Until the 1800s, population growth was incredibly slow on a global level. The global population was estimated to have been around 188 million people in the year 1CE, and did not reach one billion until around 1803. However, since the 1800s, a phenomenon known as the demographic transition has seen population growth skyrocket, reaching eight billion people in 2023, and this is expected to peak at over 10 billion in the 2080s.

The world's population first reached one billion people in 1805, and reached eight billion in 2022, and will peak at almost 10.2 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two-thirds of the world's population lives in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a few years later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

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.

Between 1800 and 2021, the total population of each continent experienced consistent growth, however as growth rates varied by region, population distribution has fluctuated. In the early 19th century, almost 70 percent of the world's population lived in Asia, while fewer than 10 percent lived in Africa. By the end of this century, it is believed that Asia's share will fall to roughly 45 percent, while Africa's will be on course to reach 40 percent. 19th and 20th centuries Fewer than 2.5 percent of the world's population lived in the Americas in 1800, however the demographic transition, along with waves of migration, would see this share rise to almost 10 percent a century later, peaking at almost 14 percent in the 1960s. Europe's share of the global population also grew in the 19th century, to roughly a quarter in 1900, but fell thereafter and saw the largest relative decline during the 20th century. Asia, which has consistently been the world's most populous continent, saw its population share drop by the mid-1900s, but it has been around 60 percent since the 1970s. It is important to note that the world population has grown from approximately one to eight billion people between 1800 and the 2020s, and that declines in population distribution before 2020 have resulted from different growth rates across the continents. 21st century Africa's population share remained fairly constant throughout this time, fluctuating between 7.5 and 10 percent until the late-1900s, but it is set to see the largest change over the 21st century. As Europe's total population is now falling, and it is estimated that the total populations of Asia and the Americas will fall by the 2050s and 2070s respectively, rapid population growth in Africa will see a significant shift in population distribution. Africa's population is predicted to grow from 1.3 to 3.9 billion people over the next eight decades, and its share of the total population will rise to almost 40 percent. The only other continent whose population will still be growing at this time will be Oceania, although its share of the total population has never been more than 0.7 percent.

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.

Throughout most of human history, global population growth was very low; between 10,000BCE and 1700CE, the average annual increase was just 0.04 percent. Therefore, it took several thousand years for the global population to reach one billion people, doing so in 1803. However, this period marked the beginning of a global phenomenon known as the demographic transition, from which point population growth skyrocketed. With the introduction of modern medicines (especially vaccination), as well as improvements in water sanitation, food supply, and infrastructure, child mortality fell drastically and life expectancy increased, causing the population to grow. This process is linked to economic and technological development, and did not take place concurrently across the globe; it mostly began in Europe and other industrialized regions in the 19thcentury, before spreading across Asia and Latin America in the 20th century. As the most populous societies in the world are found in Asia, the demographic transition in this region coincided with the fastest period of global population growth. Today, Sub-Saharan Africa is the region at the earliest stage of this transition. As population growth slows across the other continents, with the populations of the Americas, Asia, and Europe expected to be in decline by the 2070s, Africa's population is expected to grow by three billion people by the end of the 21st century.

In the last century, the global population has increased by billions of people. And it is still growing. Job opportunities in large cities have caused an influx of people to these already packed locations. This has resulted in an increase in population density for these cities, which are now forced to expand in order to accommodate the growing population. Population density is the average number of people per unit, usually miles or kilometers, of land area. Understanding and mapping population density is important. Experts can use this information to inform decisions around resource allocation, natural disaster relief, and new infrastructure projects. Infectious disease scientists use these maps to understand the spread of infectious disease, a topic that has become critical after the COVID-19 global pandemic.While a useful tool for decision and policymakers, it is important to understand the limitations of population density. Population density is most effective in small scale places—cities or neighborhoods—where people are evenly distributed. Whereas at a larger scale, such as the state, region, or province level, population density could vary widely as it includes a mix of urban, suburban, and rural places. All of these areas have a vastly different population density, but they are averaged together. This means urban areas could appear to have fewer people than they really do, while rural areas would seem to have more. Use this map to explore the estimated global population density (people per square kilometer) in 2020. Where do people tend to live? Why might they choose those places? Do you live in a place with a high population density or a low one?

Population, female (% of total population) in World was reported at 49.72 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Population, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on September of 2025.

