Population Trends Research Articles

Unsustainable Dolphin-Watching Tourism in Fiordland, New Zealand

Bottlenose dolphins are a key resource of the tourism industry in Fiordland and are used on a daily basis by the tour operators offering cruises on the fiords. Recent studies have shown that the current levels of dolphin???boat interactions in this region cannot be sustained by bottlenose dolphins. Interactions have both short‐ and long‐term effects on both individuals and their populations. Population models indicate that these effects may be affecting the viability of the three bottlenose dolphin populations living in Fiordland. We are currently observing drastic changes in the bottlenose dolphin population living in Doubtful Sound, which can be linked to the level of boat interactions to which they are currently exposed. The creation of a multilevel marine mammal sanctuary would help minimize dolphin???boat interactions and still allow for some further growth in the tourism sector in Fiordland.

Global, regional, and national burden of seborrheic dermatitis in individuals aged 55 and older from 1990 to 2021: a trend analysis and future projections.

Seborrheic dermatitis (SD), an inflammatory dermatosis, significantly lowers quality of life, particularly in the elderly. Although studies have focused on the burden of SD globally before, trends among people 55 and older have received less attention. Utilizing the data released in 2021 by the Global Burden of Disease (GBD) consortium, our research was conducted to evaluate the global, regional, and national burden of SD in adults over 55 between 1990 and 2021 through incidence, prevalence, and disability-adjusted life years (DALYs) alongside advanced methods such as joinpoint regression analysis. We also performed decomposition analysis to examine the contributions of population and epidemiological changes. Correlation analysis was used to explore the assocaition between Socio-demographic Index (SDI) /climate-related parameters and SD. The global incidence of SD among adults aged 55 and older markedly rose from 1990 to 2021. The incidence grew by 120.84%, the prevalence by 125.09%, and the DALYs rose by 124.25%. Higher burdens were observed in the high and high-middle SDI regions, whereas low SDI areas displayed the highest age-standardized rates. Environmental factors, particularly global warming, were strongly connected with the incidence and prevalence of SD. Future projections suggested continued increases in SD cases through 2040. This study highlights the increasing burden of SD among older adults, emphasizing the role of demographic and environmental factors. Targeted public health interventions addressing aging populations and climate-related risks are urgent to mitigate the impact of SD globally.

The Impact of Talent Attraction Policies on Housing Prices in Haikou, Nanjing, and Wuhan

In the context of escalating global urban competition, attracting top talent has become essential for cities to boost economic competitiveness. Talent attraction policies significantly impact local economies and real estate markets by driving population growth and enhancing urban innovation. Talent attraction programs profoundly influence local economies and real estate markets by stimulating population expansion and fostering urban innovation. This study focuses on Haikou, Nanjing, and Wuhan, using empirical methods to analyze the impact of talent attraction policies on housing prices. Through parallel trends tests and group regression analyses, results show that these policies significantly affect housing prices, with policy implementation leading to notable price increases. Additionally, mediating effects analysis indicates that research and development levels and patent grants mediate the relationship between talent attraction policies and housing prices, highlighting innovation as a key mechanism. Placebo tests confirm the validity of these policy effects, revealing no significant impacts outside the implementation periods. This paper advises governments to refine policy measures, balance real estate market health with talent attraction, and enhance investments in research infrastructure for sustainable urban economic growth.

Exploration and comparison of the effectiveness of swarm intelligence algorithm in early identification of cardiovascular disease

Due to the aging of the global population and lifestyle changes, cardiovascular disease has become the leading cause of death worldwide, causing serious public health problems and economic pressures. Early and accurate prediction of cardiovascular disease is crucial to reducing morbidity and mortality, but traditional prediction methods often lack robustness. This study focuses on integrating swarm intelligence feature selection algorithms (including whale optimization algorithm, cuckoo search algorithm, flower pollination algorithm, Harris hawk optimization algorithm, particle swarm optimization algorithm, and genetic algorithm) with machine learning technology to improve the early diagnosis of cardiovascular disease. This study systematically evaluated the performance of each feature selection algorithm under different population sizes, specifically by comparing their average running time and objective function values to identify the optimal feature subset. Subsequently, the selected feature subsets were integrated into ten classification models, and a comprehensive weighted evaluation was performed based on the accuracy, precision, recall, F1 score, and AUC value of the model to determine the optimal model configuration. The results showed that random forest, extreme gradient boosting, adaptive boosting and k-nearest neighbor models performed best on the combined dataset (weighted score of 1), where the feature set consisted of 9 key features selected by the cuckoo search algorithm when the population size was 25; while on the Framingham dataset, the k-nearest neighbor model performed best (weighted score of 0.92), and its feature set was derived from 10 features selected by the whale optimization algorithm when the population size was 50. The results of this study show that swarm intelligence algorithms can effectively screen key and informative feature sets, significantly improve model classification accuracy, and provide strong support for the early diagnosis of cardiovascular diseases.

