Today, globally, women of childbearing age have an average of approximately 2.2 children over the course of their lifetime. In pre-industrial times, most women could expect to have somewhere between five and ten live births throughout their lifetime; however, the demographic transition then sees fertility rates fall significantly. Looking ahead, it is believed that the global fertility rate will fall below replacement level in the 2050s, which will eventually lead to population decline when life expectancy plateaus. Recent decades Between the 1950s and 1970s, the global fertility rate was roughly five children per woman - this was partly due to the post-WWII baby boom in many countries, on top of already-high rates in less-developed countries. The drop around 1960 can be attributed to China's "Great Leap Forward", where famine and disease in the world's most populous country saw the global fertility rate drop by roughly 0.5 children per woman. Between the 1970s and today, fertility rates fell consistently, although the rate of decline noticeably slowed as the baby boomer generation then began having their own children. Replacement level fertility Replacement level fertility, i.e. the number of children born per woman that a population needs for long-term stability, is approximately 2.1 children per woman. Populations may continue to grow naturally despite below-replacement level fertility, due to reduced mortality and increased life expectancy, however, these will plateau with time and then population decline will occur. It is believed that the global fertility rate will drop below replacement level in the mid-2050s, although improvements in healthcare and living standards will see population growth continue into the 2080s when the global population will then start falling.

The data collection contains population projections for UK ethnic groups and all local area by age (single year of age up to 100+) and sex. Included in the data set are also input data to the cohort component model that was used to project populations into the future-fertility rates, mortality rates, international migration flows and internal migration probabilities. Also included in data set are output data: Number of deaths, births and internal migrants. All data included are for the years 2011 to 2061. We have produced two ethnic population projections for UK local authorities, based on information on 2011 Census ethnic populations and 2010-2011-2012 ethnic components. Both projections align fertility and mortality assumptions to ONS assumptions. Where they differ is in the migration assumptions. In LEEDS L1 we employ internal migration rates for 2001 to 2011, including periods of boom and bust. We use a new assumption about international migration anticipating that the UK may leave the EU (BREXIT). In LEEDS L2 we use average internal migration rates for the 5 year period 2006-11 and the official international migration flow assumptions with a long term balance of +185 thousand per annum.

This project aims to understand and to forecast the ethnic transition in the United Kingdom's population at national and sub-national levels. The ethnic transition is the change in population composition from one dominated by the White British to much greater diversity. In the decade 2001-2011 the UK population grew strongly as a result of high immigration, increased fertility and reduced mortality. Both the Office for National Statistics (ONS) and Leeds University estimated the growth or decline in the sixteen ethnic groups making up the UK's population in 2001. The 2011 Census results revealed that both teams had over-estimated the growth of the White British population and under-estimated the growth of the ethnic minority populations. The wide variation between our local authority projected populations in 2011 and the Census suggested inaccurate forecasting of internal migration. We propose to develop, working closely with ONS as our first external partner, fresh estimates of mid-year ethnic populations and their components of change using new data on the later years of the decade and new methods to ensure the estimates agree in 2011 with the Census. This will involve using population accounting theory and an adjustment technique known as iterative proportional fitting to generate a fully consistent set of ethnic population estimates between 2001 and 2011.

We will study, at national and local scales, the development of demographic rates for ethnic group populations (fertility, mortality, internal migration and international migration). The ten year time series of component summary indicators and age-specific rates will provide a basis for modelling future assumptions for projections. We will, in our main projection, align the assumptions to the ONS 2012-based principal projection. The national assumptions will need conversion to ethnic groups and to local scale. The ten years of revised ethnic-specific component rates will enable us to study the relationships between national and local demographic trends. In addition, we will analyse a consistent time series of local authority internal migration. We cannot be sure, at this stage, how the national-local relationships for each ethnic group will be modelled but we will be able to test our models using the time series.

Of course, all future projections of the population are uncertain. We will therefore work to measure the uncertainty of component rates. The error distributions can be used to construct probability distributions of future populations via stochastic projections so that we can define confidence intervals around our projections. Users of projections are always interested in the impact of the component assumptions on future populations. We will run a set of reference projections to estimate the magnitude and direction of impact of international migrations assumptions (net effect of immigration less emigration), of internal migration assumptions (the net effect of in-migration less out-migration), of fertility assumptions compared with replacement level, of mortality assumptions compared with no change and finally the effect of the initial age distribution (i.e. demographic potential).

