BackgroundExtensive studies in different fields have been performed to reconstruct the prehistory of populations in the Japanese archipelago. Estimates the ancestral population dynamics based on Japanese molecular sequences can extend our understanding about the colonization of Japan and the ethnogenesis of modern Japanese. Methodology/Principal FindingsWe applied Bayesian skyline plot (BSP) with a dataset based on 952 Japanese mitochondrial DNA (mtDNA) genomes to depict the female effective population size (Nef) through time for the total Japanese and each of the major mtDNA haplogroups in Japanese. Our results revealed a rapid Nef growth since ∼5 thousand years ago had left ∼72% Japanese mtDNA lineages with a salient signature. The BSP for the major mtDNA haplogroups indicated some different demographic history. Conclusions/SignificanceThe results suggested that the rapid population expansion acted as a major force in shaping current maternal pool of Japanese. It supported a model for population dynamics in Japan in which the prehistoric population growth initiated in the Middle Jomon Period experienced a smooth and swift transition from Jomon to Yayoi, and then continued through the Yayoi Period. The confounding demographic backgrounds of different mtDNA haplogroups could also have some implications for some related studies in future.

This statistic shows the 20 countries with the highest population growth rate in 2024. In SouthSudan, the population grew by about 4.65 percent compared to the previous year, making it the country with the highest population growth rate in 2024. The global population Today, the global population amounts to around 7 billion people, i.e. the total number of living humans on Earth. More than half of the global population is living in Asia, while one quarter of the global population resides in Africa. High fertility rates in Africa and Asia, a decline in the mortality rates and an increase in the median age of the world population all contribute to the global population growth. Statistics show that the global population is subject to increase by almost 4 billion people by 2100. The global population growth is a direct result of people living longer because of better living conditions and a healthier nutrition. Three out of five of the most populous countries in the world are located in Asia. Ultimately the highest population growth rate is also found there, the country with the highest population growth rate is Syria. This could be due to a low infant mortality rate in Syria or the ever -expanding tourism sector.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 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 live 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 decade 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.

India population growth rate for 2023 was 0.88%, a 0.09% increase from 2022.

<ul style='margin-top:20px;'>

<li>India population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.03% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.82%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.97%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

According to latest figures, the Chinese population decreased by 1.39 million to around 1.408 billion people in 2024. After decades of rapid growth, China arrived at the turning point of its demographic development in 2022, which was earlier than expected. The annual population decrease is estimated to remain at moderate levels until around 2030 but to accelerate thereafter. Population development in China China had for a long time been the country with the largest population worldwide, but according to UN estimates, it has been overtaken by India in 2023. As the population in India is still growing, the country is very likely to remain being home of the largest population on earth in the near future. Due to several mechanisms put into place by the Chinese government as well as changing circumstances in the working and social environment of the Chinese people, population growth has subsided over the past decades, displaying an annual population growth rate of -0.1 percent in 2024. Nevertheless, compared to the world population in total, China held a share of about 17 percent of the overall global population in 2024. China's aging population In terms of demographic developments, the birth control efforts of the Chinese government had considerable effects on the demographic pyramid in China. Upon closer examination of the age distribution, a clear trend of an aging population becomes visible. In order to curb the negative effects of an aging population, the Chinese government abolished the one-child policy in 2015, which had been in effect since 1979, and introduced a three-child policy in May 2021. However, many Chinese parents nowadays are reluctant to have a second or third child, as is the case in most of the developed countries in the world. The number of births in China varied in the years following the abolishment of the one-child policy, but did not increase considerably. Among the reasons most prominent for parents not having more children are the rising living costs and costs for child care, growing work pressure, a growing trend towards self-realization and individualism, and changing social behaviors.

Human-induced environmental changes have a direct impact on species populations, with some species experiencing declines while others display population growth. Understanding why and how species populations respond differently to environmental changes is fundamental to mitigate and predict future biodiversity changes. Theoretically, species life-history strategies are key determinants shaping the response of populations to environmental impacts. Despite this, the association between species' life-histories and the response of populations to environmental changes has not been tested. In this study, we analysed the effects of recent land-cover and temperature changes on rates of population change of 1,072 populations recorded in the Living Planet Database. We selected populations with at least 5 yearly consecutive records (after imputation of missing population estimates) between 1992 and 2016, and for which we achieved high population imputation accuracy (in the cases where missing values had to be imputed). These populations were distributed across 553 different locations and included 461 terrestrial amniote vertebrate species (273 birds, 137 mammals, and 51 reptiles) with different life-history strategies. We showed that populations of fast-lived species inhabiting areas that have experienced recent expansion of cropland or bare soil present positive population trends on average, whereas slow-lived species display negative population trends. Although these findings support previous hypotheses that fast-lived species are better adapted to recover their populations after an environmental perturbation, the sensitivity analysis revealed that model outcomes are strongly influenced by the addition or exclusion of populations with extreme rates of change. Therefore, the results should be interpreted with caution. With climate and land-use changes likely to increase in the future, establishing clear links between species characteristics and responses to these threats is fundamental for designing and conducting conservation actions. The results of this study can aid in evaluating population sensitivity, assessing the likely conservation status of species with poor data coverage, and predicting future scenarios of biodiversity change.

