Search Results (187)

To date, Philaenus spumarius (Linnaeus, 1758), Philaenus italosignus Drosopoulos & Remane, 2000, and Neophilaenus campestris (Fallén, 1805) are proven vectors of the phytopathogenic bacterium Xylella fastidiosa Wells et al., 1987 in Europe. Currently, the identification of these three species relies on the well-documented status of morphological and taxonomical characters, making the discrimination of vector adult males possible by genitalia comparison. This study updates the biomolecular diagnostic tests with a rapid identification tool for P. italosignus, using locked nucleic acid (LNA) probe technology. The test also overcomes the difficulties associated with the morphological identification of females and juveniles. The morphological α-taxonomic identification of the male, achieved through comparison with the type of the species, retains its primary role in specimen identification for probe building. Later, the proposed assay can contribute to the rapid identification of P. italosignus by the secondary (molecular) identification step. The new LNA qPCR test offers high reliability and reproducibility in the identification of P. italosignus instars, thus improving targeted surveys of X. fastidiosa vector populations and allowing discrimination between species collected in the field. The accurate identification and census of vector individuals, regardless of their gender and instar, enhances the efficacy of Xylella IPM-DSS (Integrated Pest Management Decision Support System) strategies. Full article

Background: Accurate estimation of mortality is essential for effective public health planning, policymaking, and monitoring of health interventions. In Ghana, multiple data sources are used to estimate mortality, including civil registration systems, household surveys, census data, and health and demographic surveillance systems. This scoping review explores the existing sources of mortality data in Ghana, examining their challenges and opportunities. Methods: Using Arksey and O’Malley’s framework, we identified peer-reviewed and grey literature from Ghana Health Service, Ministry of Health, Ghana Statistical Service, WHO, and the United Nations. We selected studies published between 2000 and 2024 that focused on mortality estimation in Ghana. Data was extracted and synthesized into key themes: data sources, challenges, and opportunities. Results: Six major data sources on mortality were identified: Civil Registration and Vital Statistics (CRVS), census data, Demographic and Health Surveys (DHS), Health and Demographic Surveillance Systems (HDSS), Facility-Based Health Information Systems (HMIS), modeled estimates from the Global Burden of Disease (GBD) and from the United Nations Department of Economic and Social Affairs (UN DESA). Key challenges include under-registration of deaths (CRVS and HMIS), recall bias (DHS, census), limited geographic coverage (HDSS), inconsistencies in cause-of-death classification (HMIS, HDSS), and lack of local geographic coverage (GBD, UN DESA, DHS). Nonetheless, benefits include longitudinal follow-up (HDSS), local coverage and ownership (CRVS, HMIS) and international comparability (GBD, UN DESA, DHS). Conclusions: Mortality estimation in Ghana is supported by diverse but fragmented data sources. Strengthening the CRVS and HMIS systems, integrating multiple data streams, standardizing methodologies, and enhancing institutional partnership are essential steps toward improving data quality and coverage. This review provides recommendations for improvement towards better quality estimations of mortality in Ghana. Full article

Urban safety is a critical concern for sustainable city development, with crime patterns often linked to localized environmental factors. Understanding the spatial dynamics of safety is critical for informed design and planning of urban environments. This study employs a Geographically Weighted Regression (GWR) approach to investigate how crime in Austin, Texas, correlates with Points of Interest (POIs) such as bars, transit stations, financial businesses, and public spaces, while accounting for localized socio-economic factors. Building on theoretical frameworks like Routine Activity Theory and Crime Pattern Theory, the analysis integrates crime data from the Austin Police Department (APD), POI datasets, and census variables to explore spatially varying relationships often overlooked by traditional global models (e.g., OLS). A novel adaptive geo-grid method refines spatial units by clustering high-density downtown areas into smaller zones and retaining larger grids in suburban regions, ensuring precision without over-fragmentation. Analysis of crime incidents and POI data reveals significant spatial non-stationarity in crime–environment associations. Transportation-related facilities demonstrate strong spatial correlation with crime citywide, particularly forming persistent crime hotspots around transit hubs in areas like Rundberg Lane, South Congress, and East Riverside. Alcohol-related establishments show a strong positive correlation with crime in entertainment districts (coefficient up to 13.5, p < 0.001) but a negligible association in suburban residential areas (coefficient close to 0, p > 0.05). The GWR model significantly outperforms traditional OLS regression, capturing critical local variations obscured by global models. Downtown Austin emerges as a complex hotspot for urban safety where multiple high-risk POI types overlap. This research advances urban design and planning knowledge by providing empirical evidence that environmental factors’ influence on safety is spatially conditional rather than universally consistent, aligning with Crime Pattern Theory and Routine Activity Theory. The findings support place-specific crime prevention strategies, offering policymakers data-driven insights for developing targeted design strategies for urban zones. Full article

