Assessing the impacts of changing environmental conditions on animal species requires thorough understanding of population dynamics, which can be difficult to estimate when animals aggregate into spatially discrete subpopulations. We used 39 years of fecundity, capture-recapture and abundance data in an integrated metapopulation model to study environmental drivers of demography in a declining migratory bird, the Greenland white-fronted goose (Anser albifrons flavirostris). We found that low fecundity due to earlier spring vegetation phenology on staging areas and increased snow on breeding areas explained metapopulation decline, though the strength of these effects varied by subpopulation. Differential immigration and emigration rates affected local wintering abundance trends, highlighting the importance of quantifying subpopulation-metapopulation dynamics for understanding fragmented animal populations. We provide a framework for extending commonly used integrated population models to a metapopulation framework for testing novel ecological hypotheses about how changing environmental conditions within and among subpopulations drive changes in animal abundance.

Children on the move in the ECOWAS subregion are part of historical mobility networks shaped by structural poverty, inadequate services, and inequalities. Using the Structural Violence Theory framework, the review examines how economic, social service, and governance policies interact to both create the demand for migration and increase the risks faced by children on the move. The review has three research objectives. Systematic literature review guided by PRISMA. There was an overwhelming response of relevant literature sources. Literature from 1966 to 2025 on child migration, trafficking, displacement, and protection by ECOWAS was collected. Among the 987 sources identified through a literature search of central academic databases and institutional repositories, 56 met the selection criteria. Qualitative analysis was employed to evaluate the robustness of the sources based on their methods. Findings indicate rising levels of children on the move, driven by independent migration from rural areas to cities and cross-border migration along traditional migration routes. Factors such as economic hardship, limited access to quality education, conflict, gender-related labor market conditions, and family dynamics are interconnected and play crucial roles. Children on the move are increasingly vulnerable to exploitation, labor dangers, trafficking, and social exclusion. While international, regional, and national frameworks set standards legally, their implementation remains inefficient. Children on the move within ECOWAS are seen as an inevitable result of structural factors rather than isolated incidents. One policy implication of this analysis is to include children on the move within the ECOWAS mobility framework. Additionally, social protection programs for children need to be expanded in countries with high emigration rates. Nurses and allied frontline providers are well-positioned to identify mobility-related risks, deliver trauma-informed, non-discriminatory care, document safeguarding concerns, and activate referral pathways for child protection, psychosocial support, and legal assistance.

Context Understanding the biological and environmental processes that regulate populations is a central goal of ecology and is fundamental to fisheries management. Aims This study aims to quantify the environmental and biological factors influencing barramundi (Lates calcarifer) recruitment dynamics in Corroboree Billabong, a seasonally isolated reach of the Mary River, located in the wet–dry tropics of northern Australia. Methods Depletion sampling was conducted annually by using gillnets, and the age of sampled individuals was estimated, providing age-specific abundance estimates across a 20-year period. To explore the biotic (e.g. density dependence) and abiotic (e.g. rainfall) drivers of recruitment and size-at-age, a Piecewise Structural Equation Model was developed. Key results Young-of-year recruitment was negatively correlated with 1-year-old abundance, and size-at-age was negatively correlated with cohort strength, suggesting that cannibalism and intraspecific competition are important determinants of recruitment and juvenile growth rates respectively. Wetter years were associated with stronger recruitment, and higher rates of emigration by 1-year olds. Conclusions Our results provided new insights into river–floodplain fish recruitment dynamics showing that both density-dependent and abiotic drivers can affect recruitment dynamics. Implications Incorporating both abiotic and biotic drivers may improve the predictive capacity of population and stock assessment models to underpin sustainable management of this valuable and iconic species.

Studies on South Korea’s population have primarily relied on aggregate data or focused exclusively on urban areas. However, rural population dynamics differ significantly from national trends, making it challenging to apply national population projections directly to rural and agricultural populations. This study estimates the in-migration and out-migration rates of rural areas using municipality-level statistical data from 2012 to 2022 and forecasts regional net migration rates. The population is categorized by gender and age group, and in-migration and out-migration rates are estimated for each cohort. Given that regional migration rates are non-negative, the Tobit model is employed for the estimation. The analysis reveals heterogeneity in migration behaviors across different demographic groups. In particular, young adults in their twenties exhibit the highest out-migration rates, mainly due to limited access to higher education and employment opportunities in rural areas. In contrast, for individuals in their thirties and early forties, the availability of childcare and family-supportive environments plays a significant role in migration decisions. These findings highlight the need for differentiated policy strategies tailored to the specific needs of each age group. This study enhances understanding of rural population dynamics and provides evidence to inform the formulation of regional revitalization policies.