Until the 19th century, population growth across the globe was incredibly low. In the first millennium of the Common Era, the world's population grew by an average of just 0.02 percent each year. In Western Europe and Asia, the populations on either side of the millennium were almost the exact same. It was only in the centuries that followed where population growth began to increase, however it was still very low until the 1800s.

Beginning in the 19th century, a phenomenon known as the demographic transition took place, and the world's population began to grow exponentially. The population of the Americas in particular saw the highest average growth rates in these years, due to the high levels of migration and their smaller starting population size in 1820 compared to most other regions. Overall, the average global population growth rate in the period between 1820 and 1998 was roughly six times higher than the preceding eight centuries, and almost 50 times higher than the millennium before that.

The statistic shows the development of the world population from 1950 to 2050. The world population was around 7.38 billion people in 2015.

The global population

As shown above, the total number of people living on Earth has more than doubled since the 1950s, and continues to increase. A look at the development of the world population since the beginning of the Common Era shows that such a surge in numbers is unprecedented. The first significant rise in population occurred during the 14th century, after the Black Death had killed approximately 25 million people worldwide. Subsequently, the global population increased slowly but steadily until it reached record numbers between 1950 and 2000.

The majority of the global population lives on the Asian continent, as a statistic of the world population by continent shows. In around 100 years, it is estimated that population levels on the African continent will have reached similar levels to those we see in Asia today. As for a forecast of the development of the world population, the figures are estimated to have reached more than 10 billion by the 22nd century.

Growing population numbers pose an increasing risk to the planet, since rocketing numbers equal increased consumption of food and resources. Scientists worry that natural resources, such as oil, and food resources will become scarce, endangering the human race and, even more so, the world’s ecosystem. Nowadays, the number of undernourished / starving people worldwide has decreased slightly, but forecasts paint a darker picture.

In 2022, approximately 5.8 billion people across the globe had access to safely managed drinking water resources, an increase of 55.7 percent compared to the beginning of the century.

We shared record-breaking probabilities and population exposures for eight extreme climate extreme indices including PRCPTOT, RX1D, R50, WD, WN, HW, SPH, and CDHW for the late-21st century and mid-21st century under four SSPs, record-breaking probabilities and population exposures for the decadal intervals used in the trend analysis, and data on the share of record-breaking probabilities in exposure trajectories and global exposure trends. Please see the published article for more details.

The methodology used to produce these projections differs from ICLUS v2.0 (https://cfpub.epa.gov/ncea/iclus/recordisplay.cfm?deid=322479). The demographic components of change (i.e., rates of fertility and mortality) for ICLUS v2.1 were taken directly from the Wittgenstein Centre Data Explorer (http://witt.null2.net/shiny/wic/). These projections were produced more recently than the Census projections used in ICLUS v2.0, and incorporate more recent observations of population change. SSP2 is a “middle-of-the-road” projection, where social, economic and technological trends do not shift markedly from historical patterns, resulting in a U.S. population of 455 million people by 2100. Domestic migration trends remain largely consistent with the recent past, however the amenity value of local climate (average precipitation and temperature for summer and winter) is used in ICLUS v2.1.1 to influence migration patterns. The name of the climate model used as the source of future climate patterns is included at the end of the file name (e.g., "GISS-E2-R" or "HadGEM2-ES"). The approach for incorporating climate change into the migration model is described in the ICLUS v2.0 documentation. The SSP5 narrative describes a rapidly growing and flourishing global economy that remains heavily dependent on fossil fuels, and a U.S. population that exceeds 730 million by 2100. ICLUS v2.1 land use projections under SSP5 result in a considerably larger expansion of developed lands relative to SSP2. The the amenity value of local climate (average precipitation and temperature for summer and winter) is used in ICLUS v2.1.1 to influence migration patterns. The name of the climate model used as the source of future climate patterns is included at the end of the file name (e.g., "GISS-E2-R" or "HadGEM2-ES"). The approach for incorporating climate change into the migration model is described in the ICLUS v2.0 documentation. RCP4.5 assumes that global greenhoue gas emissions increase into the latter part of the century, before leveling off and eventually stabilizing by 2100 as a result of various climate change policies. RCP8.5 assumes that global greenhoue gas emissions increase through the year 2100.

