32 datasets found
  1. Global population density by region 2025

    • statista.com
    • ai-chatbox.pro
    Updated May 27, 2025
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    Statista (2025). Global population density by region 2025 [Dataset]. https://www.statista.com/statistics/912416/global-population-density-by-region/
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    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Worldwide
    Description

    As of 2025, Asia was the most densely populated region of the world, with nearly 156 inhabitants per square kilometer, whereas Oceania's population density was just over five inhabitants per square kilometer.

  2. k

    Continent of Africa: High Resolution Population Density Maps

    • lschub.kalro.org
    • kenya.lsc-hubs.org
    • +1more
    Updated Dec 13, 2024
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    (2024). Continent of Africa: High Resolution Population Density Maps [Dataset]. https://lschub.kalro.org/cat/collections/metadata:main/items/meta-population-density
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    Dataset updated
    Dec 13, 2024
    Area covered
    Africa
    Description

    These 28 tiff files represent 2015 population estimates. However, please note that many of the country-level files include 2020 population estimates including: Angola, Benin, Botswana, Burundi, Cameroon, Cabo Verde, Cote d'Ivoire, Djibouti, Eritrea, Eswatini, The Gambia, Ghana, Lesotho, Liberia, Mozambique, Namibia, Sao Tome & Principe, Sierra Leone, South Africa, Togo, Zambia, and Zimbabwe. South Sudan, Sudan, Somalia and Ethiopia are intentionally omitted from this dataset. However, a country-level dataset for Ethiopia can be found at https://data.humdata.org/dataset/ethiopia-high-resolution-population-density-maps-demographic-estimates.

  3. Distribution of the global population by continent 2024

    • statista.com
    • ai-chatbox.pro
    Updated Mar 27, 2025
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    Statista (2025). Distribution of the global population by continent 2024 [Dataset]. https://www.statista.com/statistics/237584/distribution-of-the-world-population-by-continent/
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    Dataset updated
    Mar 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    World
    Description

    In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

  4. Forecast: world population, by continent 2100

    • ai-chatbox.pro
    • statista.com
    Updated Apr 8, 2025
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    Statista Research Department (2025). Forecast: world population, by continent 2100 [Dataset]. https://www.ai-chatbox.pro/?_=%2Ftopics%2F13342%2Faging-populations%2F%23XgboD02vawLKoDs%2BT%2BQLIV8B6B4Q9itA
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    Dataset updated
    Apr 8, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Statista Research Department
    Area covered
    World
    Description

    Whereas the population is expected to decrease somewhat until 2100 in Asia, Europe, and South America, it is predicted to grow significantly in Africa. While there were 1.5 billion inhabitants on the continent at the beginning of 2024, the number of inhabitants is expected to reach 3.8 billion by 2100. In total, the global population is expected to reach nearly 10.4 billion by 2100. Worldwide population In the United States, the total population is expected to steadily increase over the next couple of years. In 2024, Asia held over half of the global population and is expected to have the highest number of people living in urban areas in 2050. Asia is home to the two most populous countries, India and China, both with a population of over one billion people. However, the small country of Monaco had the highest population density worldwide in 2021. Effects of overpopulation Alongside the growing worldwide population, there are negative effects of overpopulation. The increasing population puts a higher pressure on existing resources and contributes to pollution. As the population grows, the demand for food grows, which requires more water, which in turn takes away from the freshwater available. Concurrently, food needs to be transported through different mechanisms, which contributes to air pollution. Not every resource is renewable, meaning the world is using up limited resources that will eventually run out. Furthermore, more species will become extinct which harms the ecosystem and food chain. Overpopulation was considered to be one of the most important environmental issues worldwide in 2020.

  5. Population by Cities

    • kaggle.com
    Updated Nov 18, 2024
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    Umair A. Chaudhry (2024). Population by Cities [Dataset]. https://www.kaggle.com/datasets/umxir9/population-by-cities
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 18, 2024
    Dataset provided by
    Kaggle
    Authors
    Umair A. Chaudhry
    License

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

    Description

    Database Name: population_cities

    Description: The population_cities dataset provides information on the population of various cities worldwide. It includes key details such as the city's name, the country it is located in, the total population, and the continent it belongs to. This dataset is ideal for researchers, data analysts, and enthusiasts looking to explore global population trends, conduct regional comparisons, or analyze urban demographics across continents.

    Columns:
    1. City: Name of the city.
    2. Country: Name of the country where the city is located.
    3. Population: Total population of the city.
    4. Continent: The continent where the city is situated (e.g., Asia, Europe, Africa, etc.).

