Ukraine SSSU Forecast: Population: Constant Variant data was reported at 27,535.250 Person th in 2060. This records a decrease from the previous number of 27,927.475 Person th for 2059. Ukraine SSSU Forecast: Population: Constant Variant data is updated yearly, averaging 37,346.617 Person th from Dec 2011 (Median) to 2060, with 50 observations. The data reached an all-time high of 45,402.678 Person th in 2011 and a record low of 27,535.250 Person th in 2060. Ukraine SSSU Forecast: Population: Constant Variant data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.G005: Population: Forecast: State Statistical Service of Ukraine. The Constant Variant assumes all components are fixed at their level in 2010.

Non-selective effects, like genetic drift, are an important factor in modern conceptions of evolution, and have been extensively studied for constant population sizes (Kimura, 1955; Otto and Whitlock, 1997). Here, we consider non-selective evolution in the case of growing populations that are of small size and have varying trait compositions (e.g. after a population bottleneck). We find that, in these conditions, populations never fixate to a trait, but tend to a random limit composition, and that the distribution of compositions “freezes” to a steady state. This final state is crucially influenced by the initial conditions. We obtain these findings from a combined theoretical and experimental approach, using multiple mixed subpopulations of two Pseudomonas putida strains in non-selective growth conditions (Matthijs et al, 2009) as model system. The experimental results for the population dynamics match the theoretical predictions based on the Pólya urn model (Eggenberger and Pólya, 1923) for all analyzed parameter regimes. In summary, we show that exponential growth stops genetic drift. This result contrasts with previous theoretical analyses of non-selective evolution (e.g. genetic drift), which investigated how traits spread and eventually take over populations (fixate) (Kimura, 1955; Otto and Whitlock, 1997). Moreover, our work highlights how deeply growth influences non-selective evolution, and how it plays a key role in maintaining genetic variability. Consequently, it is of particular importance in life-cycles models (Melbinger et al, 2010; Cremer et al, 2011; Cremer et al, 2012) of periodically shrinking and expanding populations.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Constant fertility variant projection for the UK - population by five-year age groups and sex.

Continuous Population Statistics: Resident population by date, sex and age. Quarterly. Provinces.

In 2024, the population of Africa was projected to grow by 2.27 percent compared to the previous year. The population growth rate on the continent has been constantly over 2.5 percent from 2000 onwards, and it peaked at 2.63 percent in 2013. Despite a slowdown in the growth rate after that, the continent's population will continue to increase significantly in the coming years. The second-largest population worldwide In 2023, the total population of Africa amounted to almost 1.5 billion. The number of inhabitants had grown steadily in the previous decades, rising from approximately 831 million in 2000. Driven by a decreasing mortality rate and a higher life expectancy at birth, the African population was forecast to increase to about 2.5 billion individuals by 2050. Africa is currently the second most populous continent worldwide after Asia. However, forecasts showed that Africa could gradually close the gap and almost reach the size of the Asian population in 2100. By that year, Africa might count 3.8 billion people, compared to 4.6 billion in Asia. The world's youngest continent The median age in Africa corresponded to 19.2 years in 2024. Although the median age has increased in recent years, the continent remains the youngest worldwide. In 2023, roughly 40 percent of the African population was aged 15 years and younger, compared to a global average of 25 percent. Africa recorded not only the highest share of youth but also the smallest elderly population worldwide. As of the same year, only three percent of Africa's population was aged 65 years and older. Africa and Latin America were the only regions below the global average of ten percent. On the continent, Niger, Uganda, and Angola were the countries with the youngest population in 2023.

Values in brackets represent the probabilities for each class of scenarios that the constant population size model (SIC, CMC, AMC, and SCC, see Fig. 3) is the correct model, given the observed posterior probabilities (see Text S1).

The population density in Stockholm increased steadily since 2010, reaching ***** inhabitants per square kilometer in 2022. This corresponds with the constant population growth in the city during the same period.