The persistence of large carnivores in human-dominated landscapes is particularly sensitive to the impact of humans on key demographic parameters, such as survival, which is strongly influenced by legal and illegal killing. However, estimating demographic parameters is challenging, requiring remarkable logistical and economic efforts. We developed a Bayesian integrated population model for wolves persisting in a human-dominated landscape at the edge of their European range. We incorporated multiple long-term datasets (2007–2019) of population counts, fecundity, molecular individual identification, and dead recoveries of GPS-collared wolves. With the IPM, we estimated population size and structure, growth rate, survival and emigration rates, the latter two being largely unknown parameters for wolves persisting in these landscapes. We estimated a growth rate of 1.04 (95%BCI: 1.03–1.05). Estimated survival rates were 0.72 (95%BCI: 0.66–0.77) for adults and 0.53 (95%BCI: 0.30–0.71) for pups, and the emigration rate was 0.13 (95%BCI: 0.06–0.21). The low emigration rates estimated may contribute to explaining the cryptic population structure documented in the Iberian wolf population. By forecasting population growth over a ten-year period (2020–2029) under different fecundity and survival rate scenarios, we identified adult survival as a key factor influencing wolf persistence in human-dominated landscapes. Conflicts around wolf depredation on livestock, which may boost retaliatory killing and public pressure to reduce wolf populations, together with other anthropogenic mortality causes and the impacts of infrastructure development, can reduce wolf survival rates to an unknown extent and, therefore, jeopardize wolf recovery. • Integrated Population Model applied to wolves in human-dominated landscapes • Survival rates were estimated at 0.72 for adults and 0.53 for pups • Adult survival is a key factor for wolf persistence in anthropogenic landscapes • A low emigration rate of 0.13 is consistent with the cryptic population structure • Apparent survival rate of 0.62 was lower than in other anthropogenic landscapes

Existing models of country-level net migration ignore the effect of population age distribution on past and projected migration rates. We propose a method to estimate and forecast international net migration rates for the 200 most populous countries, taking account of changes in population age structure. We use age-standardized estimates of country-level net migration rates and in-migration (i.e., immigration) rates over five-year periods from 1990 through 2020 to decompose past net migration rates into in-migration rates and out-migration (i.e., emigration) rates. We then recalculate historic migration rates on a scale that removes the influence of the population age distribution. This is done by scaling past and projected migration rates in terms of a reference population and period using a quantity we call the migration age structure index (MASI). We use a Bayesian hierarchical model to generate joint probabilistic forecasts of net migration rates over five-year periods for all countries through 2100. We find that accounting for population age structure in historic and forecast net migration rates leads to narrower prediction intervals by the end of the century for most countries. Furthermore, accounting for population age structure leads to less out-migration among countries with rapidly aging populations that are forecast to contract most rapidly by the end of the century. This approach leads to less drastic population declines than are forecast without accounting for population age structure.

Few studies examine how slow-onset climate change interacts with local structural conditions to shape internal migration and long-term community sustainability. Using 2021 county-to-county migration data for the contiguous United States, this study analyzes spatial variation in in-migration, out-migration, and net migration rates in relation to temperature anomalies and place-based socioeconomic characteristics. Spatial regression results reveal no uniform relationship between recent temperature anomalies and migration outcomes. Instead, migration patterns are more strongly associated with urban status, housing market conditions, population composition, and long-run average climate. In some counties, higher temperature anomalies are associated with reduced out-migration, suggesting constrained mobility where economic and housing conditions limit relocation options. By contrast, extreme anomalies and greater environmental vulnerability are linked to lower in-migration, indicating diminished destination attractiveness. Overall, the findings suggest that internal migration responses to climate stress are mediated by local structural conditions rather than driven by temperature change alone, underscoring the importance of equitable adaption policies and place-based resilience strategies for sustainable regional development.