    Potential Uses: - Comparative analysis of city populations across continents.
    - Visualization of population density in specific regions.
    - Studies on urbanization trends and growth patterns.
    - Development of machine learning models for population prediction or clustering analysis.

    Feel free to explore and share insights from this dataset!

  6. Historical population of the continents 10,000BCE-2000CE

    • statista.com
    Updated Dec 31, 2007
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    Statista (2007). Historical population of the continents 10,000BCE-2000CE [Dataset]. https://www.statista.com/statistics/1006557/global-population-per-continent-10000bce-2000ce/
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    Dataset updated
    Dec 31, 2007
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The earliest point where scientists can make reasonable estimates for the population of global regions is around 10,000 years before the Common Era (or 12,000 years ago). Estimates suggest that Asia has consistently been the most populated continent, and the least populated continent has generally been Oceania (although it was more heavily populated than areas such as North America in very early years). Population growth was very slow, but an increase can be observed between most of the given time periods. There were, however, dips in population due to pandemics, the most notable of these being the impact of plague in Eurasia in the 14th century, and the impact of European contact with the indigenous populations of the Americas after 1492, where it took almost four centuries for the population of Latin America to return to its pre-1500 level. The world's population first reached one billion people in 1803, which also coincided with a spike in population growth, due to the onset of the demographic transition. This wave of growth first spread across the most industrially developed countries in the 19th century, and the correlation between demographic development and industrial or economic maturity continued until today, with Africa being the final major region to begin its transition in the late-1900s.

  7. World Population Statistics - 2023

    • kaggle.com
    Updated Jan 9, 2024
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    Bhavik Jikadara (2024). World Population Statistics - 2023 [Dataset]. https://www.kaggle.com/datasets/bhavikjikadara/world-population-statistics-2023
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 9, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bhavik Jikadara
    License

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

    Area covered
    World
    Description
    • The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
    • China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
    • The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
    • Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
    • In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
    • This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

    Content

    • In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
    • Rank: Rank by Population.
    • CCA3: 3 Digit Country/Territories Code.
    • Country/Territories: Name of the Country/Territories.
    • Capital: Name of the Capital.
    • Continent: Name of the Continent.
    • 2022 Population: Population of the Country/Territories in the year 2022.
    • 2020 Population: Population of the Country/Territories in the year 2020.
    • 2015 Population: Population of the Country/Territories in the year 2015.
    • 2010 Population: Population of the Country/Territories in the year 2010.
    • 2000 Population: Population of the Country/Territories in the year 2000.
    • 1990 Population: Population of the Country/Territories in the year 1990.
    • 1980 Population: Population of the Country/Territories in the year 1980.
    • 1970 Population: Population of the Country/Territories in the year 1970.
    • Area (km²): Area size of the Country/Territories in square kilometers.
    • Density (per km²): Population Density per square kilometer.
    • Growth Rate: Population Growth Rate by Country/Territories.
    • World Population Percentage: The population percentage by each Country/Territories.
  8. Population density in Africa 2000-2030

    • statista.com
    Updated Jul 1, 2025
    + more versions
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    Statista (2025). Population density in Africa 2000-2030 [Dataset]. https://www.statista.com/statistics/1225875/population-density-in-africa/
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    Dataset updated
    Jul 1, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Africa
    Description

    In 2024, the population density in Africa was 51.3 inhabitants per square kilometer. From 2000 onwards, the density of the population on the continent has increased annually. Moreover, the average number of people living within a square kilometer was expected to increase to around 58.5 by 2030. Mauritius, Rwanda, and Burundi were the African countries with the highest population density as of 2023.

  9. Population; key figures

    • cbs.nl
    • ckan.mobidatalab.eu
    • +1more
    xml
    Updated Jul 17, 2024
    + more versions
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    Centraal Bureau voor de Statistiek (2024). Population; key figures [Dataset]. https://www.cbs.nl/en-gb/figures/detail/85496ENG
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    xmlAvailable download formats
    Dataset updated
    Jul 17, 2024
    Dataset provided by
    Statistics Netherlands
    Authors
    Centraal Bureau voor de Statistiek
    License

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

    Time period covered
    1950 - 2024
    Area covered
    Netherlands
    Description

    Key figures on the population of the Netherlands.

    The following information is available: - Population by sex; - Population by marital status; - Population by age (groups); - Population by origin; - Private households; - Persons in institutional households; - Population growth; - Population density.