Brazil Population: Residents: North: Amazonas: Benjamin Constant data was reported at 42,020.000 Person in 2018. This records an increase from the previous number of 41,329.000 Person for 2017. Brazil Population: Residents: North: Amazonas: Benjamin Constant data is updated yearly, averaging 26,974.000 Person from Jun 1992 (Median) to 2018, with 24 observations. The data reached an all-time high of 42,020.000 Person in 2018 and a record low of 19,178.000 Person in 1992. Brazil Population: Residents: North: Amazonas: Benjamin Constant data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAA035: Population: by Municipality: North: Amazonas.

Working Age Population: % Share: Brazil: by Number of Year Studies data was reported at 100.000 % in Mar 2019. This stayed constant from the previous number of 100.000 % for Dec 2018. Working Age Population: % Share: Brazil: by Number of Year Studies data is updated quarterly, averaging 100.000 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 100.000 % in Mar 2019 and a record low of 100.000 % in Mar 2019. Working Age Population: % Share: Brazil: by Number of Year Studies data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA022: Continuous National Household Sample Survey: Working Age Population: % Share: by Number of Year Studies. [External Remarks] Person at work age covers people with 14 years or more at the reference date.

*Effective population size (expressed as 103 individuals) for A. halleri (hal), A. lyrata (lyr), and their ancestor (A).†Time (ka) of the split between A. halleri and A. lyrata.The 95% highest posterior density intervals are shown in parentheses.

Brazil Working Age Population: Labour Force: % Share: Mato Grosso data was reported at 100.000 % in Mar 2019. This stayed constant from the previous number of 100.000 % for Dec 2018. Brazil Working Age Population: Labour Force: % Share: Mato Grosso data is updated quarterly, averaging 100.000 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 100.000 % in Mar 2019 and a record low of 100.000 % in Mar 2019. Brazil Working Age Population: Labour Force: % Share: Mato Grosso data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA023: Continuous National Household Sample Survey: Working Age Population: % Share: Labour Force: by Sex.

Working Age Population: % Share: Espírito Santo data was reported at 100.000 % in Mar 2019. This stayed constant from the previous number of 100.000 % for Dec 2018. Working Age Population: % Share: Espírito Santo data is updated quarterly, averaging 100.000 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 100.000 % in Mar 2019 and a record low of 100.000 % in Mar 2019. Working Age Population: % Share: Espírito Santo data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA020: Continuous National Household Sample Survey: Working Age Population: % Share: by Sex.

Brazil Population Census: South: Rio Grande do Sul: Benjamin Constant do Sul data was reported at 2,307.000 Person in 2010. This records an increase from the previous number of 2,256.000 Person for 2007. Brazil Population Census: South: Rio Grande do Sul: Benjamin Constant do Sul data is updated yearly, averaging 2,307.000 Person from Jul 2000 (Median) to 2010, with 3 observations. The data reached an all-time high of 2,727.000 Person in 2000 and a record low of 2,256.000 Person in 2007. Brazil Population Census: South: Rio Grande do Sul: Benjamin Constant do Sul data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAC058: Population Census: by Municipality: South: Rio Grande do Sul.

Working Age Population: % Share: São Paulo data was reported at 100.000 % in Mar 2019. This stayed constant from the previous number of 100.000 % for Dec 2018. Working Age Population: % Share: São Paulo data is updated quarterly, averaging 100.000 % from Mar 2012 (Median) to Mar 2019, with 29 observations. The data reached an all-time high of 100.000 % in Mar 2019 and a record low of 100.000 % in Mar 2019. Working Age Population: % Share: São Paulo data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBA020: Continuous National Household Sample Survey: Working Age Population: % Share: by Sex.