Territorial transformations in Indigenous regions are shaped by intersecting ecological, political, and cultural dynamics. In San Juan Bautista Valle Nacional, Oaxaca, the construction of the Cerro de Oro dam disrupted river flows, displaced livelihoods, and triggered the decline of irrigated agriculture. This study examines the long-term impacts of these changes on land use, demographics, and cultural practices, emphasizing women’s contributions to community resilience. Using a mixed-methods approach, the study integrates geospatial analysis (1992–2021), census data (2000–2020), documentary review, and ethnographic fieldwork, including participatory mapping. Results show a shift toward seasonal rainfed agriculture, fluctuating forest cover, and a rise in female-headed households. Women have emerged as central actors in adapting to change through practices such as seed saving, agroforestry, and backstrap-loom weaving. These spatially grounded practices, enacted across varied socio-ecological zones, sustain food systems, preserve biodiversity, and reinforce biocultural memory. Although often overlooked in formal governance, women’s territorial agency plays a vital role in shaping land use and community adaptation. This research highlights the need to recognize Indigenous women’s roles in managing change and sustaining territorial heritage. Acknowledging these contributions is essential for building inclusive, culturally grounded, and sustainable development pathways in regions facing structural and environmental pressures. Full article

This study investigates the potential of fine-tuned large language models (LLMs) to enhance geospatial intelligence by translating natural language queries into executable Python code. Traditional GIS workflows, while effective, often lack usability and scalability for non-technical users. LLMs offer a new approach by enabling conversational interaction with spatial data. We evaluate OpenAI’s GPT-4o-mini model in two forms: an “As-Is” baseline and a fine-tuned version trained on 600+ prompt–response pairs related to geospatial Python scripting in Virginia. Using U.S. Census shapefiles and hospital data, we tested both models across six types of spatial queries. The fine-tuned model achieved 89.7%, a 49.2 percentage point improvement over the baseline’s 40.5%. It also demonstrated substantial reductions in execution errors and token usage. Key innovations include the integration of spatial reasoning, modular external function calls, and fuzzy geographic input correction. These findings suggest that fine-tuned LLMs can improve the accuracy, efficiency, and usability of geospatial dashboards when they are powered by LLMs. Our results further imply a scalable and replicable approach for future domain-specific AI applications in geospatial science and smart cities studies. Full article

Saproxylic beetles are key bioindicators of forest ecosystem quality and play essential roles in deadwood decomposition and nutrient cycling. However, their populations are increasingly threatened by habitat fragmentation, deadwood removal, and climate-driven environmental changes. For this reason, an integrated sampling method can increase the detection of species with varying ecological traits. We evaluated the effectiveness of integrative sampling methodologies to assess saproxylic beetle diversity within Sila National Park, a Mediterranean forest ecosystem of high conservation value, specifically in two beech forests and four pine forests. The sampling methods tested included Pan Traps (PaTs), Malaise Traps (MTs), Pitfall Traps (PTs), Bait Bottle Traps (BBTs), and Visual Census (VC). All specimens were identified to the species level whenever possible, using specialized dichotomous keys and preserved in the Entomological Collection TB, Unical. Various trap types captured a different number of species: the PaT collected 32 species, followed by the PT with 24, the MT with 16, the VC with 7, and the BBT with 5 species. Interestingly, biodiversity analyses conducted using PAST software version 4.17 revealed that PaTs and MTs recorded the highest biodiversity indices. The GLMM analysis, performed using SPSS software 29.0.1.0, demonstrated that various traps attracted different species with different abundances. By combining multiple trapping techniques, we documented a more comprehensive community composition compared to single-method approaches. Moreover, PaTs, MTs, and PTs recorded 20%, 40%, and 33% of the Near Threatened species, respectively. We report new records for Sila National Park, including the LC species Pteryngium crenulatum (Curculionidae) and the NT species Grynocharis oblonga (Trogossitidae). For the first time in Calabria, the LC species Triplax rufipes (Erotylidae) and the NT species Oxypleurus nodieri (Cerambycidae) and Glischrochilus quadrisignatus (Nitidulidae) were collected. Our results emphasize the importance of method diversity in capturing species with distinct ecological requirements and highlight the relevance of saproxylic beetles as indicators of forest health. These findings support the adoption of multi-method sampling protocols in forest biodiversity monitoring and management programs, especially in biodiversity-rich and structurally heterogeneous landscapes. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

