahi, Osman; Mugo, Daisy; Karani, Angela; Jomo, Jane; Wanjiru, Eva; Lipsitch, Marc
    Description

    Demographic distribution of the target population and the study sample.

  17. d

    Data from: Several candidate size metrics explain vital rates across...

    • search.dataone.org
    • datadryad.org
    Updated Aug 20, 2025
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    Maude E. A. Baudraz; Dylan Z. Childs; Ruth Kelly; Annabel L. Smith; Jesus Villellas; Martin Andrzejak; Benedicte Bachelot; Lajos Benedek; Simone P. Blomberg; Judit Bodis; Francis Q. Brearley; Anna Bucharova; Christina M. Caruso; Jane A. Catford; Matthew Coghill; Aldo Compagnoni; Anna Mária P. CsergÅ‘; Richard P. Duncan; John Dwyer; Johan Ehrlén; Bret Elderd; Alain Finn; Lauchlan Fraser; Maria B. GarcÃa; Jennifer R. Gremer; Ronny Groenteman; Liv Norunn Hamre; Aveliina Helm; Mária Höhn; Lotte Korell; Lauri Laanisto; Anna-Liisa Laine; Michele Lonati; Caroline M. McKeon; Aoife Molloy; Joslin L. Moore; Melanie Morales; Sergi Munne Bosch; Zuzana Münzbergová; Siri Lie Olsen; Adrian Oprea; Meelis Pärtel; Rachel M. Penczykowski; William K. Petry; Satu Ramula; Pil U. Rasmussen; Simone Ravetto Enri; Deborah A. Roach; Anna Roeder; Christiane Roscher; Marjo Saastamoinen; Cheryl Schultz; R. Drew Sieg; Olav Skarpaas; Ayco J. M. Tack; Joachim Töpper; Peter A. Vesk; Gregory Vose; Elizabeth M. Wandrag; Glenda M. Wardle; Astrid Wingler; Yvonne M. Buckley (2025). Several candidate size metrics explain vital rates across multiple populations throughout a widespread species' range [Dataset]. http://doi.org/10.5061/dryad.mw6m9067c
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    Dataset updated
    Aug 20, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Maude E. A. Baudraz; Dylan Z. Childs; Ruth Kelly; Annabel L. Smith; Jesus Villellas; Martin Andrzejak; Benedicte Bachelot; Lajos Benedek; Simone P. Blomberg; Judit Bodis; Francis Q. Brearley; Anna Bucharova; Christina M. Caruso; Jane A. Catford; Matthew Coghill; Aldo Compagnoni; Anna Mária P. Csergő; Richard P. Duncan; John Dwyer; Johan Ehrlén; Bret Elderd; Alain Finn; Lauchlan Fraser; Maria B. García; Jennifer R. Gremer; Ronny Groenteman; Liv Norunn Hamre; Aveliina Helm; Mária Höhn; Lotte Korell; Lauri Laanisto; Anna-Liisa Laine; Michele Lonati; Caroline M. McKeon; Aoife Molloy; Joslin L. Moore; Melanie Morales; Sergi Munne Bosch; Zuzana Münzbergová; Siri Lie Olsen; Adrian Oprea; Meelis Pärtel; Rachel M. Penczykowski; William K. Petry; Satu Ramula; Pil U. Rasmussen; Simone Ravetto Enri; Deborah A. Roach; Anna Roeder; Christiane Roscher; Marjo Saastamoinen; Cheryl Schultz; R. Drew Sieg; Olav Skarpaas; Ayco J. M. Tack; Joachim Töpper; Peter A. Vesk; Gregory Vose; Elizabeth M. Wandrag; Glenda M. Wardle; Astrid Wingler; Yvonne M. Buckley
    Description