Advances and shortfalls in knowledge of Antarctic terrestrial and freshwater biodiversity.

Antarctica harbors many distinctive features of life, yet much about the diversity and functioning of Antarctica's life remains unknown. Evolutionary histories and functional ecology are well understood only for vertebrates, whereas research on invertebrates is largely limited to species descriptions and some studies on environmental tolerances. Knowledge on Antarctic vegetation cover showcases the challenges of characterizing population trends for most groups. Recent community-level microbial studies have provided insights into the functioning of life at its limits. Overall, biotic interactions remain largely unknown across all groups, restricted to basic information on trophic level placement. Insufficient knowledge of many groups limits the understanding of ecological processes on the continent. Remedies for the current situation rely on identifying the caveats of each ecological discipline and finding targeted solutions. Such precise delimitation of knowledge gaps will enable a more aware, representative, and strategic systematic conservation planning of Antarctica.

Effect of Carbon Nanomaterials Incorporated Polymeric Membrane Separators for Energy Storage Devices.

The rapid expansion of the global population and technological advancements have heightened the need for efficient energy conversion and electrochemical energy storage. Electrochemical energy systems like batteries and supercapacitors have seen notable development to meet this demand. However, conventional polymeric membrane separators in these systems face challenges due to limited porosity and poor mechanical and thermal properties, reducing overall electrochemical performance. Researchers have incorporated nanoparticles into the polymer matrix to address these limitations and enhance separator properties. Carbon-based nanomaterials, in particular, have gained prominence due to their unique features, such as surface-dependent characteristics, size, porosity, morphology, and electrical conductivity. These properties make carbon-based nanomaterials advantageous in improving energy storage compared to conventional materials. Advanced carbon-doped polymeric membrane separators have emerged as a potential solution to the issues faced by conventional separators. Adding carbon nanoparticles, such as graphene-based materials and carbon nanotubes to the polymeric separators of batteries and supercapacitors has helped researchers solve problems and improve the electrochemical performance. This review article provides a state-of-the-art overview of carbon-doped polymeric membrane separators, their properties, fabrication processes, and performance in lithium batteries, as well as supercapacitors. It emphasizes advantages of these novel separator materials and suggests future research directions in this field.

Computational simulation of graphene/h-BN nanopores for single-molecule herbicide sensing

The growing world population and climate change are key drivers for the increasing pursuit of more efficient and environmentally-safe food production. In this scenario, the large scale use of herbicides demands the development of new technologies to control and monitor the application of these compounds, due to their severe environmental and health-related problems. Motivated by these issues, in this work, a hybrid graphene/boron nitride nanopore is explored to detect/identify herbicide molecules (Glyphosate, aminomethylphosphonic acid, Diuron, and 2,4D). Solid-state nanopores based on 2D materials have been widely explored as novel generation sensors capable of single-molecule resolution. The present investigation combines density functional theory (DFT) and the non-equilibrium Green's function method to assess the interaction of each herbicide with the nanopore and how its interaction modulates the device's electronic transport properties. The device's sensitivity spreads from 9.0% up to 27.0% when probed at different gate voltages. Overall, the proposed device seems to be sensitive and selective to be considered as a promising single-molecule herbicide sensor.