Population growth models are integral to ecological studies by providing estimates of population performance across space and time. Several models have been developed that estimate population growth through correlates of demographic traits, as measuring each parameter of the model can be prohibitive in experimental studies. Since differences in female size can accurately reflect changes in fecundity for many taxa, Livdahl and Sugihara developed a population growth index that incorporates size-fecundity relationships as a proxy for fecundity. To investigate the extent to which this model is robust to variation of this proxy, we tested if genetic (source population), temperature and resource treatments affect the size-fecundity relationship in Aedes albopictus (Skuse), the Asian tiger mosquito. We then determined if variation in the size-fecundity relationship alters the population growth estimates, lambda (λ’), when applied to Livdahl and Sugihara’s model. We performed 2 laboratory experiments in which we reared cohorts of four different geographic populations of A. albopictus across 5 temperature treatments (18, 21, 25, 18, 31°C) and three resource treatments (low, medium, high larval resources). We determined if the slope of the size-fecundity relationship varied by source population, temperature, or resource; and if variation in this relationship affects lambda (λ’) estimates in a competition study between A. albopictus and Culex pipiens (Linnaeus), the northern house mosquito. Temperature treatments significantly affected the size-fecundity relationship, resource level marginally affected the relationship, while source population had no effect. We found positive relationships between size and fecundity when mosquito larvae were reared at high temperatures and low resource levels but the relationship disappeared when mosquitoes were reared at a low temperature or with high levels of resources. The variation in the size-fecundity relationship produced from different temperatures resulted in statistically different lambda (λ’) estimates. However, these changes in lambda (λ’) did not alter the trends in the population performance across treatments or conclusions of the competition study. This study provides evidence that the population growth model is sensitive to variation in size-fecundity relationships and we recommend biologists apply the most compatible size-fecundity relationship to the models to obtain the most accurate estimates of population performance.

Demographic processes that ensure the recovery and resilience of marine populations are critical as climate change sends an increasing proportion on a trajectory of decline. Yet for some populations, recovery potential remains high. We conducted annual monitoring over 9-years (2012–2020) to assess the recovery of coral populations belonging to genus Pocillopora. These populations experienced a catastrophic collapse following a severe typhoon in 2009. From the start of the monitoring period, high initial recruitment led to the establishment of a juvenile population that rapidly transitioned to sexually mature adults, which dominated the population within six years after the disturbance. As a result, coral cover increased from 1.1% to 20.2% during this time. To identify key demographic drivers of recovery and population growth rates (λ), we applied kernel resampled Integral Projection Models (IPMs), constructing eight successive models to examine annual change. IPMs were able to capture reproductive traits as key demographic drivers over the initial 3 years, whilst individual growth was a continuous key demographic driver throughout the entire monitoring period. IPMs further detected a pulse of reproductive output subsequent to two further Category 5 typhoon events during the monitoring period, exemplifying key mechanisms of resilience for coral populations impacted by disturbance. Despite rapid recovery, (i.e., increased coral cover, individual colony growth, low mortality), IPMs estimated predominantly negative values of λ, indicating a declining population. Indeed, whilst λ translates to a change in the number of individuals, the recovery of coral populations can also be driven by an increase in the size of coral surviving colonies. Our results illustrate that accumulating long-term data of historical dynamics and applying IPMs to extract demographic drivers are crucial for future predictions that are based on comprehensive and robust understandings of ecological change.

The annual population growth in the Philippines increased by 0.1 percentage points (+13.16 percent) in 2023 in comparison to the previous year. This was the first time during the observed period that the population growth has increased in the Philippines. Population growth refers to the annual change in population, and is based on the balance between birth and death rates, as well as migration.