There are approximately 8.16 billion people living in the world today, a figure that shows a dramatic increase since the beginning of the Common Era. Since the 1970s, the global population has also more than doubled in size. It is estimated that the world's population will reach and surpass 10 billion people by 2060 and plateau at around 10.3 billion in the 2080s, before it then begins to fall. Asia When it comes to number of inhabitants per continent, Asia is the most populous continent in the world by a significant margin, with roughly 60 percent of the world's population living there. Similar to other global regions, a quarter of inhabitants in Asia are under 15 years of age. The most populous nations in the world are India and China respectively; each inhabit more than three times the amount of people than the third-ranked United States. 10 of the 20 most populous countries in the world are found in Asia. Africa Interestingly, the top 20 countries with highest population growth rate are mainly countries in Africa. This is due to the present stage of Sub-Saharan Africa's demographic transition, where mortality rates are falling significantly, although fertility rates are yet to drop and match this. As much of Asia is nearing the end of its demographic transition, population growth is predicted to be much slower in this century than in the previous; in contrast, Africa's population is expected to reach almost four billion by the year 2100. Unlike demographic transitions in other continents, Africa's population development is being influenced by climate change on a scale unseen by most other global regions. Rising temperatures are exacerbating challenges such as poor sanitation, lack of infrastructure, and political instability, which have historically hindered societal progress. It remains to be seen how Africa and the world at large adapts to this crisis as it continues to cause drought, desertification, natural disasters, and climate migration across the region.

The Titicaca grebe (Rollandia microptera) is a poorly studied endangered species, only found in the Lake Titicaca watershed of Peru and Bolivia. Population surveys undertaken in the early twenty-first century suggested that the species had declined in number by >70%. We conducted a population survey of the grebe between March and August 2022 in Peru and Bolivia, using both maximum entropy and Bayesian occupancy models to estimate factors affecting habitat suitability for the grebe. We conducted surveys between March and August 2022 in Peru and Bolivia. Contrary to the International Union for Conservation of Nature (IUCN) population estimates of <1,000 individuals, there are likely tens of thousands of individual grebes. The population estimation was sensitive to the type of model used. Distance from shore and fishing intensity were the most significant factors influencing grebe populations. The Reserva Nacional del Titicaca, the only protected area in the lake, covers some of the ..., , , # Estimating the Global Population Size and Highlighting Conservation Priority Areas for the Endangered Titicaca Grebe

https://doi.org/10.5061/dryad.tqjq2bw63

Description of the data and file structure

This is supplemental material of the article "Estimating the Global Population Size and Highlighting Conservation Priority Areas for the Endangered Titicaca Grebe"

This includes the R code used in this analysis, the population data, and the rasters which were produced as part of the output. It also includes a word document with a link to the function used to convert continous rasters to binary rasters which is referenced in the text, but not in the bibliography as it was published as part of a blog rather than as part of a published R package.

File Explanations

Rollandia_microptera_points_rounded.csv - rounded data points of the locations of Titicaca Grebes observed in this study. The locations have been rounded due to the species' ...

Some of the SNK rasters intentionally do not align or have the same extent. These rasters were not snapped to a common raster per the authors discretion. Please review selected rasters prior to use. These varying alignments are a result of the use of differing source data sets and all products derived from them. We recommend that users snap or align rasters as best suits their own projects. - This set of files includes downscaled projections of decadal means of monthly total precipitation (in millimeters, no unit conversion necessary) for each month of decades 2020-2029, 2050-2059, and 2060-2069 at 2x2 kilometer spatial resolution. Each file represents a mean monthly total in a given decade.

The spatial extent is clipped to a Seward REA boundary bounding box.

Overview:

Most of SNAP#8217;s climate projections come in multiple versions. There are 5 climate models, one 5 model average, 3 climate scenarios, 12 months, and 100 years. This amounts to 21,600 files per variable. Some datasets are derived products such as monthly decadal averages or specific seasonal averages, among others. This specific dataset is one subset of those.

Each set of files originates from one of five top ranked global circulation models or is calculated as a 5 Model Average. These models are referred to by the acronyms: cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, miroc3_2_medres, or 5modelavg.

For a description of the model selection process, please see Walsh et al. 2008. Global Climate Model Performance over Alaska and Greenland. Journal of Climate. v. 21 pp. 6156-6174

Each set of files also represents one projected emission scenario referred to as: sresb1, sresa2, or sresa1b.