Avifaunal Diversity of Shaheed Ashfaq Ullah Khan Prani Udyan (Zoological Park) in Uttar Pradesh, India

Avian taxa are natural indicators of a healthy ecosystem. India has 1332 bird species, about 6% of population. Birds survey was carried out in the winter season from December 2023 to February 2024 at Gorakhpur Zoo (26.713403°N and 83.407705°E, 68m altitude), Uttar Pradesh, following the fixed transects. We recorded 85 avian species belonging to 39 families and 17 orders. Ardeidae was the most diverse family of birds in the study area (RDi value = 8.33). Among the recorded species, 63 species are Resident, 19 species are winter migrant and 3 species are local migrant. During the survey, we recorded one threatened species and winter migrant, the Ferruginous Pochard. There are no studies conducted on birds at the study site despite its abundant avian population. It is essential to conduct further research to monitor the species and population trends of birds, particularly in light of shifting climatic conditions.

Sex-specific associations between estimated glucose disposal rate and cognitive decline in middle-aged and older adults in China: a longitudinal cohort study

BackgroundInsulin resistance (IR) is recognized as a potential modifiable risk factor for cognitive decline, but findings within Asian populations have been inconsistent. Given the high prevalence of dementia and its substantial economic burden in China, large-scale longitudinal studies are essential to elucidate the complex relationship between IR and cognitive function.MethodsThis longitudinal cohort study included 8,734 middle-aged and older adults (median age: 58 years; 53.6% females) from the China Health and Retirement Longitudinal Study (CHARLS), followed from 2011 to 2018. Estimated glucose disposal rate (eGDR) was used to assess IR and was calculated using waist circumference, hypertension status, and HbA1c levels. Participants were categorized into tertiles based on eGDR levels (Tertile 1: lowest; Tertile 3: highest). Cognitive function was calculated as the sum of episodic memory and executive function scores, which was then standardized to a Z-score. Linear mixed-effects models and dose-response analyses were performed to evaluate the association between baseline eGDR and cognitive changes in the total population and stratified by sex.ResultsHigher eGDR levels were significantly associated with slower global cognitive decline (Tertile 3 vs. Tertile 1: β = 0.007; 95% CI: 0.000–0.014; P = 0.047). This association was stronger in females (Tertile 3 vs. Tertile 1: β = 0.011; 95% CI: 0.002–0.021; P = 0.021), while no significant association was observed in males. Dose-response analyses indicated a linear positive relationship between baseline eGDR and global cognitive function in the total population and in females, but not in males. Similar patterns were found for episodic memory and executive function, with significant associations predominantly in females.ConclusionHigher eGDR was significantly associated with slower cognitive decline, particularly among women. These findings underscore the potential of eGDR as a marker for identifying and mitigating cognitive decline and highlight the importance of sex-specific strategies to address insulin resistance and promote cognitive health.

GenomeDecoder: Inferring Segmental Duplica-tions in Highly-Repetitive Genomic Regions.

The emergence of the "telomere-to-telomere" genomics brought the challenge of identifying segmental duplications (SDs) in complete genomes. It further opened a possibility for identifying the differences in SDs across individual human genomes and studying the SD evolution. These newly emerged challenges require algorithms for reconstructing SDs in the most complex genomic regions that evaded all previous attempts to analyze their architecture, such as rapidly-evolving immunoglobulin loci. We describe the GenomeDecoder algorithm for inferring SDs and apply it to analyzing genomic architectures of various loci in primate genomes. Our analysis revealed that multiple duplications/deletions led to a rapid birth/death of immunoglobulin genes within the human population and large changes in genomic architecture of immunoglobulin loci across primate genomes. Comparison of immunoglobulin loci across primate genomes suggests that they are subjected to diversifying selection. GenomeDecoder is available at https://github.com/ZhangZhenmiao/GenomeDecoder. The software version and test data used in this paper is uploaded to https://doi.org/10.5281/zenodo.14753844. Supplementary data are available at Bioinformatics online.

IDENTIFYING THE DRIVERS OF HOUSEHOLD WATER USAGE EFFICIENCY IN TERENGGANU: THEORY OF PLANNED BEHAVIOR (TPB) APPROACH

In the contemporary era, the issue of water scarcity has emerged as a critical concern on a global scale. Factors such as rapid population expansion, urbanization, and the uncertainties associated with climate change have exerted significant influence on water availability, particularly in the context of domestic consumption. Regions including Klang Valley, Selangor, Johor, Perlis, Melaka, and Negeri Sembilan are currently grappling with water shortages. Despite Malaysia's reputation for substantial rainfall, the nation is increasingly confronted with freshwater scarcity concerns. Consequently, the primary objectives encompass an examination of water consumption patterns and the identification of determinants driving water conservation within households. The study sample encompasses 271 households. Results indicate that both attitude and subjective norms are significantly correlated with water use efficiency, with corresponding p-values of 0.076 and 0.86, respectively. The insights gleaned from water usage patterns can serve as valuable tools for water operators in the management and educational efforts targeted at households, including campaigns promoting sustainable water usage and conservation practices.