1. Given their vulnerability to local extinction, the reintroduction of megafauna species (often long-lived, ecologically-influential and highly-social) is an increasingly relevant conservation intervention. Studies that evaluate past megafauna reintroductions are both critical and rare. 2. Between 1981 and 1996, 12 cohorts of a total of 200 juvenile (<5 years old) African savanna elephants (Loxodonta africana africana) were re-introduced to Hluhluwe-iMfolozi Park (HiP), South Africa, after 100 years of absence. Here we model the population's long term growth. We also present data on the current (2016) age class distribution and social dynamics of the population based on a year of intensive vehicle-based monitoring of 16 collared adult females and their family groups. 3. Exponential population growth (7.1% annual increase) between 1996 and 2014 suggests reintroduction success but has created concerns about overpopulation (with contraception implemented since 2014 to suppress reproduction). The age class distribution has normalised as the juveniles have aged; reproductive females (>10 years old) composed 30% of the population in 2016. The population remains relatively young and forecasts suggest high potential for sustained growth over the next decade. 4. The first calf was born to a reintroduced female in 1990 and since then mother-calf units have gradually developed into semi-independent multi-generation families (7-15 individuals in size in 2016). The size of observed cow-calf groups was highly variable (mean=21.4 individuals, range: 7-109), with repeat observation of individual collared females revealing fusion and fission among different family groups through time, as is typical of more natural elephant populations. 5. Synthesis and applications: The development of normal elephant demography and sociality from an irregular founder population may be an encouragement for the reintroduction of other megaherbivores. The potential for rapid population growth must however be carefully considered, especially when ecologically-influential species are introduced to closed systems. The observed age class distribution and the estimated potential for future growth over the next decade have implications for the park's contraception strategy. Finally, our study provides key long-term insights for elephant translocations, which are becoming an increasingly common and necessary management intervention (due to overpopulation in some areas and local extinction in others).04-Jun-2018

This layer shares SEDAC's population projections for U.S. counties for 2020-2100 in increments of 5 years, for each of five population projection scenarios known as Shared Socioeconomic Pathways (SSPs). This layer supports mapping, data visualizations, analysis and data exports.Before using this layer, read:The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview by Keywan Riahi, Detlef P. van Vuuren, Elmar Kriegler, Jae Edmonds, Brian C. O’Neill, Shinichiro Fujimori, Nico Bauer, Katherine Calvin, Rob Dellink, Oliver Fricko, Wolfgang Lutz, Alexander Popp, Jesus Crespo Cuaresma, Samir KC, Marian Leimbach, Leiwen Jiang, Tom Kram, Shilpa Rao, Johannes Emmerling, Kristie Ebi, Tomoko Hasegawa, Petr Havlik, Florian Humpenöder, Lara Aleluia Da Silva, Steve Smith, Elke Stehfest, Valentina Bosetti, Jiyong Eom, David Gernaat, Toshihiko Masui, Joeri Rogelj, Jessica Strefler, Laurent Drouet, Volker Krey, Gunnar Luderer, Mathijs Harmsen, Kiyoshi Takahashi, Lavinia Baumstark, Jonathan C. Doelman, Mikiko Kainuma, Zbigniew Klimont, Giacomo Marangoni, Hermann Lotze-Campen, Michael Obersteiner, Andrzej Tabeau, Massimo Tavoni. Global Environmental Change, Volume 42, 2017, Pages 153-168, ISSN 0959-3780, https://doi.org/10.1016/j.gloenvcha.2016.05.009.From the 2017 paper: "The SSPs are part of a new scenario framework, established by the climate change research community in order to facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation, and mitigation. The pathways were developed over the last years as a joint community effort and describe plausible major global developments that together would lead in the future to different challenges for mitigation and adaptation to climate change. The SSPs are based on five narratives describing alternative socio-economic developments, including sustainable development, regional rivalry, inequality, fossil-fueled development, and middle-of-the-road development. The long-term demographic and economic projections of the SSPs depict a wide uncertainty range consistent with the scenario literature."According to SEDAC, the purpose of this data is:"To provide subnational (county) population projection scenarios for the United States essential for understanding long-term demographic changes, planning for the future, and decision-making in a variety of applications."According to Francesco Bassetti of Foresight, "The SSP’s baseline worlds are useful because they allow us to see how different socioeconomic factors impact climate change. They include: a world of sustainability-focused growth and equality (SSP1); a “middle of the road” world where trends broadly follow their historical patterns (SSP2); a fragmented world of “resurgent nationalism” (SSP3); a world of ever-increasing inequality (SSP4);a world of rapid and unconstrained growth in economic output and energy use (SSP5).There are seven sublayers, each with county boundaries and an identical set of attribute fields containing projections for these seven groupings across the five SSPs and nine decades.Total PopulationBlack Non-Hispanic PopulationWhite Non-Hispanic PopulationOther Non-Hispanic PopulationHispanic PopulationMale PopulationFemale PopulationMethodology: Documentation for the Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, v1 (2020 – 2100)Data currency: This layer was created from a shapefile downloaded April 18, 2023 from SEDAC's Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, v1 (2020 – 2100)Enhancements found in this layer: Every field was given a field alias and field description created from SEDAC's Data Dictionary downloaded April 18, 2023. Citation: Hauer, M., and Center for International Earth Science Information Network - CIESIN - Columbia University. 2021. Georeferenced U.S. County-Level Population Projections, Total and by Sex, Race and Age, Based on the SSPs, 2020-2100. Palisades, New York: NASA Socioeconomic Data and Applications Center (SEDAC). https://doi.org/10.7927/dv72-s254. Accessed 18 April 2023.Hauer, M. E. 2019. Population Projections for U.S. Counties by Age, Sex, and Race Controlled to Shared Socioeconomic Pathway. Scientific Data 6: 190005. https://doi.org/10.1038/sdata.2019.5.Distribution Liability: CIESIN follows procedures designed to ensure that data disseminated by CIESIN are of reasonable quality. If, despite these procedures, users encounter apparent errors or misstatements in the data, they should contact SEDAC User Services at +1 845-465-8920 or via email at ciesin.info@ciesin.columbia.edu. Neither CIESIN nor NASA verifies or guarantees the accuracy, reliability, or completeness of any data provided. CIESIN provides this data without warranty of any kind whatsoever, either expressed or implied. CIESIN shall not be liable for incidental, consequential, or special damages arising out of the use of any data provided by CIESIN.