The usage patterns of healthcare services differ significantly between the native and migrant populations. Using the administrative health database of the Lombardy Region, we compared the hospitalization rates of natives and migrants from 2010 to 2019. Migrants were categorized into two groups: those from countries with high emigration rates (HMPC) and those from other countries (HDC). Standardized hospitalization rates decreased between 2010 and 2019 for both men and women across all groups (Italians, HMPC migrants, and HDC migrants). Women exhibited higher hospitalization rates compared to men due to childbirth and pregnancy-related complications. Among women, HMPC migrants had the highest standardized hospitalization rates throughout the study period, though the gap with natives has recently narrowed. Among men, HMPC migrants had the lowest standardized hospitalization rates, with the disparity between natives and migrants remaining consistent over time. Poisson and negative binomial regression models were used to analyse the crude hospitalization rate as the dependent variable to highlight the differences among geographic groups and sex across years. Age plays a key role, with younger women and those under childbearing age showing lower hospitalization rates. Additionally, we calculated crude and standardised rates for avoidable hospitalization and access to the Emergency Department.

ABSTRACTA major challenge in dispersal ecology consists of testing whether distinct sets of phenotypic traits are associated with the three main phases of dispersal, requiring direct observations of disperser movements during emigration, transience, and immigration. Although freshwater ciliates have been used as a model in artificial dispersal landscapes for over 15 years, most studies would relate dispersal propensity to phenotypic traits measured at the end of dispersal assays. Using ‘two‐dimensional’ fragmented microcosms, abundance, movement and morphology data of Tetrahymena thermophila were collected at numerous time points throughout 6.5 h‐long dispersal assays. Data were compared across distinct zones (‘Start’ and ‘Target’ patches, connected by a ‘Corridor’) to identify shifts in the mean value and distribution of dispersal‐related traits. Inference on the existence of dispersal decisions was obtained by comparing these results to similar outputs generated by a ‘null’ movement model (without decision rules). Five genotypes were used, among which two strategies were identified: swimming speed and linearity either increased (‘hump’) or decreased (‘slope’) during transience, while both traits generally decreased at immigration. Doubling the length of corridors (10 mm vs. 20 mm) modified dispersal timing, but did not affect emigration rates. Simulated data predicted a shift towards increased velocity at immigration; however, the opposite was found in most strains, suggesting a plastic inducement of typical foraging movements after settling in the ‘Target’ patch. Since a ‘snapshot’ approach was used (capturing sparse movement sequences throughout the dispersal process instead of prolonged tracking), phenotypic plasticity could not be confirmed with certainty; however, the hypothesis of strict spatial sorting was insufficient to explain movement patterns. Overall, our results hint at the plastic and reversible nature of dispersal syndromes displayed by T. thermophila across fragmented landscapes, which bears significance in the context of habitat loss and the maintenance of metapopulation stability.

Capture-recapture is a well-established sampling technique used to estimate population size and related demographic parameters such as birth, mortality, immigration, and emigration rates. Traditional methods rely on a fixed-size recapture sample. In this work, we propose a sequential capture-recapture method where individuals are sampled one by one until a fixed number of previously marked individuals is observed. We derive an unbiased estimator of the population size and establish its variance analytically. A stability-based stopping rule is also introduced to optimize the sampling effort while preserving estimation accuracy. Simulation results demonstrate that the proposed estimator outperforms classical estimators in terms of efficiency and stability. Approximate confidence intervals are also derived and empirically shown to achieve near-nominal coverage probabilities.

We analyze the structure of positive solutions to a class of steady state equations arising in modeling a prey population that grows logistically, experiences Holling Type III predation from a generalist predator, and exhibits an overall negative relationship between density and emigration rate (-DDE). In particular, the predator is assumed to operate on a different time scale than the prey and, thus, its density is held constant. Under some general hypotheses on the reaction term and boundary nonlinearity, we establish existence, nonexistence, and multiplicity results for certain ranges of a parameter which is proportional to patch size squared via the method of sub-super-solutions. In particular, we establish that the bifurcation curve of positive solutions for the steady state equation is at least $ \Sigma $-shaped. In this case, there is a range of patch size where a patch-level Allee effect occurs, i.e., a situation where the trivial solution and at least one other positive steady state are stable arises for small patch sizes, and a non-Allee effect type bi-stability arises for a range of larger patch sizes. As an application of our result, we consider the case when $ \Omega $ is a ball, the reaction term is exactly logistic growth with a Type III functional response and the boundary nonlinearity is a -DDE form with a fast decay rate and show that the hypotheses in our theorems are satisfied. Further, when $ \Omega = (0, 1), $ we employ quadrature methods and computations using Wolfram Mathematica to show that the bifurcation diagram for positive solutions of this example is exactly $ \Sigma $-shaped for certain values of the parameters. The occurrence of multiple steady states in real-world metapopulations can influence the fraction and distribution of occupied patches and cause uncertainty in predicting minimum patch size and density-area relationships.