Bamboozle: A Bioinformatic Tool for Identification and Quantification of Intraspecific Barcodes.

Evolutionary changes in populations of microbes, such as microalgae, cannot be traced using conventional metabarcoding loci as they lack intraspecific resolution. Consequently, selection and competition processes among strains of the same species cannot be resolved without elaborate isolation, culturing, and genotyping efforts. Bamboozle, a new bioinformatic tool introduced here, scans the entire genome of a species and identifies allele-rich barcodes that enable direct identification of different genetic strains from a population using amplicon sequencing of a single DNA sample. We demonstrate its usefulness by identifying hypervariable barcoding loci (< 500 bp) from genomic data in two microalgal species, the diploid diatom Skeletonema marinoi and the haploid chlorophyte Chlamydomonas reinhardtii. Across the two genomes, four and twenty-two loci, respectively, were identified that could in silico resolve all analysed genotypes. All of the identified loci are within protein-coding genes with various metabolic functions. Single nucleotide polymorphisms (SNPs) provided the most reliable genetic markers, and among 54 strains of S. marinoi, three 500 bp loci contained, on average, 46 SNPs, 103 strain-specific alleles, and displayed 100% heterozygosity. This high level of heterozygosity was identified as a novel opportunity to improve strain quantification and detect false positive artefacts during denoising of amplicon sequences. Finally, we illustrate how metabarcoding of a single genetic locus can be used to track abundances of S. marinoi strains in an artificial selection experiment. As future genomic datasets become available and DNA sequencing technologies develop, Bamboozle has flexible user settings enabling optimal barcodes to be designed for other species and applications.

Many winners, few losers: stable bird populations on an Afrotropical mountain amidst climate change

Organisms in mountainous areas are frequently exposed to climatic extremes and are among the most vulnerable to climate change. Long-term studies on birds along elevational gradients, which are vital in understanding species dynamics, are rare in tropical mountains, which limits the ability to understand their population trends in the face of climate change. We modelled local abundances of understorey bird species (N=18) over a 13-year period (2011–2023) in Mt. Kasigau, Kenya, using mist netting data collected along an elevational gradient. Our models show relatively stable bird abundances in the study period. However, we found two distinct population crashes that affected most species in 2015 and 2022, suggesting that changes in local dynamics may lead to heavy declines of bird populations in mountainous regions. Most species had stable local abundances in the study period, but parametric bootstrapping revealed a declining trend for a few species, including an endemic, threatened species. We highlight the importance of mountainous regions in maintaining relatively stable populations in the face of global environmental transformation such as posed by climate change, and the dynamism of bird species populations across relatively small spatial-temporal variations. While mountain ecosystems are viewed as potential refugia for biodiversity in the face of a warming climate, further studies are needed to understand the drivers of short and long-term declines in bird populations at higher elevations, especially in tropical Africa.

When Rentier Patronage Breaks Down: The Politics of Citizen Outsiders on Gulf Oil States’ Labour Markets

Abstract In oil-rich Gulf monarchies, fiscal constraints and demographic growth are leading to the exclusion of young citizens from the established social contract as government jobs—the dominant channel of patronage in the region—are becoming unavailable to them. We show that such outsider citizens constitute a new, politically consequential social class that is exposed to a much less attractive private labour market where they compete with low-cost migrant workers. The dualization of labour markets for citizens provides a new lens for understanding regional political unrest since the late 2000s and new group interests emerging around labour and migration policy, in which labour organizations representing outsiders have started to display solidarity with migrant workers. The new insider–outsider cleavages require a revision of rentier state theory’s claims about (the absence of) class formation and the role of inequality in rentier politics. They help us expand and refine Eurocentric theories of labour market dualism.