1. Density regulation of the population growth rate occurs through negative feedbacks on underlying vital rates, in response to increasing population size. Here, we examine in a capital breeder how vital rates of different life history stages, their elasticities, and population growth rates are affected by changes in population size. 2. We developed an integrated population model for a local population of Svalbard barnacle geese, Branta leucopsis, using counts, reproductive data and individual-based mark-recapture data (1990-2017) to model age class-specific survival, reproduction and number of individuals. Based on these estimates, we quantified the changes in demographic structure and the effect of population size on age class-specific vital rates and elasticities, as well as the population growth rate. 3. Local density regulation at the breeding grounds acted to reduce population growth through negative effects on reproduction; however, population size could not explain substantial variation in survival rates, although there was some support for density-dependent first year survival. 4. With the use of prospective perturbation analysis of the density-dependent projection matrix, we show that the elasticities to different vital rates changed as population size increased. As population size approached carrying capacity, the influence of reproductive rates and early life-survival on the population growth rate were reduced, whereas the influence of adult survival increased. A retrospective perturbation analysis revealed that density dependence resulted in a positive contribution of reproductive rates, and a negative contribution of the numbers of individuals in the adult age class, to the realised population growth rate. 5. The patterns of density dependence in this population of barnacle geese were different from those recorded in income breeding birds, where density regulation mainly occurs through an effect on early life survival. This indicates that the population dynamics of capital breeders, such as the barnacle goose, are likely to be more reproduction-driven than is the case for income breeders.

In 2023, the population of Africa was projected to grow by 2.34 percent compared to the previous year. The population growth rate on the continent has been constantly over 2.3 percent from 2000 onwards, and it peaked at 2.59 percent between 2012 and 2013. Despite a slowdown in the growth rate, the continent's population will continue to increase significantly in the coming years. The second-largest population worldwide In 2022, the total population of Africa amounted to around 1.4 billion. The number of inhabitants had grown steadily in the previous decades, rising from approximately 810 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 3.9 billion people, compared to 4.7 billion in Asia. The world's youngest continent The median age in Africa corresponded to 18.8 years in 2023. 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 10 percent. On the continent, Niger, Uganda, and Angola were the countries with the youngest population in 2023.

1. Reproductive asynchrony, a temporal mismatch in reproductive maturation between an individual and potential mates, may contribute to mate-finding failure and Allee effects that influence the establishment and spread of invasive species. Variation in elevation is likely to promote variability in maturation times for species with temperature-dependent development, but it is not known how strongly this influences reproductive asynchrony or the population growth of invasive species. 2. We examined whether spatial variation in reproductive asynchrony, due to differences in elevation and local heterogeneity in elevation (hilliness), can explain spatial heterogeneity in the population growth rate of the gypsy moth, Lymantria dispar (L.), along its invasion front in Virginia and West Virginia, USA. 3. We used a spatially explicit model of the effects of reproductive asynchrony on mating success to develop predictions of the influences of elevation and elevational heterogeneity on local population growth rates. Population growth rates declined with increased elevation and more modestly with increased elevational heterogeneity. As in earlier work, we found a positive relationship between the population growth rate and the number of introduced egg masses, indicating a demographic Allee effect. At high elevations and high heterogeneity in elevation, the population growth rate was lowest and the density at which the population tended to replace itself (i.e., the Allee threshold) was highest. 4. An analysis of 22 years of field data also showed decreases in population growth rates with elevation and heterogeneity in elevation that were largely consistent with the model predictions. 5. These results highlight how topographic characteristics can affect reproductive asynchrony and influence mate-finding Allee effects in an invading non-native insect population. Given the dependence of developmental rates on temperature in poikilotherms, topographic effects on reproductive success could potentially be important to the population dynamics of many organisms.