The outputs from the project will be a set of technical reports on each aspect of the research, journal papers submitted for peer review and a database of projection inputs and outputs available to users via the web. The demographic inputs will be subject to quality assurance by Edge Analytics, our second external partner. They will also help in disseminating these inputs to local government users who want to use them in their own ethnic projections. In sum, the project will show how a wide range of secondary data sources can be used in theoretically refined demographic...

Many populations exhibit boom-bust dynamics in which abundance fluctuates dramatically over time. Past research has focused on identifying whether the cause of fluctuations is primarily exogenous, e.g., environmental stochasticity coupled with weak density dependence, or endogenous, e.g., over-compensatory density dependence. Far fewer studies have addressed whether the mechanism responsible for boom-bust dynamics matters with respect to at-risk species management. Here, we ask whether the best strategy for restoring habitat across a landscape differs under exogenously versus endogenously driven boom-bust dynamics. We used spatially explicit individual-based models to assess how butterfly populations governed by the two mechanisms would respond to habitat restoration strategies that varied in the level of resource patchiness – from a single large patch to multiple patches spaced at different distances. Our models showed that the restoration strategy that minimized extinction risk and boom-bust dynamics would be markedly different depending on the governing mechanism. Exogenously governed populations fared best in a single large habitat patch, whereas for endogenously driven populations, boom-bust dynamics were dampened and extinction risk declined when the total restored area was split into multiple patches with low to moderate inter-patch spacing. Adding environmental stochasticity to the endogenous model did not alter this result. Habitat fragmentation lowered extinction risk in the endogenously driven populations by reducing their growth rate, precluding both "boom" phases and, more importantly, "bust" phases. Our findings suggest that: 1) successful restoration will depend on understanding the causes of fluctuations in at-risk populations; 2) the level and pattern of spatiotemporal environmental heterogeneity will also affect the ideal management approach; and 3) counter-intuitively, for at-risk species with endogenously governed boom-bust dynamics, lowering the intrinsic population growth rate may decrease extinction risk.

In 2023, the number of births in South Korea stood at 230,028, recording the lowest figure during the given period. Around two decades earlier, this number was twice as high. Declining fertility in South Korea A phenomenon that most East Asian countries and territories grapple with is a stark decline in fertility rates. This is especially evident in South Korea, which has the lowest fertility rate in the world, far below the 2.1 children per woman threshold that represents replacement fertility. In response to the expected economic consequences of a declining population, South Korea has implemented various initiatives to encourage married couples to have children. Factors contributing to low birth rates in South Korea One major element is the societal change in attitudes toward childbirth. In a survey, half of South Korean respondents asserted that marriages can be happy without children, and a sizeable share also stated that having children was dependent on economic factors. In addition, an increasing number of South Koreans are choosing not to get married – In 2023, South Korea recorded one of the lowest numbers of marriages in its history. Furthermore, there has been a growing trend among South Korean women to prioritize their financial independence and career continuity over traditional childbearing expectations.

While the standard image of the nuclear family with two parents and 2.5 children has persisted in the American imagination, the number of births in the U.S. has steadily been decreasing since 1990, with about 3.67 million babies born in 2022. In 1990, this figure was 4.16 million. Birth and replacement rates A country’s birth rate is defined as the number of live births per 1,000 inhabitants, and it is this particularly important number that has been decreasing over the past few decades. The declining birth rate is not solely an American problem, with EU member states showing comparable rates to the U.S. Additionally, each country has what is called a “replacement rate.” The replacement rate is the rate of fertility needed to keep a population stable when compared with the death rate. In the U.S., the fertility rate needed to keep the population stable is around 2.1 children per woman, but this figure was at 1.67 in 2022. Falling birth rates Currently, there is much discussion as to what exactly is causing the birth rate to decrease in the United States. There seem to be several factors in play, including longer life expectancies, financial concerns (such as the economic crisis of 2008), and an increased focus on careers, all of which are causing people to wait longer to start a family. How international governments will handle falling populations remains to be seen, but what is clear is that the declining birth rate is a multifaceted problem without an easy solution.