Emmission scenarios in brief:

The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) created a range of scenarios to explore alternative development pathways, covering a wide range of demographic, economic and technological driving forces and resulting greenhouse gas emissions. The B1 scenario describes a convergent world, a global population that peaks in mid-century, with rapid changes in economic structures toward a service and information economy. The Scenario A1B assumes a world of very rapid economic growth, a global population that peaks in mid-century, rapid introduction of new and more efficient technologies, and a balance between fossil fuels and other energy sources. The A2 scenario describes a very heterogeneous world with high population growth, slow economic development and slow technological change.

These files are bias corrected and downscaled via the delta method using PRISM (http:prism.oregonstate.edu) 1961-1990 2km data as baseline climate. Absolute anomalies are utilized for temperature variables. Proportional anomalies are utilized for precipitation variables. Please see http:www.snap.uaf.eduabout for a description of the downscaling process.

File naming scheme:

[variable]_[metric]_[units]_[format]_[assessmentReport] [groupModel][scenario]_[timeFrame].[fileFormat]

[variable] pr, tas, logs, dot, dof, veg, age, dem etc

[metric] mean, total, decadal mean monthly mean, etc

[units] mm, C, in, km

[format] optional, if layer is formatted for special use

[assessmentReport] ar4, ar5

[groupModel] cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, miroc3_2_medres, 5modelavg, cru_ts30

[scenario] sresb1, sresa2, sresa1b

[timeFrame] yyyy or mm_yyyy or yyyy_yyyy or mm_yyyy_mm_yyyy

[fileFormat] txt, png, pdf, bmp, tif

examples:

tas_mean_C_ar4_cccma_cgcm3_1_sresb1_05_2034.tif

this file represents mean May, 2034 temperature from the 4th Assessment Report on Climate Change from the CCCMA modeling group, using their CGCM3.1 model, under the B1 climate scenario.

pr_total_mm_ar4_5modelAvg_sresa1b_09_2077.tif

this file represents total September, 2077 precipitation from the 4th Assessment Report on Climate Change from the 5 Model Average, under the A1B climate scenario.

tas = near-surface air temperature

pr = precipitation including both liquid and solid phases

Over the next 30 years, 90% of global population growth is expected to take place in African and Asian cities alone. While the rates of population growth in many low- and middle-income countries (LMICs) are similar to the rates of high-income countries (HIC) a century ago, the absolute numbers of people being added to LMIC cities today are unprecedented in human history.The majority of those people will live in slums, informal settlements, and other deprived urban areas. Rapid urbanization in LMIC cities means that traditional modes of population data collection such as government administrative records, censuses (conducted roughly every 10 years), and routine household surveys (conducted roughly every five years) are increasingly inaccurate, especially in regard to the urban poorest. With limited updated information about how many people live where, local and national leaders are handicapped in their ability to monitor indicators such as local Sustainable Development Goals (SDGs), and respond effectively to compounding challenges.

This set of files includes downscaled projections of decadal means of July mean temperatures (in degrees Celsius, no unit conversion necessary) for each month of decades 2010-2019, 2020-2029, 2050-2059, and 2060-2069 at 771x771 meter spatial resolution. Each file represents a mean monthly mean in a given decade. Overview: This set of files is an average of five top performing Global Climate Models. These models are referred to by the acronyms: cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, and miroc3_2_medres. For a description of the model selection process, please see Walsh et al. 2008. Global Climate Model Performance over Alaska and Greenland. Journal of Climate. v. 21 pp. 6156-6174 This set of files represents the A2 projected emission scenario. Emission scenarios in brief: The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) created a range of scenarios to explore alternative development pathways, covering a wide range of demographic, economic and technological driving forces and resulting greenhouse gas emissions. The B1 scenario describes a convergent world, a global population that peaks in mid-century, with rapid changes in economic structures toward a service and information economy. The Scenario A1B assumes a world of very rapid economic growth, a global population that peaks in mid-century, rapid introduction of new and more efficient technologies, and a balance between fossil fuels and other energy sources. The A2 scenario describes a very heterogeneous world with high population growth, slow economic development and slow technological change. These files are bias corrected and downscaled via the delta method using PRISM (http://prism.oregonstate.edu/) 1971-2000 771m data as baseline climate. Absolute anomalies are utilized for temperature variables. Proportional anomalies are utilized for precipitation variables. Please see http://www.snap.uaf.edu/about for a description of the downscaling process.