Climate Change Impact on the Populations of Goldcrest Regulus regulus and Firecrest Regulus ignicapilla Migrating Through the Southern Baltic Coast

Climate change has a great impact on wildlife, which needs to be considered when designing conservation and management practices in habitats rich in biodiversity, such as wetlands and forests. Varied responses to climate change of species with different environmental preferences can be used to monitor different aspects of the environment. Since 2000, we have observed contrasting changes in the numbers of two related forest bird species, Goldcrest and Firecrest, monitored during autumn migration (14 August–1 November) over 1976–2024 by mist netting at 2 bird ringing stations on the Polish coast of the Baltic Sea. At both stations of the Operation Baltic project (Bukowo-Kopań and Mierzeja Wiślana), located ca 200 km apart, we observed a long-term decline in the number of Goldcrest since the 1980s but an increase in the number of Firecrest since the year 2000. These two species with ranges overlapping in Europe slightly differ in their preferences for breeding habitat and migration strategies. We found that in both species, the changes in migrating bird abundance in autumn at both stations were correlated with the Pan-European breeding population trends from the Pan-European Common Bird Monitoring Scheme (PECBMS) over 1982–2022. These correlations suggest that some Europe-wide factors underly these changes. Thus, we analyzed the effects of seven climate factors: the European Temperature Anomaly and the North Atlantic Oscillation Index in spring (March–April), summer (May–July) and autumn (October), and the Eurasian Snow Cover in October, on bird abundance indexes during breeding and autumn migration, using multiple regression models. Both species were more abundant during breeding and migration after warm springs, which conduce their early breeding and two broods per season, thus improving their breeding success. But with warm summers, Goldcrest were less abundant during breeding in Europe and on migration at Bukowo-Kopań. We attribute that pattern to Goldcrest’s tendency to overwinter in Scandinavia after warm summers. We suggest that this strategy became an ecological trap, as the climate change in Europe involves the increase of summer temperatures by 2 °C over the last 42 years but also earlier snow in October, which impedes Goldcrest’s feeding. These factors, combined with the decreasing proportion of coniferous forests in Scandinavia, which are Goldcrest’s main breeding habitat, assumably caused the species’ decline, which we expect to continue. Firecrest showed a weaker response to snow in October, but their autumn migration at both stations shifted earlier since the late 1980s, alleviating any effect of early winters. Warm spring and summers favor Firecrest abundance during breeding and migration. Firecrest also benefit from more broadleaf trees in Fennoscandia, thus we expect this species to expand its breeding range farther northeast and to continue the population increase. The change in forest management policy in Scandinavia by planting more broadleaf trees aims at increasing biodiversity and might considerably influence the forest environment. Thus, it is imperative to identify the methods suited for early detection of such changes. We showed that monitoring the numbers of migrating birds provides good indicators of the effects of short- and long-term environmental changes on bird populations.

The role of climate and population change in global flood exposure and vulnerability

Flooding is a pervasive natural hazard with wide-ranging impacts on society. Using a high-resolution global flood model considering coastal, fluvial, and pluvial hazards, we clarify the role of climate effects versus population growth effects in changing flood exposure. Between 2020 and 2100, the population likely exposed to 1% annual risk (100-year) flood hazard will increase from 1.6 to 1.9 billion people. Of this change from the 2020 exposure, we attribute 21.1% to climate change, 76.8% to population change, and 2.1% to both climate and population change. The largest driver of uncertainty in exposure is population change, while climate change remains a smaller but still important driver. The global increase in exposure between 2020 and 2100 is primarily driven by low-GDP regions, and by 2100 the lowest GDP areas will make up 63% of the exposure both overall and in urban areas. Urban areas are especially vulnerable in nearly all global regions, and urban areas sensitive to extreme events are expected to see a 33% increase in population exposure. This study highlights the vast inequities in flood exposure, and future work should direct resources and strategies toward sustainable risk mitigation in these areas.