    CBS is in transition towards a new classification of the population by origin. Greater emphasis is now placed on where a person was born, aside from where that person’s parents were born. The term ‘migration background’ is no longer used in this regard. The main categories western/non-western are being replaced by categories based on continents and a few countries that share a specific migration history with the Netherlands. The new classification is being implemented gradually in tables and publications on population by origin.

    Data available from: 1950 Figures on population by origin are only available from 2022 at this moment. The periods 1996 through 2021 will be added to the table at a later time.

    Status of the figures: All the figures are final.

    Changes as of 17 July 2024: Final figures with regard to population growth for 2023 and final figures of the population on 1 January 2024 have been added.

    Changes as of 26 April 2023: None, this is a new table. This table succeeds the table Population; key figures; 1950-2022. See section 3. The following changes have been implemented compared to the discontinued table: - The topic folder 'Population by migration background' has been replaced by 'Population by origin'; - The underlying topic folders regarding 'first and second generation migration background' have been replaced by 'Born in the Netherlands' and 'Born abroad'; - The origin countries Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan, Turkmenistan and Turkey have been assigned to the continent of Asia (previously Europe).

    When will new figures be published? In the last quarter of 2025 final figures with regard to population growth for 2024 and final figures of the population on 1 January 2025 will be added.

  10. a

    Urbanization in Africa

    • hub.arcgis.com
    • fesec-cesj.opendata.arcgis.com
    • +1more
    Updated Apr 27, 2019
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    ArcGIS StoryMaps (2019). Urbanization in Africa [Dataset]. https://hub.arcgis.com/maps/0263c93beb6a471e97497f1fca05d8e6
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    Dataset updated
    Apr 27, 2019
    Dataset authored and provided by
    ArcGIS StoryMaps
    Area covered
    Description

    This map presents layers derived from Africapolis.org and NASA's Socioeconomic Data and Applications Center (SEDAC) hosted by Columbia University.Africapolis data consists of urban populations from 1950 through 2015 and percentage of the population that is urban (the urban level). SEDAC data represents population density at local scales for the continent of Africa.This map is featured in Urban Africa produced by Esri's StoryMaps team. In generating this map, the StoryMaps team downloaded the original data files from the Africapolis and SEDAC data portals, cleaned and processed the spreadsheets, and visualized the output feature layers in ArcGIS Online.AfricapolisTotal population, city and country (2015)Urban population, city and country (2015)Percent change in urban population, city and country (2000, 2015)SEDACPopulation density (2015)

  11. d

    countries Main continent Africa

    • deepfo.com
    csv, excel, html, xml
    Updated Jul 22, 2021
    + more versions
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    Deepfo.com by Polyolbion SL, Barcelona, Spain (2021). countries Main continent Africa [Dataset]. https://deepfo.com/en/most/countries-Main-continent-Africa
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    csv, excel, html, xmlAvailable download formats
    Dataset updated
    Jul 22, 2021
    Dataset authored and provided by
    Deepfo.com by Polyolbion SL, Barcelona, Spain
    License

    https://deepfo.com/documentacion.php?idioma=enhttps://deepfo.com/documentacion.php?idioma=en

    Area covered
    Africa
    Description

    countries Main continent Africa. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

  12. d

    Terrestrial Condition Assessment (TCA) Feral Pig Density (Map Service)

    • catalog.data.gov
    • agdatacommons.nal.usda.gov
    • +3more
    Updated Apr 21, 2025
    + more versions
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    U.S. Forest Service (2025). Terrestrial Condition Assessment (TCA) Feral Pig Density (Map Service) [Dataset]. https://catalog.data.gov/dataset/terrestrial-condition-assessment-tca-feral-pig-density-map-service-42e23
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    Dataset updated
    Apr 21, 2025
    Dataset provided by
    U.S. Forest Service
    Description

    Data are derived from generalized linear models and model selection techniques using 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents. Models were used to determine the strength of association among a diverse set of biotic and abiotic factors associated with wild pig population dynamics. The models and associated factors were used to predict the potential population density of wild pigs at the 1 km resolution. Predictions were then compared with available population estimates for wild pigs on their native range in North America indicating the predicted densities are within observed values. See Lewis et al (2017) and Lewis et al (2019) for more information.Lewis, Jesse S., Matthew L. Farnsworth, Chris L. Burdett, David M. Theobald, Miranda Gray, and Ryan S. Miller. "Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal." Scientific reports7 (2017): 44152.Lewis, Jesse S., Joseph L. Corn, John J. Mayer, Thomas R. Jordan, Matthew L. Farnsworth, Christopher L. Burdett, Kurt C. VerCauteren, Steven J. Sweeney, and Ryan S. Miller. "Historical, current, and potential population size estimates of invasive wild pigs (Sus scrofa) in the United States." Biological Invasions21, no. 7 (2019): 2373-2384.