Sustained below replacement fertility leads to declining population size. Several countries in Asia have experienced below replacement fertility for many years. The paper applies a novel approach to examining the viability of using immigration to achieve zero population growth in six Asian countries: China, Japan, Republic of Korea, Thailand, Singapore and Australia. The novel approach is to estimate the level of immigration that would be required to maintain a constant annual number of births in the long term. Maintaining the number of births at the current level is the fastest way to achieve eventual zero population growth. A population with a constant annual number of births, labeled as a quasi-stationary population, also has a near-to constant age structure that is not excessively old. The study concludes that, for all countries except Australia, no reasonable level of immigration could produce a quasi-stationary population if fertility remains at the country's 2020 level. The constraining factors are the current population size and level of fertility and the extent to which there is acceptance of permanent immigrants in the country. If fertility were to increase over 15–20 years to 1.7 births per woman and the country was accepting of relatively large numbers of permanent immigrants, the quasi-stable outcome becomes potentially viable for all countries except China.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

Brazil Population Census: North: Amazonas: Benjamin Constant data was reported at 33,411.000 Person in 2010. This records an increase from the previous number of 29,268.000 Person for 2007. Brazil Population Census: North: Amazonas: Benjamin Constant data is updated yearly, averaging 26,450.500 Person from Jul 1996 (Median) to 2010, with 4 observations. The data reached an all-time high of 33,411.000 Person in 2010 and a record low of 23,219.000 Person in 2000. Brazil Population Census: North: Amazonas: Benjamin Constant data remains active status in CEIC and is reported by Brazilian Institute of Geography and Statistics. The data is categorized under Brazil Premium Database’s Socio and Demographic – Table BR.GAC039: Population Census: by Municipality: North: Amazonas.

This is a data record of the input and output data associated with the following publication:

Jiang, L., B.C. O'Neill, H. Zoraghein, and S. Dahlke. 2020. Population scenarios for U.S. states consistent with Shared Socioeconomic Pathways. Environmental Research Letters, https://doi.org/10.1088/1748-9326/aba5b1.

The accompanying code can be found here:

Zoraghein, H., R. Nawrotzki, L. Jiang, and S. Dahlke (2020). IMMM-SFA/statepop: v0.1.0 (Version v0.1.0). Zenodo. http://doi.org/10.5281/zenodo.3956703

The following detail the contents:

SSP.zip

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_In_Mig.jpg

output figure for in-migration change through time for the target state

_Net_Mig.jpg

output figure for net-migration change through time for the target state

_Out_Mig.jpg

output figure for out-migration change through time for the target state

_proj_in_mig.csv

projected age and gender specific number of domestic in-migration for the state over time

_proj_net_mig.csv

projected age and gender specific number of domestic net-migration for the state over time

_proj_out_mig.csv

projected age and gender specific number of domestic out-migration for the state over time

_proj_pop.csv

projected age and gender specific number of population for the state over time

_total_in_mig.csv

projected age and gender specific in-migration from other states to the current state over time

_total_out_mig.csv

projected age and gender specific out-migration from the current state to other states over time

_.jpg

figure for projected change of population for the state

State_inputs.zip

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_in_mig.csv

a table containing gender- and age-specific migration rates from all states to the current state at the base year.

_out_mig.csv

a table containing gender- and age-specific migration rates from the current state to all other states at the base year.

basePop.csv

a table containing gender- and age-specific counts of people in the current state at the base year (2010).

Constant_rate.csv

a table that constructs a constant scenario for fertility, mortality (life expectancy), urbanization level (required if we differentiate urban and rural), sex ratio at birth and net estimates of international migrants for the current state. The table is from 2010 to 2100 at 5 year intervals used for scenario building. The presented scenario, for instance, keeps everything constant at its historical record estimated from the data.

fertility.csv

a table containing age-specific fertility rates for the current state at the base year.

intMig.csv

a table containing gender- and age-specific proportions of international migrants to the current state at the base year.

mortality.csv

a table containing gender- and age-specific life expectancy and mortality rates for the current state at the base year (life table).

The simulated data is generated using msprime for testing SMC++ under different sets of demographic models. We have generated ten different replicates with each demographic model. The demographic_model_1 includes population bottleneck followed by constant population size and then population expansion. demographic_model_2 simulates a population with constant population size throughout history. demographic_model_3 simulates population expansion post-population formulation. The README file within the folder contains the information about the demographic models.