This project represents the data used in “Influences of potential oil and gas development and future climate on sage-grouse declines and redistribution.” The data sets describe greater sage-grouse (Centrocercus urophasianus) population change, summarized in different boundaries within the Wyoming Landscape Conservation Initiative (WLCI; southwestern Wyoming). Population changes were based on different scenarios of oil and gas development intensities, projected climate models, and initial sage-grouse population estimates. Description of data sets pertaining to this project: Greater sage-grouse population change (percent change) in a high oil and gas development, low population estimate scenario, and with and without effects of climate change. 1. Greater sage-grouse population change (percent change) over 50-years in a high oil and gas development, low population estimate scenario, and with effects of climate change under an RCP 8.5 scenario (2050) 2. Greater sage-grouse population change (percent change) in a low oil and gas development, high population estimate scenario, and with no effects of climate change (2006-2062) 3. Greater sage-grouse population change (percent change) over 50-years in a low oil and gas development, low population estimate scenario, and with effects of climate change under an RCP 8.5 scenario (2050) 4. Greater sage-grouse population change (percent change) in a moderate oil and gas development, high population estimate scenario, and with no effects of climate change (2006-2062) 5. Greater sage-grouse population change (percent change) in a high oil and gas development, low population estimate scenario, and with no effects of climate change (2006-2062) The oil and gas development scenario were based on an energy footprint model that simulates well, pad, and road patterns for oil and gas recovery options that vary in well types (vertical and directional) and number of wells per pad and use simulation results to quantify physical and wildlife-habitat impacts. I applied the model to assess tradeoffs among 10 conventional and directional-drilling scenarios in a natural gas field in southwestern Wyoming (see Garman 2017). The effects climate change on sagebrush were developed using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM, version 4) climate model and representative concentration pathway 8.5 scenario (emissions continue to rise throughout the 21st century). The projected climate scenario was used to estimate the change in percent cover of sagebrush (see Homer et al. 2015). The percent changes in sage-grouse population sizes represented in these data are modeled using an individual-based population model that simulates dynamics of populations by tracking movements of individuals in dynamically changing landscapes, as well as the fates of individuals as influenced by spatially heterogeneous demography. We developed a case study to assess how spatially explicit individual based modeling could be used to evaluate future population outcomes of gradual landscape change from multiple stressors. For Greater sage-grouse in southwest Wyoming, we projected oil and gas development footprints and climate-induced vegetation changes fifty years into the future. Using a time-series of planned oil and gas development and predicted climate-induced changes in vegetation, we re-calculated habitat selection maps to dynamically modify future habitat quantity, quality, and configuration. We simulated long-term sage-grouse responses to habitat change by allowing individuals to adjust to shifts in habitat availability and quality. The use of spatially explicit individual-based modeling offered an important means of evaluating delayed indirect impacts of landscape change on wildlife population outcomes. This process and the outcomes on sage-grouse population changes are reflected in this data set.

Objectives: The theory of ecological unequal exchange explains how trade and various forms of economic activity create the problem of environmental degradation, and lead to the deterioration of population health. Based on this theory, our study examined the inter-relationship among economic characteristics, ecological footprints, CO2 emissions, infant mortality rates and under-5 mortality rates in low-income countries. Design: A longitudinal ecological study design. Setting: Sixty-six low-income countries from 1980 to 2010 were included in the analyses. Data for each country represented an average of 23 years (N=1497). Data sources: Data were from the World Development Indicators, UN Commodity Trade Statistics Database, Global Footprint Network and Polity IV Project. Analyses: Linear mixed models with a spatial power covariance structure and a correlation that decreased over time were constructed to accommodate the repeated measures. Statistical analyses were conducted separately by sub-Saharan Africa, Latin America and other regions. Results: After controlling for country-level sociodemographic characteristics, debt and manufacturing, economic activities were positively associated with infant mortality rates and under-5 mortality rates in sub-Saharan Africa. By contrast, export intensity and foreign investment were beneficial for reducing infant and under-5 mortality rates in Latin America and other regions. Although the ecological footprints and CO2 emissions did not mediate the relationship between economic characteristics and health outcomes, export intensity increased CO2 emissions, but reduced the ecological footprints in sub-Saharan Africa. By contrast, in Asia, the Middle East and North Africa, although export intensity was positively associated with the ecological footprints and also CO2 emissions, the percentage of exports to high-income countries was negatively associated with the ecological footprints. Conclusions: This study suggested that environmental protection and economic development are important for reducing infant and under-5 mortality rates in low-income countries.