  13. d

    Data from: Mammal population densities at a global scale are higher in...

    • datadryad.org
    zip
    Updated Sep 22, 2020
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    Marlee A. Tucker; Luca Santini; Chris Carbone; Thomas Mueller (2020). Mammal population densities at a global scale are higher in human-modified areas [Dataset]. http://doi.org/10.5061/dryad.m63xsj40d
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    zipAvailable download formats
    Dataset updated
    Sep 22, 2020
    Dataset provided by
    Dryad
    Authors
    Marlee A. Tucker; Luca Santini; Chris Carbone; Thomas Mueller
    Time period covered
    Sep 18, 2020
    Description

    This data file includes 6729 population density estimates of 468 terrestrial mammal species. Population density is measured as the number of individuals per square kilometre. Also included are taxonomic information (order & family), longitude/latitude of the location where population density was estimated, the site/country/continent where the estimate was collected, the method used to estimate density, mean body mass (grams), and trophic guild. The environmental covariates associated with each denisty estimate is also included accessibility, human footprint index, night-time lights, percentage of cropland, percentage of pasture, human population density, Normalized Difference Vegetation Index (NDVI) and mean mammal species richness. These environmental covariates have three different spatial resolutions including 1 km, 10 km and 50 km, and were extracted based on the longitude/latitude position and in the case of the 10 km data, using a buffer with a radius...

  14. d

    Code and data from: Survey-based inference of continental African elephant...

    • datadryad.org
    • data.niaid.nih.gov
    zip
    Updated Oct 25, 2024
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    Charles Edwards; George Wittemyer (2024). Code and data from: Survey-based inference of continental African elephant decline [Dataset]. http://doi.org/10.5061/dryad.brv15dvjw
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    zipAvailable download formats
    Dataset updated
    Oct 25, 2024
    Dataset provided by
    Dryad
    Authors
    Charles Edwards; George Wittemyer
    Time period covered
    Oct 7, 2024
    Area covered
    Africa
    Description

    Code for analysis of data in 'Survey-based inference of continental African elephant decline'

    https://doi.org/10.5061/dryad.brv15dvjw

    Survey-based inference of continental African elephant decline

    Code and scripts for model release. R code is supplied for running the constant and linear trend models with the global, species and regional partitions. To execute each model using R (>=4.4.1) and rstan (>=2.32.6) simply run the run_regression.R script within the appropriate directory.

    Please contact the authors if any assistance is required.

    Files and variables

    Two data files are included: "DataFileElephantTrends" and "survey_area"

    The first file "DataFile_ElephantTrends" contains 6 columns of data. The names of sites for which survey data are available of African elephant numbers are in the column labeled "site" - note these sites names have been anonymized to comply with IUCN rules regarding place names harboring a ...

  15. g

    Population; key figures | gimi9.com

    • gimi9.com
    Updated May 3, 2025
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    (2025). Population; key figures | gimi9.com [Dataset]. https://gimi9.com/dataset/nl_38367-population--key-figures/
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    Dataset updated
    May 3, 2025
    License

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

    Description

    🇳🇱 네덜란드 Dutch Key figures on the population of the Netherlands. The following information is available: - Population by sex; - Population by marital status; - Population by age (groups); - Population by origin; - Private households; - Persons in institutional households; - Population growth; - Population density. CBS is in transition towards a new classification of the population by origin. Greater emphasis is now placed on where a person was born, aside from where that person’s parents were born. The term ‘migration background’ is no longer used in this regard. The main categories western/non-western are being replaced by categories based on continents and a few countries that share a specific migration history with the Netherlands. The new classification is being implemented gradually in tables and publications on population by origin. Data available from: 1950 Figures on population by origin are only available from 2022 at this moment. The periods 1996 through 2021 will be added to the table at a later time. Status of the figures: All the figures are final. Changes as of 17 July 2024: Final figures with regard to population growth for 2023 and final figures of the population on 1 January 2024 have been added. Changes as of 26 April 2023: None, this is a new table. This table succeeds the table Population; key figures; 1950-2022. See section 3. The following changes have been implemented compared to the discontinued table: - The topic folder 'Population by migration background' has been replaced by 'Population by origin'; - The underlying topic folders regarding 'first and second generation migration background' have been replaced by 'Born in the Netherlands' and 'Born abroad'; - The origin countries Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan, Turkmenistan and Turkey have been assigned to the continent of Asia (previously Europe). When will new figures be published? In the last quarter of 2025 final figures with regard to population growth for 2024 and final figures of the population on 1 January 2025 will be added.