Rapid urbanization and demographic shifts present significant challenges to spatial justice in green space provision. Traditional static assessments have become increasingly inadequate for guiding park planning, which now requires a dynamic, future-oriented analytical approach. To address this gap, this study incorporates population dynamics into urban park planning by developing a dynamic evaluation framework for park accessibility. Building on the Gaussian-based two-step floating catchment area (Ga2SFCA) method, we propose the human-population-projection-Ga2SFCA (HPP-Ga2SFCA) model, which integrates population forecasts to assess park service efficiency under future demographic pressures. Using neighborhood-committee-level census data from 2000 to 2020 and detailed park spatial data, we identified five types of population change and forecast demographic distributions for both short- and long-term scenarios. Our findings indicate population decline in the urban core and outer suburbs, with growth concentrated in the transitional inner-suburban zones. Long-term projections suggest that 66% of communities will experience population growth, whereas short-term forecasts indicate a decline in 52%. Static models overestimate park accessibility by approximately 40%. In contrast, our dynamic model reveals that accessibility is overestimated in 71% and underestimated in 7% of the city, highlighting a potential mismatch between future population demand and current park supply. This study offers a forward-looking planning framework that enhances the responsiveness of park systems to demographic change and supports the development of more equitable, adaptive green space strategies. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

Formative research is an essential component of higher education, aimed at developing research competencies in students, with an emphasis on critical thinking, academic autonomy, and analytical capacity. Its purpose is not the production of original knowledge but the systematic preparation for research activity. Within this framework, the objective of this study is to analyze how conceptual appropriation, which encompasses theoretical, methodological, procedural, and normative knowledge, is related to students’ perceived research skills. This study is grounded in the imperative of fostering higher education that cultivates critical, autonomous, and ethically responsible researchers. For this purpose, a quantitative methodology was used, with a non-experimental and correlational design, applying a census sampling to 10,536 students from a higher education institution. Data were collected through a structured survey on conceptual appropriation and perceived research skills. After the removal of inconsistent records, the data were processed statistically using non-parametric tests, particularly Spearman’s correlation, due to the non-normal distribution of the variables. The results reveal strong and significant correlations between conceptual appropriation and key research skills such as hypothesis formulation, critical thinking, and motivation for research, demonstrating that greater conceptual mastery promotes a more solid and engaged research training. These findings reinforce the need to systematically and progressively integrate research content into the university curriculum, fostering an authentic, reflective, and contextualized education. Full article

Geographic disparities threaten equitable access for children to health-promoting safe green spaces, and quality early education in the communities in which they live and grow. To address gaps in the field, we integrated the fields of developmental psychology, public health, and environmental science to examine, at the population level, associations between the environmental burden, socioeconomic vulnerability, and kindergarten readiness in a diverse urban county. Three administrative datasets were integrated through an early childhood data sharing research partnership in Miami-Dade County. The Bruner Child Raising Vulnerability Index, the five domains of the Environmental Burden module from the Environmental Justice Index, and public school kindergarten readiness scores were aggregated at the census tract level. Analysis of variance and multiple regression analyses found associations between socioeconomic vulnerability and race/ethnicity. The socioeconomic vulnerability levels were highest in census tracts with a higher percentage of Black residents, compared to all other races/ethnicities. Areas of greater social vulnerability had lower kindergarten readiness and a higher environmental burden. A higher environmental burden predicted lower kindergarten readiness scores above and beyond race/ethnicity and socioeconomic vulnerability. The findings advance our understanding of global challenges to sustainable healthy child development, such as the persistence of a disproportionate environmental burden and inequitable access to resources such as green spaces and early education programs. The present study results can inform community health improvement plans to reduce risk exposures and promote greater access to positive environmental and educational resources for all children. Full article