The article is devoted to the study of in-working poverty in the Republic of Moldova, which is also one of the reasons for mass emigration from the country. The study analyzes a multifaceted array of factors contributing to the persistent spread of poverty among those who are actively engaged in the workforce. These factors include: persistently low minimum wages that fail to meet the basic needs of the population; severely limited opportunities for skills upgrading and professional development, particularly in the often-overlooked rural areas; the widespread prevalence of informal employment, characterized by a lack of legal protections and social security benefits; insufficient wages offered in crucial economic sectors, such as agriculture, the backbone of the Moldovan economy, and the expanding service sector. Furthermore, the analysis highlights the significant wage gap that exists between highly skilled and lower-skilled labor, creating a system where upward mobility is challenging to achieve. Part-time or unstable employment patterns, often characterized by precarious working conditions, exacerbate the financial insecurity of many Moldovan workers. The high cost of living, especially during the harsh winter months when energy prices soar, places an additional burden on already strained household budgets. Finally, the geographical location of an individual’s area of residence also plays a significant role in determining one’s economic opportunities. The research unequivocally demonstrates a direct correlation between poverty among the working population and the alarming rate of emigration. Driven by a desperate search for improved living conditions and the promise of significantly higher wages, Moldovan citizens are increasingly choosing to leave their home country in pursuit of economic security elsewhere. In conclusion, to effectively address the challenges plaguing the Moldovan labor market, reduce the rate of poverty, particularly in impoverished rural communities, and curtail the alarming outflow of population, the author proposes a comprehensive set of policy recommendations for the Moldovan authorities. These include: implementing a substantial increase in the minimum wage to ensure a living wage for all workers, stimulating sustainable economic growth and actively creating new jobs, investing heavily in developing human capital and improving the education level of the workforce, strengthening targeted social assistance programs, and decisively combating corruption.

The rise of far-right ideologies in Europe presents a significant challenge, driven by complex socio-economic, cultural, and psychological factors. This paper examines the role of high emigration rates, economic stagnation, and nostalgia for a perceived utopian past in fueling far-right support. It also explores broader issues such as economic grievances, digital misinformation, and cultural backlash. Through an interdisciplinary approach, combining quantitative and qualitative methods, this study highlights the interplay between these factors and their impact on political behavior. Key findings indicate that regions experiencing high emigration and economic stagnation tend to show higher levels of support for far-right parties. The departure of young and skilled individuals can contribute to sustained economic challenges and create socio-political conditions in which certain political actors gain traction. Feelings of nostalgia for past social or economic conditions, along with reactions to rapid cultural change, also appear to be associated with increased receptiveness to such parties. Digital information dynamics, including the circulation of misleading content, further shape these patterns by influencing how political messages are disseminated and perceived. Policy recommendations in the literature suggest that addressing development traps through investment in education, vocational training, and local entrepreneurship may strengthen economic resilience. Initiatives aimed at promoting social cohesion and community engagement are also identified as potentially relevant for reducing perceived socio-political marginalisation. Furthermore, improving digital literacy and reviewing the regulatory frameworks governing online platforms have been proposed as approaches that could help improve the quality and reliability of information circulating in digital environments. This study highlights the relevance of adopting comprehensive and balanced policy approaches to address factors associated with regional variations in support for far-right parties. Policies that encourage economic development, strengthen social inclusion, and improve communication and outreach mechanisms are identified in the literature as potentially contributing to greater socio-political stability. Future research could benefit from longitudinal and comparative analyses to deepen understanding of these dynamics and to inform context-sensitive policy design.