An analysis of the burden of migraine and tension-type headache across the global, China, the United States, India and Japan

BackgroundRecurrent headaches in headache disorders adversely impact quality of life and job. Migraines and tension-type headache TTH) are the most common primary headaches and a prominent cause of disability globally. However, few research compare headache illness burden in China, India, the United States (US), and Japan.MethodsGlobal and Chinese, the US, Indian, and Japanese migraine and TTH incidence, prevalence, and disability-adjusted life years were taken from the GBD database for 1990–2021. The data is studied utilizing decomposition analysis, health inequality research, joinpoint regression model, and Bayesian Average Annual Percentage Change (BAPC) model.ResultsThe study found that migraine mostly affects women aged 15–49, while TTH are evenly distributed across gender and age. The worldwide average annual percentage change (AAPC) in disease-adjusted life years (DALYs) for migraine and TTH from 1990 to 2021 was 0.0357, a statistically significant trend (p &amp;lt; 0.001), as determined using joinpoint analysis. China exhibited the quickest rise in migraine and TTH incidence and prevalence, as well as the age-standardized rate (ASR) of DALYs, of the four nations analyzed. The US had the highest value of these indicators. Forecasting models reveal that without policy action, migraine prevalence will grow but TTH prevalence would stay unchanged. Decomposition research showed that population expansion is the major cause of migraines and TTH, which will be slightly alleviated by population aging. Health disparities across economic growth areas lessened between 1990 and 2021, according to the report.ConclusionGlobally and in China, migraine and TTH incidence and burden have increased since 1990. Migraines are becoming more common in young and middle-aged women, so headache treatment professionals should invest more in patient education to raise awareness and improve self-management to reduce disease burden and medical costs.

Realizing the Right to Special Geriatric Care

The demographic trend of an aging population places increasing demands on healthcare systems worldwide, which necessitates adapting public health services to the needs of older adults. In Poland, current regulations lack provisions specifically tailored to the elderly. Recent legal reforms by public authorities represent an attempt to address this gap by establishing a network of entities providing special geriatric care. This article analyzes these regulatory frameworks and assesses the feasibility of their implementation.

Population Size and Language Change: An Evolutionary Perspective

There is increasing interest in the way that the size, composition, and environment of populations influence the way that their languages evolve. There are two reasons why an exploration of population and language change from the perspective of evolutionary biology might be useful. First, some of the relevant hypotheses rest explicitly or implicitly on theories developed in evolutionary biology, so it is important to critically evaluate the fit of these theories to language change. Second, methods developed in evolutionary biology have been applied to evaluating these hypotheses. Instead of aiming for a comprehensive review of the interaction between population size and language change, the focus of this review is on analogies drawn to processes in biological evolution (e.g., founder effects), processes that may have interesting parallels in both species and languages (e.g., evolution of complexity in small populations), and techniques from evolutionary biology that have been applied to language data (e.g., Wright-Fisher models).

An integrative framework to combine migratory connectivity and demographic data

Abstract Migratory species experience various conditions and events throughout their annual cycle that influence their spatial and demographic dynamics. To understand these dynamics, it is essential to describe the origin and destination of individuals. Migratory connectivity, which is defined as the geographic linkage between populations across the annual cycle, is increasingly incorporated in population models to relate population trends to environmental variables at different stages of the cycle. However, such information on migratory movements is obtained independently from the study of population dynamics despite the interaction between both processes. Expanding on the growing use of integrated modelling approaches, we developed an integrated framework that allows the sharing of information between migratory connectivity and population data. We first assembled an integrated migratory connectivity model and an integrated population model to join the analysis of GPS, live‐reencounter, dead‐recovery, capture–mark–recapture, and population count data within a unified framework. Based on simulated data, we assessed the ability of the resulting integrated connectivity and population model to produce unbiased and precise connectivity and demographic estimates. We then applied the same assessment to real data using the Eurasian Curlew (Numenius arquata) as a case study. On simulated data, the integrated connectivity and population model estimated connectivity and survival parameters with no bias and similar precision to the connectivity model alone. However, it outperformed the population model in estimating fecundity in the absence of explicit productivity data. When applied to the Eurasian Curlew, the integrated connectivity and population model produced overall similar migratory connectivity and more accurate demographic estimates than the connectivity model alone, consistent with previous studies. Additionally, the model was able to estimate fecundity, whereas the data were too sparse for the population model alone to disentangle juvenile survival and fecundity. The sharing of information between migratory connectivity and population data improved the estimation of demographic parameters by the population model and improved connectivity parameter estimates when data were scarce. This flexible framework can be generalised to include diverse data on migration movements, population structure, individual heterogeneity or environmental variables, allowing further investigation of the interaction between migration patterns and population dynamics.