SummaryThis metadata record provides details of the data supporting the claims of the related manuscript: “Projecting future populations of urban agglomerations: around the world and through the 21st century ”.The data consist of HTML files with interactive maps for future populations projections of urban agglomerations, and HTML file displaying figures for postdictions of urban agglomerations, as well as 5 .csv files containing the raw data.The related study estimated population trends throughout the 21st century for approximately 20,000 urban agglomerations in 151 countries by working within the Shared Socioeconomic Pathways (SSPs) and using a simple urban growth model.Data accessThe following resources, which were among the sources of the data analyzed in the related study, are available from the links below.- Postdiction results for 1794 urban agglomerations http://stwww.eng.kagawa-u.ac.jp/~kii/Research/UPP_2020/UPP_2020.html#postdiction-for-1794-agglomerations-link- Temporal evolution from 2010 to 2100 of the geographical distribution of urban agglomerations, arranged by population scale, as predicted within the various SSP scenarios http://stwww.eng.kagawa-u.ac.jp/~kii/Research/UPP_2020/UPP_2020.htmlThese data are also available in raw .csv form via the 'Raw data' link on the same page, and also in the 5 files included as part of this data record.- Available urban-population data include the UN’s World Urbanization Prospects 2018 (https://population.un.org/wup/) and Gridded Population of the World, v4 (https://doi.org/10.7927/H4BC3WMT). Available settlement-point data include, in addition to the above urban population sources, World Gazetteer (https://www.arcgis.com/home/item.html?id=346ce13fa2d4468a9049f71bcc250f37) and GeoNames (https://www.geonames.org/). GDP per capita data is available from OECD.stat (https://stats.oecd.org/), Global Metro Monitor (https://www.brookings.edu/research/global-metro-monitor/), and World Development Indicators (http://datatopics.worldbank.org/world-development-indicators/). OpenStreetMap is available at https://www.openstreetmap.org/. Scenario data for SSPs are available at the IIASA-SSP database (https://doi.org/10.1016/j.gloenvcha.2016.05.009). CodeCode used for the analysis can be downloaded from the author's lab's website: http://stwww.eng.kagawa-u.ac.jp/~kii/Research/UPP_2020/UPP_2020.html#codes. These are written in R. They are provided only for the purpose of tracing the analytical procedure. They are not executable without appropriate datasets.

1. Population and life-history diversity can buffer species from environmental variability and contribute to long-term stability through differing responses to varying conditions akin to the stabilizing effect of asset diversity on financial portfolios. While it is well known that many salmon populations have declined in abundance over the last century, we understand less about how different dimensions of diversity may have shifted. Specifically, how has diminished wild abundance and increased artificial production (i.e., enhancement) changed portfolios of salmon populations, and how might such change influence fisheries and ecosystems?
2. We apply modern genetic tools to century-old sockeye salmon (Oncorhynchus nerka) scales from Canada’s Skeena River watershed to (i) reconstruct historical abundance and age-trait data for 1913–1947 to compare with recent information, (ii) quantify changes in population and life-history diversity and the role of enhancement in population dynamics, and (iii) quantify the risk to fisheries and local ecosystems resulting from observed changes in diversity and enhancement.
3. The total number of wild sockeye returning to the Skeena River during the modern era is 69% lower than during the historical era; all wild populations have declined, several by more than 90%. However, enhancement of a single population has offset declines in wild populations such that aggregate abundances now are similar to historical levels.
4. Population diversity has declined by 70%, and life-history diversity has shifted: populations are migrating from freshwater at an earlier age, and spending more time in the ocean. There also has been a contraction in abundance throughout the watershed, which likely has decreased the spatial extent of salmon provisions to Indigenous fisheries and local ecosystems. Despite the erosion of portfolio strength that this salmon complex hosted a century ago, total returns now are no more variable than they were historically perhaps in part due to the stabilizing effect of artificial production.
5. Policy implications. Our study provides a rare example of the extent of erosion of within-species biodiversity over the last century of human influence. Rebuilding a diversity of abundant wild populations – that is, maintaining functioning portfolios - may help ensure that watershed complexes like the Skeena are robust to global change.
   Methods Generated from fish scales collected in commercial fisheries during 1913–1947 and the skeena tyee test fishery 1973–2016, genetically assigned to population.