    Individual plant size often determines the vital rates of growth, survival, and reproduction. However, size can be measured in several ways (e.g., height, biomass, leaf length). There is no consensus on the best size metric for modelling vital rates in plants. Demographic datasets are expanding in geographic extent, leading to choices about how to represent size for the same species in multiple ecological contexts. If the choice of size variable varies among locations, inter-population comparative demography increases in complexity. Here, we present a framework to perform size metric selection in large-scale demographic studies. We highlight potential pitfalls and suggest methods applicable to diverse study organisms. We assessed the performance of five different size metrics for the perennial herb Plantago lanceolata across 55 populations on three continents within its native and non-native ranges, using the spatially replicated demographic dataset PlantPopNet. We compared the performa..., PlantPopNet (www.plantpopnet.com) collaborators collect demographic information on 65 naturally occurring populations of P. lanceolata across three continents. The present study included 55 populations that had at least two consecutive yearly censuses, presented here. Each population consists of an initial 100 individuals marked in naturally occurring populations and re-visited yearly at the peak of the flowering season. New recruits within the original plots were recorded and followed in subsequent years. The number of rosettes, number of leaves per rosette, length of the longest leaf, and width of the longest leaf for each rosette, flowering status (flowered, not flowered), reproductive output, and survival or death of each individual were recorded at each annual census. For further information on the PlantPopNet protocol, see Buckley et al. (2019). This data is presented as it was used to perform a study on a subset of the plantpopnet data. For said study, we used the first transitio..., , # Several candidate size metrics explain vital rates across multiple populations throughout a widespread species' range

    https://doi.org/10.5061/dryad.mw6m9067c

    Description of the data and file structure

    Code and analysis are described in detail in the main text and supplementary materials of the associated Journal of Ecology paper. If you have any questions regarding the R code files you may contact Maude Baudraz at baudrazm@tcd.ie or maude.baudraz@gmail.com

    Data provided herein represent a derived version from the PlantPopNet dataset, a Spatially Distributed Model System for Population Ecology. They represent demographic information for all individuals in over 55 populations of the perennial plant Plantago lanceolata spread throughout three continents. The data published contains size, growth, reproduction, and survival information. More information about the PlantPopNet netw...,

  18. d

    Data from: Demography and habitat of desert tortoises at the Desert Tortoise...

    • catalog.data.gov
    • data.usgs.gov
    • +1more
    Updated Oct 22, 2025
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    U.S. Geological Survey (2025). Demography and habitat of desert tortoises at the Desert Tortoise Research Natural Area, western Mojave Desert, California (1978 - 2014) [Dataset]. https://catalog.data.gov/dataset/demography-and-habitat-of-desert-tortoises-at-the-desert-tortoise-research-natural-ar-1978
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    Dataset updated
    Oct 22, 2025
    Dataset provided by
    U.S. Geological Survey
    Area covered
    Mojave Desert, California
    Description

    A long-term research project was conducted on Agassiz’s desert tortoises (Gopherus agassizii) at a 7.77 square kilometer plot at the Desert Tortoise Research Natural Area, Western Mojave Desert, California, USA. The plot included tortoise populations and habitat both inside and outside the protective fence at the Research Natural Area. Databases used in the research and publications from the research project are assembled here and include: census (survey) database used for the demographic analysis and Bayesian modeling of the desert tortoise population; shell-skeletal remains of desert tortoises; clinical signs of health, disease, and trauma in desert tortoises; perennial (shrubs, perennial grasses) and annual plant data from transects within the study area; potential avian predators of desert tortoises at the study area; evidence of mammalian carnivores at the study area; and evidence of anthropogenic impacts to desert tortoise and their habitats inside and outside the fenced Natural Area. These data support the following publications: 1) Berry, K.H., and Yee, J.L., 2021, Development of demographic models to analyze populations with multi-year data-Using Agassiz’s Desert Tortoise (Gopherus agassizii) as a case study: U.S. Geological Survey Open-File Report 2018-1094, 55 p., https://doi.org/10.3133/ofr20181094. 2) Berry, K.H., Yee, J.L., Shields, T.A., and Stockton, L. 2020. The catastrophic decline of tortoises at a fenced Natural Area. Wildlife Monographs 205:1-53. DOI:10.1002/wmon.1052