The working-age population can be divided into two broad categories: the early-working age group (15-34) and the later working age group (35-64). The effect of fertility on the composition of these groups is obvious. The later working age group is largely composed of the baby-boomers (those born between 1946 and 1965), while the early working age group is composed of those born during the baby-bust period (1966-1974) and the children of baby-boomers. Thus, despite the fact that baby-boomers are now older, they still remain the largest group in the population. This is evident in the relatively large proportion (42.6%) of the population that belonged to the late working age group in 2006. The corresponding proportion was much smaller (31.3%) just 25 years ago in 1981. As a result of the entry into the working age group of the people born during the baby-bust period and the children of baby-boomers in 2006, only 26.0% of the population belonged to the 15 to 34 age group in 2006, compared with 36.5% in 1981.

Raw and processed datasets

Over the history of humankind cultural innovations have helped improve survival and adaptation to environmental stress. This has led to an overall increase in human population size, which in turn further contributed to cumulative cultural learning. During the Anthropocene, or arguably even earlier, this positive socio-demographic feedback has caused a strong decline in important resources, that - coupled with projected future transgression of planetary boundaries - may potentially reverse the long-term trend in population growth. Here we present a simple consumer/resource model that captures the coupled dynamics of stochastic cultural learning and transmission, population growth, and resource depletion in a changing environment. The idealized stochastic mathematical model simulates boom/bust cycles between low-population subsistence, high density resource exploitation and subsequent population decline. For slow resource recovery timescales and in the absence of climate forcing, the model predicts a longterm global population collapse. Including a simplified periodic climate forcing, we find that cultural innovation and population growth can couple with the climatic forcing via nonlinear phase-synchronization. We discuss the relevance of this finding in the context of cultural innovation, the anthropological record and longterm future resilience of our own predatory species. Methods This dataset contains the Matlab code used to solve the ordinary differential equations (ODE) (1-3) of the paper "Phase synchronization between culture and climate forcing" in Proceedings of the Royal Society, B. The prognostic equation describe the dynamics of population density, resources/carrying capacity and culture, respectively. The Matlab code represents an Euler discretization of the stochastic ODEs and a Weibull-distributed noise distribution is assumed for the cultural innovation term. All images in the paper can be reproduced - at least in a statistical sense - by changing the parameters in the code by the parameters indicated in the figure caption of the manuscript.

Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long‐term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long‐term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long‐term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long‐term dynamics of body size. The long‐term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long‐term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.

The working-age population can be divided into two broad categories: the early-working age group (15-34) and the later working age group (35-64). The effect of fertility on the composition of these groups is obvious. The later working age group is largely composed of the baby-boomers (those born between 1946 and 1965), while the early working age group is composed of those born during the baby-bust period (1966-1974) and the children of baby-boomers. Thus, despite the fact that baby-boomers are now older, they still remain the largest group in the population. This is evident in the relatively large proportion (42.6%) of the population that belonged to the late working age group in 2006. The corresponding proportion was much smaller (31.3%) just 25 years ago in 1981. As a result of the entry into the working age group of the people born during the baby-bust period and the children of baby-boomers in 2006, only 26.0% of the population belonged to the 15 to 34 age group in 2006, compared with 36.5% in 1981.

Endogenous ModelNetlogo file containing code, user interface, and information tab describing this model and how to use it. This model simulates boom-bust dynamics of a butterfly species via endogenous consumer-resource density dependent dynamics.HimesBoor_EcAp_TCB_Endog.nlogoExogenous ModelNetlogo file containing code, user interface, and information tab describing this model and how to use it. This model simulates boom-bust dynamics of a butterfly species via exogenous dynamics including a population ceiling and environmental stochasticity.HimesBoor_EcAp_TCB_Exog.nlogoNumber of patches lookup tableLookup table read by Netlogo code.new-scenario-#patch-lookup4.txtDistance between patches lookup tableLookup table read by Netlogo code.new-scenario-dist-lookup.txtMap - Scenario 1.0Landscape map portraying restoration Scenario 1.0TCB_Scen1.0_map.txtTCB_Scen2.1b_mapLandscape map portraying restoration Scenario 2.1TCB_Scen2.2b_mapLandscape map portraying restoration Scenario 2.2TCB_Scen2.3b_ma...