  16. Population in Africa 2024, by selected country

    • ai-chatbox.pro
    Updated Jul 8, 2024
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    Saifaddin Galal (2024). Population in Africa 2024, by selected country [Dataset]. https://www.ai-chatbox.pro/?_=%2Ftopics%2F7499%2Fdemographics-of-algeria%2F%23XgboDwS6a1rKoGJjSPEePEUG%2FVFd%2Bik%3D
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    Dataset updated
    Jul 8, 2024
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Saifaddin Galal
    Description

    Nigeria has the largest population in Africa. As of 2024, the country counted over 232.6 million individuals, whereas Ethiopia, which ranked second, has around 132 million inhabitants. Egypt registered the largest population in North Africa, reaching nearly 116 million people. In terms of inhabitants per square kilometer, Nigeria only ranks seventh, while Mauritius has the highest population density on the whole African continent. The fastest-growing world region Africa is the second most populous continent in the world, after Asia. Nevertheless, Africa records the highest growth rate worldwide, with figures rising by over two percent every year. In some countries, such as Niger, the Democratic Republic of Congo, and Chad, the population increase peaks at over three percent. With so many births, Africa is also the youngest continent in the world. However, this coincides with a low life expectancy. African cities on the rise The last decades have seen high urbanization rates in Asia, mainly in China and India. However, African cities are currently growing at larger rates. Indeed, most of the fastest-growing cities in the world are located in Sub-Saharan Africa. Gwagwalada, in Nigeria, and Kabinda, in the Democratic Republic of the Congo, ranked first worldwide. By 2035, instead, Africa's fastest-growing cities are forecast to be Bujumbura, in Burundi, and Zinder, Nigeria.

  17. d

    Data from: Cross-continental comparison of parasite communities in a...

    • search.dataone.org
    • data.niaid.nih.gov
    • +2more
    Updated Apr 26, 2025
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    Astrid Stronen; Barbara Molnar; Paolo Ciucci; Chris Darimont; Lorenza Grottoli; Paul Paquet; Tim Sallows; Judit Smits; Heather Bryan (2025). Cross-continental comparison of parasite communities in a wide-ranging carnivore suggests associations with prey diversity and host density [Dataset]. http://doi.org/10.5061/dryad.3r2280gg9
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    Dataset updated
    Apr 26, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Astrid Stronen; Barbara Molnar; Paolo Ciucci; Chris Darimont; Lorenza Grottoli; Paul Paquet; Tim Sallows; Judit Smits; Heather Bryan
    Time period covered
    Jan 1, 2021
    Description

    Parasites are integral to ecosystem functioning yet often overlooked. Improved understanding of host-parasite associations is important, particularly for wide-ranging species for which host range shifts and climate change could alter host-parasite interactions and their effects on ecosystem function.

    Among the most widely distributed mammals with diverse diets, grey wolves (Canis lupus) host parasites that are transmitted among canids and via prey species. Grey wolf-parasite associations may therefore influence the population dynamics and ecological functions of both wolves and their prey. Our goal was to identify large-scale processes that shape host-parasite interactions across populations, with the grey wolf as a model organism.

    By compiling data from various studies, we examined the faecal prevalence of gastrointestinal parasites in six wolf populations from two continents in relation to wolf density, diet diversity, and other ecological conditions.

    As expected, we found ...