Demographic data for introduced crab from multiple bays along the Central California coast, shallow subtidal (<3 m depth), in 2015. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description=We conducted monthly trappings of invasive European green crabs to gather demographic data from several bays in northern California: Bodega Harbor, Tomales Bay, Bolinas Lagoon, San Francisco Bay, and Elkhorn Slough. All sites were accessed by foot via shore entry. At each of four sites within each bay, we placed 5 baited traps (folding Fukui fish traps) and 5 baited minnow traps in shallow intertidal areas. Traps arrays were set with fish and minnow traps alternating and with each 20 m apart. Traps were retrieved 24 hours later and traps were rebaited and collected again the following day.\u00a0Trapping was continued for three consecutive days with traps removed on the final day.\u00a0Each day, data for crab species, size, sex, reproductive condition, and injuries were collected for all crabs in the field. Following data collection, all crabs were returned to the lab, and frozen overnight prior to disposal.\u00a0

See Turner et al. (2016)\u00a0Biological Invasions\u00a018: 533-548 for additional methodological details:
Turner, B.C., de Rivera, C.E., Grosholz, E.D., & Ruiz, G.M. 2016. Assessing population increase as a possible outcome to management of invasive species. Biological Invasions, 18(2), pp 533\u2013548. doi:10.1007/s10530-015-1026-9 awards_0_award_nid=699764 awards_0_award_number=OCE-1514893 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1514893 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 cdm_data_type=Other comment=Demographic data for introduced crab from multiple bays in 2015 PI: Edwin Grosholz (UC Davis) Co-PI: Catherine de Rivera & Gregory Ruiz (Portland State University)
Version: 15 June 2017 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.701751.1 Easternmost_Easting=-121.738422 geospatial_lat_max=38.316968 geospatial_lat_min=36.823953 geospatial_lat_units=degrees_north geospatial_lon_max=-121.738422 geospatial_lon_min=-123.058725 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/701751 institution=BCO-DMO instruments_0_dataset_instrument_description=At each of four sites within each bay, we placed 5 baited traps (folding Fukui fish traps) and 5 baited minnow traps in shallow intertidal areas. instruments_0_dataset_instrument_nid=701774 instruments_0_description=Fukui produces multi-species, multi-purpose collapsible or stackable fish traps, available in different sizes. instruments_0_instrument_name=Fukui fish trap instruments_0_instrument_nid=701772 instruments_0_supplied_name=folding Fukui fish traps metadata_source=https://www.bco-dmo.org/api/dataset/701751 Northernmost_Northing=38.316968 param_mapping={'701751': {'lat': 'master - latitude', 'lon': 'master - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/701751/parameters people_0_affiliation=University of California-Davis people_0_affiliation_acronym=UC Davis people_0_person_name=Edwin Grosholz people_0_person_nid=699768 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Portland State University people_1_affiliation_acronym=PSU people_1_person_name=Catherine de Rivera people_1_person_nid=699771 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=Portland State University people_2_affiliation_acronym=PSU people_2_person_name=Gregory Ruiz people_2_person_nid=471603 people_2_role=Co-Principal Investigator people_2_role_type=originator people_3_affiliation=Woods Hole Oceanographic Institution people_3_affiliation_acronym=WHOI BCO-DMO people_3_person_name=Shannon Rauch people_3_person_nid=51498 people_3_role=BCO-DMO Data Manager people_3_role_type=related project=Invasive_predator_harvest projects_0_acronym=Invasive_predator_harvest projects_0_description=The usual expectation is that when populations of plants and animals experience repeated losses to predators or human harvest, they would decline over time. If instead these populations rebound to numbers exceeding their initial levels, this would seem counter-intuitive or even paradoxical. However, for several decades mathematical models of population processes have shown that this unexpected response, formally known as overcompensation, is not only possible, but even expected under some circumstances. In what may be the first example of overcompensation in a marine system, a dramatic increase in a population of the non-native European green crab was recently observed following an intensive removal program. This RAPID project will use field surveys and laboratory experiments to verify that this population explosion results from overcompensation. Data will be fed into population models to understand to what degree populations processes such as cannibalism by adult crabs on juvenile crabs and changes in maturity rate of reproductive females are contributing to or modifying overcompensation. The work will provide important insights into the fundamental population dynamics that can produce overcompensation in both natural and managed populations. Broader Impacts include mentoring graduate trainees and undergraduate interns in the design and execution of field experiments as well as in laboratory culture and feeding experiments. The project will also involve a network of citizen scientists who are involved with restoration activities in this region and results will be posted on the European Green Crab Project website. This project aims to establish the first example of overcompensation in marine systems. Overcompensation refers to the paradoxical process where reduction of a population due to natural or human causes results in a greater equilibrium population than before the reduction. A population explosion of green crabs has been recently documented in a coastal lagoon and there are strong indications that this may be the result of overcompensation. Accelerated maturation of females, which can accompany and modify the expression of overcompensation has been observed. This RAPID project will collect field data from this unusual recruitment class and conduct targeted mesocosm experiments. These will include population surveys and mark-recapture studies to measure demographic rates across study sites. Laboratory mesocosm studies using this recruitment class will determine size specific mortality. Outcomes will be used in population dynamics models to determine to what degree overcompensation has created this dramatic population increase. The project will seek answers to the following questions: 1) what are the rates of cannibalism by adult green crabs and large juveniles on different sizes of juvenile green crabs, 2) what are the consequences of smaller size at first reproduction for population dynamics and for overcompensation and 3) how quickly will the green crab population return to the levels observed prior to the eradication program five years earlier? projects_0_end_date=2016-11 projects_0_geolocation=Europe projects_0_name=RAPID: A rare opportunity to examine overcompensation resulting from intensive harvest of an introduced predator projects_0_project_nid=699765 projects_0_start_date=2014-12 sourceUrl=(local files) Southernmost_Northing=36.823953 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-123.058725 xml_source=osprey2erddap.update_xml() v1.3