In 2022, the crude birth rate in Saint Lucia remained nearly unchanged at around 11.32 live births per 1,000 inhabitants. But still, the rate reached its lowest value of the observation period in 2022. The crude birth rate is the annual number of live births divided by the total population, expressed per 1,000 people.Find more statistics on other topics about Saint Lucia with key insights such as total fertility rate, infant mortality rate, and death rate.

Human water use combined with a recent megadrought have reduced river and stream flow through the Southwestern United States and led to periodic drying of formerly perennial river segments. Reductions in snowmelt runoff and increased extent of drying collectively threaten short-lived, obligate aquatic species, including the endangered Rio Grande Silvery Minnow. This species experiences ‘boom-and-bust’ population dynamics where large fluctuations in abundance are expected to lower estimates of effective population size and erode genetic diversity over time. Rates of diversity loss are also affected by additions of hatchery-origin fish used to supplement the wild population. We leveraged demographic and genetic data from wild and hatchery individuals to understand the relationship of genetic diversity and effective population size to abundance over the last two decades. Genetic diversity was low during the early 2000s, but diversity and demographic metrics stabilized after the hatchery program was initiated and environmental conditions improved. Yet, from 2017 onward, allelic diversity declined (Cohen’s d=1.34) and remains low despite hatchery stocking and brief wild population recovery. Across the time series, single-sample estimates of effective population size (NeD) were positively associated (r=0.53) with wild/total abundance, but as the proportion of hatchery-origin spawners increased, NeD was reduced (NeD r= -0.55). Megadrought limits wild spawner abundance and precludes refreshment of hatchery brood stocks with wild fish, hence we predict an increasingly hatchery-dominated population, and accelerated loss of genetic diversity despite supplementation. We recommend an adaptive and accelerated management plan that integrates river flow management and hatchery operations to slow the pace of genetic diversity loss exacerbated by megadrought.

1. Jellyfish blooms are conspicuous demographic events with significant ecological and socio-economic impact. Despite worldwide concern about an increased frequency and intensity of such mass occurrences, predicting their booms and busts remains challenging.
2. Forecasting how jellyfish populations may respond to environmental change requires considering their complex life histories. Metagenic life cycles, which include a benthic polyp stage, can boost jellyfish mass occurrences via asexual recruitment of pelagic medusae.
3. Here we present stage-structured matrix population models with monthly, individual-based demographic rates of all life stages of the moon jellyfish Aurelia aurita L. (sensu stricto). We investigate the life stage-dynamics of these complex populations under low and high food conditions to illustrate how changes in medusa density depend on non-medusa stage dynamics.
4. We show that increased food availability can be an important ecological driver of jellyfish mass occurrences, as it can temporarily shift the population structure from polyp- to medusa- dominated. Projecting populations for a winter warming scenario enhanced the booms and busts of jellyfish blooms.
5. We identify demographic key variables that control the intensity and frequency of jellyfish blooms in response to environmental drivers such as habitat eutrophication and climate change. By contributing to an improved understanding of mass occurrence phenomena, our findings provide perspective for future management of ecosystem health.

In 1900, the total fertility rate of Peru was approximately 6.8 children per woman, meaning that women born in Peru at this time could expect to have just under seven children on average over the course of their reproductive years. Fertility gradually declined in Peru throughout the early 20th century, as modernization and declines in child mortality would continue in the country. However, Peru's fertility rate then gradually increased from the 1930s until the 1960s, due to a thriving economy and a series of populist policies implemented in this period, along with the global baby boom that followed the Second World War.

From the 1960s onwards, this trend would see a rapid reversal, as increased access to contraception, combined with an increasingly modernizing and urbanizing society, would lead to a sharp decline in fertility in the country. As a result, fertility would halve in just the last quarter of the 20th century alone, falling from six children per woman in 1975 to just three by 2000. This decline has continued steadily in recent decades, as Peru continues to undergo demographic shifts; as a result, the average woman born in Peru in 2020 can expect to have approximately 2.3 children over the course of her reproductive years, which is slightly above replacement level.