This study proposes a novel method to assess urban park accessibility by incorporating perceived utility based on both park area and distance. Departing from conventional models that treat accessibility as a function of geometric proximity alone, we define park utility as a distance-discounted benefit of park area, thereby allowing for a more behaviorally grounded measure. A customized discounting function is introduced, where larger park sizes proportionally reduce perceived travel cost, and walking speed adjustments are applied based on demographic user profiles (children, adults, and older adults). The methodology was implemented using a Python-based v.3.12.9 geospatial workflow with network-based distance calculations between 18,614 census block groups and all urban parks in Seoul. Population-weighted utility scores were computed by integrating park size, distance, and age-specific mobility adjustments. The results reveal significant intra-urban disparities, with a citywide deficit of 4,066,046 m in population-weighted distance, particularly in areas with large populations but insufficient proximity to high-utility parks. Simulation analyses of 30 candidate sites demonstrate that strategic park placement can yield substantial utility improvements (maximum gain: 493,436 m), while indiscriminate expansion may not. These findings offer spatial decision support for optimizing limited public resources in urban green infrastructure planning and underscore the need to consider both park scale and user-specific walking behavior in evaluating accessibility. Full article

This study focuses on a subtropical evergreen broad-leaved forest in China, utilizing a large permanent plot established in the Yaoluoping National Nature Reserve. By integrating data from a full-stem census and total station surveying, we analyzed the phylogenetic structure of the plant community as a whole and across different life-history stages (saplings, juveniles, and adults) while quantitatively assessing microtopographic variables and an interspecific competition index. The results indicate that the overall community in the Yaoluoping plot exhibited a weakly overdispersed pattern, and key microtopographic factors—including aspect, terrain position index (TPI), terrain ruggedness index (TRI), roughness, and flow direction—significantly influenced the evolution of phylogenetic structure. Distinctions were also observed among saplings, juveniles, and adults in phylogenetic structuring across life-history stages. Specifically, saplings displayed a higher degree of phylogenetic clustering, significantly influenced by density, elevation, TPI, and flow direction—suggesting that environmental filtering predominates at this stage, possibly due to lower environmental tolerance, limited dispersal ability, and conspecific negative density dependence. In contrast, juveniles and adults showed a more dispersed phylogenetic structure, with density, interspecific competition, aspect, TRI, TPI, and roughness significantly correlated with phylogenetic patterns, indicating that competition and niche differentiation become increasingly important as trees mature and establish within the community. Interspecific competition was found to play a crucial role in community structuring: the competition index was generally negatively correlated with the net relatedness index (NRI) and nearest taxon index (NTI) in juveniles and adults, implying that intense competition leads to the exclusion of some species and reduces overall diversity, with the strength and significance of competitive effects differing across stages. This study enhances our understanding of the complex interplay between microtopography and interspecific competition in shaping the phylogenetic structure and diversity of subtropical evergreen broad-leaved forests, elucidates the coupled mechanisms among microtopography, phylogenetic structure, and competition, and provides a scientific basis for forest conservation and management. Full article

The rapid advancement of environmental DNA (eDNA) technology has transformed ecological research, particularly in aquatic ecosystems. However, the optimal sampling matrix (e.g., water or sediment) and the potential for eDNA to replace or complement traditional underwater visual census (UVC) remain unclear. Here, we integrate water eDNA, sediment eDNA, and UVC approaches to systematically compare the diversity of benthic macrofauna in the subtidal zones of the Nanji Islands, China. Our results show that sediment eDNA samples exhibited the highest species richness, while UVC had the lowest. Each method revealed distinct species profiles, with relatively few shared taxa at the order level and below. Environmental eDNA showed significant advantages in detecting key phyla such as Annelida and Arthropoda. In contrast, traditional UVC was crucial for identifying certain taxa, such as Bryozoa, which were undetectable by eDNA methods. The low overlap in species detected by these methods underscores their complementary nature, highlighting the necessity of integrating multiple approaches to achieve a more comprehensive and accurate biodiversity assessment. Future research should focus on refining eDNA techniques, such as developing more universal primers, to further enhance their applicability in biodiversity monitoring. Full article