This project aims to study the impacts of e-commerce on shopping behaviors and related externalities. The objectives are divided into five major tasks in this project. Methods used include Weighted Multinomial Logit (WMNL) models, time series forecasting, and Monte Carlo (MC) simulations. The American Time Use Survey (ATUS) and the National Household Travel Survey (NHTS) databases are used for identifying the independent and dependent variables for behavioral modeling. At the same time, we collected all MSA population data from the U.S. Census Bureau and combined the shares of each variable from ATUS to generate a synthesized population, which serves as input into the MC simulation framework together with the behavioral model. This simulation framework includes the generation of shopping travel parameters and the calculation of negative externalities. We do this to estimate e-commerce demand and impacts every decade until 2050. The results and analyses provide information that supports the generation of shopping travel and the estimations of a series of negative externalities using MC simulation, which includes shopping travel parameters, last-mile delivery parameters, and emission rate per person. For different parameters, a unique probability distribution or a regression relation is obtained for different MSAs, and this distribution is fed into the subsequent MC simulation. Finally, we simulated shopping behaviors for synthesized populations (until 2050) and estimated the expected negative externalities. The MC simulation generates aggregate average vehicle miles traveled (VMT) and emissions (negative externalities) for different shopping activities in the planning years and different MSAs. Methods The tasks of this project employ different combinations of methods to enable the prediction of e-commerce shopping behaviors for each MSA of interest at the individual level as well as the quantitative calculation of externalities. Methods used include Weighted Multinomial Logit (WMNL) models, time series forecasting, and Monte Carlo (MC) simulations, which are utilized throughout Task 1 to Task 5. In Task 1, we mainly build and validate the WMNL behavior models for different MSAs with specific sets of model coefficients that can be used to predict shopping behavior for a synthesized population. In the WMNL mode, the dependent variable with totally four categories, namely “No shopping”, “In-store shopping”, “Online shopping” and “Both shopping”. The results of the WMNL models vary across MSAs, as reflected by the fact that different coefficients of variables are positive in some MSAs and negative in others. In general, however, female, high education, low to moderate age group, and not in labor market are the positive influences that make the respondents choose the online and/or both shopping. Four different population growth scenarios are specified with the combinations of high/moderate IV market share time series prediction and projected population. Also, the models are validated by the synthesized populations for the planning years, resulting in around 2% in the errors of dependent variable market share predictions. Tasks 2, 3 and 4 provide information that supports the generation of shopping travels and the calculation of a series of negative externalities in Task 5 using Monte Carlo simulation, which is shopping travel parameters, last-mile delivery parameters and emission rate per person, respectively. For different parameters, a unique probability distribution or a regression relation is obtained for different MSAs, and this distribution is fed into the subsequent MC simulation. Finally, Task 5 is performed to serve the goal of the project: to simulate shopping behaviors for a synthesized population and to calculate related negative externalities. The MC simulation process is finalized by utilizing the results from Task 1 to 4, where the outputs of this part are the aggregate average VMT and emissions (negative externalities) for different shopping activities in the planning years and different MSA. This aggregate simulation results mainly come from calculations of VMT and emissions of the datasets of synthesized populations for different planning years and population growth scenarios.