Abstract Prior research shows that older Puerto Ricans may be migrating to the US mainland, which may include those with an Alzheimer’s Disease and Related Dementia (ADRD) diagnosis (Rivera-Hernandez, 2022; Kim et al., 2024). The purpose of this research was to examine yearly out-migration trends among older Puerto Ricans by examining their movement patterns from 2012-2019, which included the period of Hurricane Maria. The analysis used data from the Master Beneficiary Summary File and the American Community Survey, and focused on Medicare fee-for-service enrollees in Puerto Rico (65+). The Chronic Conditions Warehouse algorithm was used to ascertain ADRD diagnosis, and migration was defined as the change of (end-of-year) residence from one year to the next. A linear probability model was used to calculate differences in the rate of outmigration between beneficiaries with and without ADRD. There were about 44,000∼66,000 beneficiaries each year and around 15∼16% with ADRD. Outcomes showed that, overall, older Puerto Ricans previously diagnosed with ADRD were slightly more likely to move to the US mainland compared to those without an ADRD diagnosis across the years (Adjusted differences ranged, b = 0.0014∼0.0041), with the highest proportion migrating during the year of Hurricane Maria (over 2.5% in 2017). However, the difference was not statistically significant for some years. In sensitivity analyses across groups with sociodemographic and clinical characteristics, the likelihood of outmigration was higher among those with ADRD compared to those without ADRD. Our results suggest that older adults with complex health needs appear to be out-migrating following their ADRD diagnosis.

According to the International Organization for Migration, in 2021 Romania ranked among the top 20 countries worldwide with the highest emigration rates. This concerning trend contributes to labor shortages that impede Romania’s long-term economic growth. Addressing this challenge requires a deep understanding of the reasons behind individuals’ intentions to leave their city of residence, particularly their emigration intentions. This study examines the relationship between life satisfaction and migration intentions in urban Romania, using a range of individual and regional correlates while distinctly addressing intentions to migrate domestically versus internationally. The findings indicate that low levels of life satisfaction influence only emigration intentions, whereas internal migration intentions are primarily driven by specific financial and personal characteristics. Moreover, regional economic development plays a limited role in explaining urban migration intentions. Various models and specifications were employed to ensure the robustness of the empirical results.

Context Movement and migration are important components of population dynamics and affect the susceptibility of different population units to fishing mortality. Aims We applied acoustic telemetry to investigate emigration from heavily fished estuarine habitats to lightly fished inshore habitats in the largest blue swimmer crab (Portunus armatus) fishery in south-eastern Australia (Wallis Lake, New South Wales). Methods Eighty recently moulted mature female crabs were tagged across four tagging cohorts (November 2023, January, February and March 2024) and two sizes (pre-recruited, 60–65-mm carapace length, CL; recruited, ≥65 mm CL), and their movements tracked on an array of estuarine and inshore receivers. Key results Over 60% of tagged crabs left the estuary, but emigration rates were higher for pre-recruited sizes. Modelling indicated a minor influence of reduced water temperature and conductivity on emigration probability for recruited crabs, and movements showed some synchronisation with larger tides. Conclusions Mature female crabs emigrate from the estuary over the warmer months, and are likely to spawn in inshore waters. Implications It is likely that emigration has implications for both spawning and fisheries productivity, but resolution of early life-history connectivity patterns is critical for defining the full implications of these newly resolved stock dynamics.

The Mojave desert tortoise Gopherus agassizii experienced population declines during recent decades, which have persisted despite its designation as a federally protected species. A small number of populations were monitored with mark-recapture methods starting in the 1970s, but inconsistent sampling resulted in challenges estimating the range of factors influencing survival. Large amounts of tortoise telemetry data were collected in recent decades, providing an alternative source for survival estimation. Here, we describe an integrated, spatially explicit, analysis that combined mark-recapture (3923 tortoises, 35 sites, 1977-2022) and telemetry (2858 tortoises, 22 sites, 1988-2022) datasets to estimate variation in survival across tortoise populations. We produced robust estimates of annual survival conditioned on climate-related covariates and compared results to non-integrated known-fate and mark-recapture models. Integration allowed for estimation of effects on survival not recovered by non-integrated models, including higher survival of males than females, lower survival of juveniles and subadults than adults, and a positive effect of total precipitation from 2 prior winters and active seasons. The integrated analysis estimated permanent emigration rate as the difference between both true survival (via telemetry data) and apparent survival (via capture-recapture data). Annual emigration probability was ~5% in 1 km 2 plots and decreased with increasing plot size. Our results demonstrate the strength of leveraging multiple data sources in describing historical demographic rates and identifying relationships with covariates that have delayed effects on survival. Our modeling framework could be used to examine the effects of additional factors on tortoise survival and resulting population dynamics.