The fertility rate of a country is the average number of children that women from that country will have throughout their reproductive years. In Germany in 1800, the average woman of childbearing age would have 5.4 children over the course of their lifetime. It remained around this number until the late 1820s, when it then dropped to just under five, which was a long-term effect of the Napoleonic Period in Europe. From this point until the end of the nineteenth century, Germany's fertility rate was rather sporadic, reaching it's lowest point in 1855 with an average of 4.6 births per woman, and it's highest point in 1875 (just after the foundation of the German Empire in 1871), with an average of 5.4 live births per woman. From the beginning of the twentieth century until the end of the Second World War, Germany's fertility rate dropped from around 5 children per woman in 1900, to 1.9 in 1945. The only time where the fertility rate increased was in the inter-war years. Like other countries heavily involved in the Second World War, Germany (both East and West) experienced a Baby Boom from the late 1940s to the late 1960s, however it then dropped to it's lowest point of just 1.3 children per woman by 1995, shortly after the re-unification of Germany. In recent years, Germany's fertility rate has gradually been increasing again, and is expected to reach 1.6 in 2020, its highest rate in over forty years.

Jellyfish (pelagic Cnidarians and Ctenophores) form erratic and seemingly unpredictable blooms with often large, transient effects on ecosystem structure. To rapidly capitalize on favorable conditions, jellyfish can employ different life histories, which are either a life cycle with one annual sexual reproduction event and an overwintering benthic stage (metagenic life cycle), or continuous reproduction and a holoplanktonic life cycle. However, the links between life history, blooms, and environmental variability are unclear. Here, we examine how environmental variability can drive the bloom dynamics of typical jellyfish in coastal enclosed or semi-enclosed temperate ecosystems. With a simple community model, we reproduce typical seasonalities of the two strategies and trophic cascades triggered by abundant jellyfish, demonstrating how erratic blooms can be generated by irregular changes in the environment. Consistent with literature observations, we predict that metagenic jellyfish dominate early in the season, compared to holoplanktonic organisms, and are favored by increased seasonality. Our results reveal possible mechanisms driving coastal patterns of jellyfish blooms, and factors that are important for the outcome of competition between jellyfish with different life cycles. Such knowledge is important for our understanding of jellyfish blooms, which have large consequences for human activities and well-being, and may improve our ability to predict and manage local ecosystems.

Il est possible de diviser la population d’âge actif en deux groupes : les 15 à 34 ans et les 35 à 64 ans. L’effet de la fécondité sur la composition de ces groupes d’âge est évident. Le dernier groupe d’âge actif est largement composé de baby-boomers (personnes nées entre 1946 et 1965), alors que le premier compte la génération X, dite du « baby-bust » (personnes nées entre 1966 et 1974), ainsi que les enfants des baby-boomers. En dépit du fait que les baby-boomers sont maintenant plus âgés, ils demeurent le groupe démographique le plus important. Cette tendance ressort clairement dans la proportion relativement importante (42,6 %) de la population qui appartenait au dernier groupe d’âge actif en 2006. Cette proportion était beaucoup plus faible (31,3 %) il y a à peine 25 ans, en 1981. Malgré l’arrivée du groupe d’âge actif composé de personnes nées durant la période du « baby-bust », et des enfants des baby-boomers, la proportion des 15 à 34 ans ne représentait que 26,0 % de la population active en 2006, comparativement à 36,5 % en 1981.

In a country with the third-largest road network in the world, the total number of vehicles in fiscal year 2022 stood at 354 million. Road travel seemed to be the preferred choice in India with around 60 percent of the population who used personal or shared vehicles for commute. Not only public commute, the industrial movement of goods through roads has also been on the rise with nearly 2.9 billion metric tons per kilometer of freight transported through roads in the financial year 2020. Demographics The youth in the capital city of Delhi prefer to use public transport, and it is known to be one of the best public transport networks in the country. In the southern cities of Hyderabad and Chennai, however, personal two-wheelers were vehicles of choice for the young generation. This affection towards the easily navigable two-wheelers was reflected in the sales volume, with an approximate 18 million two-wheelers sold in the country in financial year 2024. Road accidents With the increase of motor bike sales in India, there was also a rise in the risks involved with them. With over 32.9 thousand road accidents by two-wheelers in 2022, each year, about three to five percent of the GDP of the country was invested in road accidents. Despite the downside, the number of motorcycles was likely to increase to make travelling within a mercilessly congested and not easily accessible network of roads within the large cities. Moreover, with continued urbanization and a consumer sector that continues to burgeon, the development of the automotive industry was expected to see continued growth.