  18. Data from: A continent-scale test of multiple hypotheses on the abundances...

    • zenodo.org
    • data.niaid.nih.gov
    • +1more
    bin, csv
    Updated May 28, 2022
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    David W. Kikuchi; Gustavo H. Kattan; Kimberly C. Navarro Velez; David W. Kikuchi; Gustavo H. Kattan; Kimberly C. Navarro Velez (2022). Data from: A continent-scale test of multiple hypotheses on the abundances of Neotropical birds [Dataset]. http://doi.org/10.5061/dryad.k5912k6
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    bin, csvAvailable download formats
    Dataset updated
    May 28, 2022
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    David W. Kikuchi; Gustavo H. Kattan; Kimberly C. Navarro Velez; David W. Kikuchi; Gustavo H. Kattan; Kimberly C. Navarro Velez
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    Explaining variation in the abundance of species remains a challenge in ecology. We sought to explain variation in abundance of Neotropical forest birds using a dataset of population densities of 596 species. We tested a priori hypotheses for the roles of species traits, environmental factors, and species interactions. Specifically, we focused on four factors: 1) body mass (trait); 2) habitat type (environmental factor), 3) net primary productivity (NPP; environmental factor); and 4) species richness of competitors (species interaction). Body size explained much variation in density, although only when analyzed at higher taxonomic levels. Habitat type was a strong predictor of density. The relationship between density and productivity was weak. Densities were related negatively to the species richness of heterospecifics, however – this trend was particularly strong within closely related groups. Our results show that the influence of energetic factors such as body size and productivity depends on phylogeny, and they act through indirect relations with other variables; alternative ecological factors such as habitat structure and species interactions play a more direct and stronger role in determining abundance than previously thought.

  19. n

    Data from: Continent-wide effects of urbanization on bird and mammal genetic...

    • data.niaid.nih.gov
    • search.dataone.org
    • +2more
    zip
    Updated Jan 20, 2020
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    Chloé Schmidt; Michael Domaratzki; Riikka Kinnunen; Jeff Bowman; Colin Garroway (2020). Continent-wide effects of urbanization on bird and mammal genetic diversity [Dataset]. http://doi.org/10.5061/dryad.cz8w9gj0c
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    zipAvailable download formats
    Dataset updated
    Jan 20, 2020
    Dataset provided by
    Ministry of Natural Resources and Forestry
    University of Manitoba
    Authors
    Chloé Schmidt; Michael Domaratzki; Riikka Kinnunen; Jeff Bowman; Colin Garroway
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    Urbanization and associated environmental changes are causing global declines in vertebrate populations. In general, population declines of the magnitudes now detected should lead to reduced effective population sizes for animals living in proximity to humans and disturbed lands. This is cause for concern because effective population sizes set the rate of genetic diversity loss due to genetic drift, the rate of increase in inbreeding, and the efficiency with which selection can act on beneficial alleles. We predicted that the effects of urbanization should decrease effective population size and genetic diversity, and increase population-level genetic differentiation. To test for such patterns, we repurposed and reanalyzed publicly archived genetic data sets for North American birds and mammals. After filtering, we had usable raw genotype data from 85 studies and 41,023 individuals, sampled from 1,008 locations spanning 41 mammal and 25 bird species. We used census-based urban-rural designations, human population density, and the Human Footprint Index as measures of urbanization and habitat disturbance. As predicted, mammals sampled in more disturbed environments had lower effective population sizes and genetic diversity, and were more genetically differentiated from those in more natural environments. There were no consistent relationships detectable for birds. This suggests that, in general, mammal populations living near humans may have less capacity to respond adaptively to further environmental changes, and be more likely to suffer from effects of inbreeding.

  20. t

    (Table 1) Population density and biomass of the foraminifer Rupertina, and...

    • service.tib.eu
    Updated Nov 30, 2024
    + more versions
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    (2024). (Table 1) Population density and biomass of the foraminifer Rupertina, and grain size of cores from the Norwegian continental slope - Vdataset - LDM [Dataset]. https://service.tib.eu/ldmservice/dataset/png-doi-10-1594-pangaea-784979
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    Dataset updated
    Nov 30, 2024
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Description

    Rupertina stabilis occupies a depth restricted biotope of suspension feeding animals situated at the Norwegian continental margin. It extends from the Voring plateau northwards for at least 200 - 300 km, in depths between 600 and 800 m. This slope position is known for relatively strong bottom currents and shifting watermass boundaries. - The species is attached to hard substrates, mainly stones or hydroid stalks and obviously prefers an elevated position. It is building a permanent cyst of sponge spicules and debris at the apertural region. The spicules are used to support a pseudopodial network similar to that described from Halyphysema (LIPPS 1983). It is believed to serve as a filter apparatus. - A review of known occurences in the Atlantic is given, suggesting a temperature adaption of the species ranging from 0°C to a maximum of 8°C. Specimens were successfully cultured for about 2-3 weeks.

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Statista (2025). Global population density by region 2025 [Dataset]. https://www.statista.com/statistics/912416/global-population-density-by-region/
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Global population density by region 2025

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Dataset updated
May 27, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2025
Area covered
Worldwide
Description

As of 2025, Asia was the most densely populated region of the world, with nearly 156 inhabitants per square kilometer, whereas Oceania's population density was just over five inhabitants per square kilometer.

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