<p>This study aims to identify barriers perceived by Generation Z to establishing and running a business, with particular attention to gender differences. The study is set in a regional context. It presents the perspective of Generation Z operating in a peripheral region characterised by a high rate of human capital outmigration to larger cities. The research problem addressed the identification of factors (economic/organisational and psychosocial) that, from the perspective of Generation Z representatives in the Podlaskie region, hinder or prevent the creation and operation of their own businesses, taking into account the gender dimension. The results presented in this study constitute an unpublished fragment of a project conducted at the University of Lomza. The study presents results from a survey of 340 Generation Z respondents (students and graduates up to 3 years after completing their higher education) in the Podlaskie region (Bialystok, Lomza, and Suwalki subregions). The empirical section utilises a proprietary CAWI survey questionnaire.</p>

Introduction: The Total Fertility Rate (TFR) of Sri Lanka has been unavailable since 2016, when the Demographic and Health Survey (DHS) reported a TFR of 2.2 live births per woman. Estimating TFR for the period 2016–2024 is crucial, particularly from a sexual and reproductive health (SRH) perspective, given the possible impacts of the COVID-19 pandemic and economic crisis on fertility behaviour. Objectives: First, it aims to assess the validity of an alternative method by comparing its TFR estimates for South Korea with those obtained through the standard technique. Second, based on the demonstrated validity of the two sets of estimates for South Korea, the alternative method is applied to estimate the TFR of Sri Lanka. Further the analysis explores the broader demographic and socio-economic implications of fertility change. Methods: Initially, the alternative method is applied to estimate the TFR for South Korea, a country with up-to-date statistics. These estimates are the compared with standard TFR figures to assess the method’s validity. Upon confirming a high degree of validity between the two sets of estimates, the alternative method is used to estimate the TFR for Sri Lanka. Results: Sri Lanka’s TFR fell below replacement level by 2016 and has continued to decline, reaching an estimated 1.4 in 2023 and 1.3 in 2024. These figures indicate that the country is on the verge of entering an ultra-low fertility regime, typically defined as a TFR below 1.3. Sri Lanka began experiencing population decline from 2022, when the total population peaked at 22.1 million. This demographic shift is primarily driven by a sharp decline in natural increase and a substantial net out-migration rate between 2022 and 2024. Conclusion: Sri Lanka’s transition toward ultra-low fertility has significant macro-level implications, including a rapidly ageing population, a shrinking labour force, and mounting pressure on healthcare and social protection. These trends underscore the urgent need for evidence-based policy interventions to stabilize/reverse fertility levels.

Emigration concerns a growing number of developing countries, which have experienced a fast pace of urbanization since 1960. Yet we lack evidence about the interlinkages between the two phenomena. Should governments expect large-scale emigration, as ongoing urbanization increases people's aspirations and capabilities to move? We analyze rates of emigration (i.e., movements crossing national borders) from different tiers of the urban hierarchy observed in 40 developing countries spanning the entire spectrum of urbanization. Estimates are obtained by demographic analysis of population censuses fielded between 1970 and 2017. Remote sensing products ensure an internationally consistent definition of cities. Statistical modelling is used to summarize global trends in emigration over the course of urbanization. Results reveal that the propensity to move abroad diffuses down the urban hierarchy. In early stages of urbanization, emigration rates are highest in cities, especially in the largest ones, but subsequently decline. Rural areas exhibit a lagged increase in emigration, first in more densely populated settlements, in the cities’ hinterlands and border areas, and eventually in the sparsely populated and remote countryside. In late stages of urbanization, rural emigration tends to plateau or increase again. There is evidence of a decline only in the remote countryside. Yet the rural rates of emigration remain consistently below the peak levels observed in cities. We interpret these findings with reference to the subnational diffusion of development and discuss implications for international migration and urbanization trends in developing countries.