  19. d

    National Longitudinal Mortality Study

    • dknet.org
    • rrid.site
    • +2more
    Updated Jul 2, 2011
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    (2011). National Longitudinal Mortality Study [Dataset]. http://identifiers.org/RRID:SCR_008946
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    Dataset updated
    Jul 2, 2011
    Description

    A database based on a random sample of the noninstitutionalized population of the United States, developed for the purpose of studying the effects of demographic and socio-economic characteristics on differentials in mortality rates. It consists of data from 26 U.S. Current Population Surveys (CPS) cohorts, annual Social and Economic Supplements, and the 1980 Census cohort, combined with death certificate information to identify mortality status and cause of death covering the time interval, 1979 to 1998. The Current Population Surveys are March Supplements selected from the time period from March 1973 to March 1998. The NLMS routinely links geographical and demographic information from Census Bureau surveys and censuses to the NLMS database, and other available sources upon request. The Census Bureau and CMS have approved the linkage protocol and data acquisition is currently underway. The plan for the NLMS is to link information on mortality to the NLMS every two years from 1998 through 2006 with research on the resulting database to continue, at least, through 2009. The NLMS will continue to incorporate data from the yearly Annual Social and Economic Supplement into the study as the data become available. Based on the expected size of the Annual Social and Economic Supplements to be conducted, the expected number of deaths to be added to the NLMS through the updating process will increase the mortality content of the study to nearly 500,000 cases out of a total number of approximately 3.3 million records. This effort would also include expanding the NLMS population base by incorporating new March Supplement Current Population Survey data into the study as they become available. Linkages to the SEER and CMS datasets are also available. Data Availability: Due to the confidential nature of the data used in the NLMS, the public use dataset consists of a reduced number of CPS cohorts with a fixed follow-up period of five years. NIA does not make the data available directly. Research access to the entire NLMS database can be obtained through the NIA program contact listed. Interested investigators should email the NIA contact and send in a one page prospectus of the proposed project. NIA will approve projects based on their relevance to NIA/BSR''s areas of emphasis. Approved projects are then assigned to NLMS statisticians at the Census Bureau who work directly with the researcher to interface with the database. A modified version of the public use data files is available also through the Census restricted Data Centers. However, since the database is quite complex, many investigators have found that the most efficient way to access it is through the Census programmers. * Dates of Study: 1973-2009 * Study Features: Longitudinal * Sample Size: ~3.3 Million Link: *ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00134

  20. Pittsburgh Youth Study Demographic Constructs, Pittsburgh, Pennsylvania,...

    • icpsr.umich.edu
    • catalog.data.gov
    Updated Sep 30, 2019
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    Loeber, Rolf; Stouthamer-Loeber, Magda; Farrington, David P.; Pardini, Dustin (2019). Pittsburgh Youth Study Demographic Constructs, Pittsburgh, Pennsylvania, 1987-2001 [Dataset]. http://doi.org/10.3886/ICPSR37350.v1
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    Dataset updated
    Sep 30, 2019
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    Authors
    Loeber, Rolf; Stouthamer-Loeber, Magda; Farrington, David P.; Pardini, Dustin
    License

    https://www.icpsr.umich.edu/web/ICPSR/studies/37350/termshttps://www.icpsr.umich.edu/web/ICPSR/studies/37350/terms