1. Economic activities such as logging and mineral extraction can result in the creation of new anthropogenic habitats that host specific biodiversity, including protected species. However, the legislation in many Western European countries requires the rehabilitation of ‘damaged’ areas following logging and mining operations, which can eliminate these early successional habitats. Conservation managers face a dilemma in these situations, but often lack knowledge about the impacts of environmental rehabilitation on the population dynamics of pioneer species and so are unable to take this into account in their actions. 2. We investigated the demography of a spatially structured population of an endangered amphibian (Bombina variegata) that uses waterbodies created by logging activities as breeding sites. Using capture–recapture (CR) data collected during a 9-year study period, we examined how the destruction of breeding patches due to environmental rehabilitation affected adult survival and the long-term population growth rate. For this purpose, we used recently developed capture-recapture multievent models to estimate survival and dispersal rates in the spatially structured population. We then used these estimates to simulate population trajectories and viability depending on differing frequency of breeding patch destruction. 3. The multievent models revealed that dispersal not resulting from patch loss was relatively high and was sex-biased. They also revealed that patch destruction had a negative impact on adult survival. Moreover, simulations showed that the increase of patch destruction frequency had a strong negative influence on the population growth rate, even when the number of patch remained constant over time. This impact was intensified if female fecundity was also affected. 4. Synthesis and applications. Our study quantified for the first time the detrimental effect of habitat rehabilitation on the population dynamics of an endangered, pioneer species. Yet our study also found that this deleterious impact of patch destruction could be reduced by certain management practices, as avoiding the systematic rehabilitation of the breeding patches and compensating for patch destruction by creating substitute breeding patches. Capture-recapture dataData description The capture-recapture data used in Cayuela et al. (2018, J. Appl. Ecol) were collected in a spatially structured population of Bombina variegata in France, over an 9-years period (2000-2008). Several capture sessions were performed per year (detailed in Supplementary material S1 of the paper). The individuals are in raws and the capture occasion on column (labelled “H:”). The column “S:” specifies the end of the capture history. The column labeled “$COV:sex” is the sex coded as a group effect (1 = male, 2 = female). The capture-recapture histories are coded with the following events. For an individual captured at t and t–1, we attributed a code of 1 if it had not dispersed and occupied a patch destroyed at t+1 or a code of 4 if the patch was still available; we attributed a code of 2 if an individual had dispersed and occupied a patch destroyed at t+1 or a code of 5 if the patch was still available. For an individual not captured at t–1 but captured at t, a code of 3 or 6 was attributed respectively if it occurred in a patch destroyed at t+1 or not. An individual was coded 0 if it was not captured at t. The txt file is compatible with E-SURGE program. Code to enter in the GEMACO in E-SURGE program to run the most general model. For Initial State: IS - Step 1 - (1): to For Transition: Survival - Step 1 - (5): from(1:6, 7:12).t(6 10 14 19 20 23 26).g+[t(6 10 14 19 20 23 26)+t(1 2 3 4 5 7 8 9 11 12 13 15 16 17 18 21 22 24 25 27 28)] For Transition: Dispersal - Step 2 - (5): from(1:3, 4:6).t(1 2 3 4 5 7 8 9 11 12 13 15 16 17 18 21 22 24 25 27 28, 6 10 14 19 20 23 26)+g For Transition: Site dynamics - Step 3 - (8): t(1 2 3 4 5 7 8 9 11 12 13 15 16 17 18 21 22 24 25 27 28, 6, 10, 14, 19, 20, 23, 26) For Transition: Recapture - Step 4 - (11): from(1:6, 7:12)+t(1 2 3 4 5 6, 7 8 9 10, 11 12 13 14, 15 16 17 18, 19, 20, 21 22 23, 24 25 26, 27 28 29)+g For Event: Events - Step 1 - (0): firste+nextedata_adult.txt

1. Increased anthropogenic influence on the environment has accentuated the need to assess how climate and other environmental factors drive vital rates and population dynamics of different types of organisms. However, to allow distinction between effects of multiple correlated variables, and to capture the effects of rare and extreme climatic conditions, studies extending over decades are often necessary.

2. In this study we used an individual-based dataset collected in three populations of Pulsatilla vulgaris subsp. gotlandica during 34 years, to explore the effects of variation in precipitation and temperature on vital rates and population dynamics.

3. Most of the observed conspicuous variation in flowering among years was associated with differences in precipitation and temperature in the previous summer and autumn with a higher incidence of flowering following summers with high precipitation and low temperatures. In contrast, climatic variables had no significant effects on individual growth or survival.

4. Although the weather-driven variation in flowering had only moderate absolute effects on the population growth rate, simulated persistent changes in average precipitation and temperature resulted in considerable reductions in population sizes compared with current conditions. Analyses carried out with with subsets of data consisting of 5 and 10 years yielded results that strongly deviated from those based on the full data set.

5. Synthesis: The results of this study illustrate the importance of long-term demographic monitoring to identify key climatic variables affecting vital rates and driving population dynamics in long-lived organisms.