    Area covered
    Pennsylvania, Pittsburgh, United States
    Description

    The Pittsburgh Youth Study (PYS) is part of the larger "Program of Research on the Causes and Correlates of Delinquency" initiated by the Office of Juvenile Justice and Delinquency Prevention in 1986. PYS aims to document the development of antisocial and delinquent behavior from childhood to early adulthood, the risk factors that impinge on that development, and help seeking and service provision of boys' behavior problems. The study also focuses on boys' development of alcohol and drug use, and internalizing problems. PYS consists of three cohorts of boys who were in the first, fourth, and seventh grades in Pittsburgh, Pennsylvania public schools during the 1987-1988 academic year (called the youngest, middle, and oldest cohorts, respectively). Using a screening risk score that measured each boy's antisocial behavior, boys identified at the top 30 percent within each grade cohort on the screening risk measure (n=~250), as well as an equal number of boys randomly selected from the remainder (n=~250), were selected for follow-up. Consequently, the final sample for the study consisted of 1,517 total students selected for follow-up. 506 of these students were in the oldest sample, 508 were in the middle sample, and 503 were in the youngest sample. Assessments were conducted semiannually and then annually using multiple informants (i.e., boys, parents, and teachers) between 1987 and 2010. The youngest cohort was assessed from ages 6-19 and again at ages 25 and 28. The middle cohort was assessed from ages 9-13 and again at age 23. The oldest cohort was assessed from ages 13-25, with an additional assessment at age 35. Information has been collected on a broad range of risk and protective factors across multiple domains (e.g., individual, family, peer, school, and neighborhood). Measures of conduct problems, substance use/abuse, criminal behavior, mental health problems have been collected. This collection contains data and syntax files for demographic constructs. The datasets include constructs on repeated grade status, demographic information of participants, participants' biological mother, biological father, female caretaker, and male caretaker, change of caretaker since last phase, number of family members and other adults or children in the home, family structure, followup participation by youth, caretaker, and teacher, and housing characteristics. The demographic constructs were created by using the PYS raw data. The raw data are available at ICPSR in the following studies: Pittsburgh Youth Study Youngest Sample (1987 - 2001) [Pittsburgh, Pennsylvania], Pittsburgh Youth Study Middle Sample (1987 - 1991) [Pittsburgh, Pennsylvania], and Pittsburgh Youth Study Oldest Sample (1987 - 2000) [Pittsburgh, Pennsylvania].

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Beth E. I. Roberts; W. Edwin Harris; Geoff M. Hilton; Stuart J. Marsden (2023). Taxonomic and Geographic Bias in Conservation Biology Research: A Systematic Review of Wildfowl Demography Studies [Dataset]. http://doi.org/10.1371/journal.pone.0153908
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Taxonomic and Geographic Bias in Conservation Biology Research: A Systematic Review of Wildfowl Demography Studies

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28 scholarly articles cite this dataset (View in Google Scholar)
tiffAvailable download formats
Dataset updated
Jun 1, 2023
Dataset provided by
PLOShttp://plos.org/
Authors
Beth E. I. Roberts; W. Edwin Harris; Geoff M. Hilton; Stuart J. Marsden
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Demographic data are important to wildlife managers to gauge population health, to allow populations to be utilised sustainably, and to inform conservation efforts. We analysed published demographic data on the world’s wildfowl to examine taxonomic and geographic biases in study, and to identify gaps in knowledge. Wildfowl (order: Anseriformes) are a comparatively well studied bird group which includes 169 species of duck, goose and swan. In all, 1,586 wildfowl research papers published between 1911 and 2010 were found using Web of Knowledge (WoK) and Google Scholar. Over half of the research output involved just 15 species from seven genera. Research output was strongly biased towards ‘high income’ countries, common wildfowl species, and measures of productivity, rather than survival and movement patterns. There were significantly fewer demographic data for the world’s 31 threatened wildfowl species than for non-threatened species. Since 1994, the volume of demographic work on threatened species has increased more than for non-threatened species, but still makes up only 2.7% of total research output. As an aid to research prioritisation, a metric was created to reflect demographic knowledge gaps for each species related to research output for the species, its threat status, and availability of potentially useful surrogate data from congeneric species. According to the metric, the 25 highest priority species include thirteen threatened taxa and nine species each from Asia and South America, and six from Africa.

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