Search Results (3,530)

This study presents the first comprehensive soil gas survey across southern Uruguay’s H₂ prospective terranes. A pre-field trip selection was done on the basement rock nature, as well as vegetation anomalies in subcircular depressions and fault presence. The Neoproterozoic terrane, north of Punta del Este, and the Archean Rio de la Plata Craton, north of Montevideo, as well as along the suture zones between the two, were targeted. Our findings reveal substantial H₂ concentrations, significantly outperforming many established basins worldwide. The suture zones act as critical migration conduits for H₂ coming from a deeper structural level. Slightly abnormal helium signatures confirm an active, deep-sourced fluid system, particularly within the Sierra Ballena and Cordillera shear zones. The Archean Rio de la Plata Craton appears promising but has only been partially sampled and warrants further investigation. These results underscore the high potential of Uruguay as a new frontier for natural hydrogen exploration. Full article

The easily defanged myth that baby rattlesnakes (genera Crotalus and Sistrurus) are more dangerous than adults has persisted in North America despite all evidence to the contrary. The most often cited reason for the babies-more-dangerous (BMD) myth is the venom-dump (VD) hypothesis: babies, in contrast to adults, cannot control how much venom they expend, and therefore inject all of it when biting. We undertook three approaches to explore the origin, transmission, and prevalence of this myth and its most frequent explanation. First, we examined historical newspaper accounts. From 130 newspaper stories mentioning the relative danger of baby rattlesnakes, we identified a timeline in which (1) most stories prior to 1969 were factually correct; (2) the BMD myth and VD hypothesis likely originated in the mid-to-late 1960s and became entrenched in California, especially, from 1970 to 1999; (3) factually incorrect statements subsequently prevailed throughout North America from 2000 to 2014; and (4) factually correct stories regained prominence with apparent effective messaging success from 2015 onward. We further learned that general information stories about rattlesnakes, more often citing subject experts like university professors, were much more likely to provide accurate information than local snakebite stories, which more often cited health professionals (e.g., physicians, veterinarians, pharmacists) and emergency responders (e.g., police and fire officers) who frequently supplied misinformation. Second, we surveyed familiarity with the BMD myth and VD hypothesis among 53 university classrooms (including one high school) representing 3751 students across 29 states within the United States. Consistent with the California media’s outsized influence on misinformation transmission, familiarity with the myth was greatest in the southwestern states (52.6%) and declined moving north and east, with the least familiarity in the northeastern states (16.4%). Third, a small survey of 75 emergency responders and health professionals from Southern California revealed that a whopping 73.3% actually believed the BMD myth. Numerous organizations generally regarded as authoritative further amplified the misinformation, especially on the internet, where some content persists to this day. Unfortunately, belief in the BMD myth and VD hypothesis can lead to negative consequences, including misinformed risk-taking by those encountering snakes, unwarranted fear among snakebite victims, and inappropriate care delivered by misinformed or patient/family-pressured medical professionals. Our findings target health professionals and emergency responders as priority audiences for education. Full article

Cryphalus dilutus is an emerging invasive pest of tropical and subtropical regions, with Mangifera indica and Ficus carica being its primary host plants. Larval damage caused by this insect can lead to severe tree wilting, posing a direct threat to agricultural production and ecological security. Native to South Asia, C. dilutus has established introduced populations in the Near East, Mexico, and other areas. In recent years, it has invaded multiple regions, including southern China and southern Italy. Given the widespread global distribution of host plants and the intensification of climate change, their distribution ranges are expected to expand. However, research assessing the potential global geographical distribution of this pest under climate change is lacking. In this study, we used the Random Forest model to predict the potential distribution range of C. dilutus. Under historical climatic conditions between 1970 and 2000, suitable climatic regions for C. dilutus were primarily distributed across southern China, southeastern Brazil, southeastern Mexico, the Congo Basin periphery, and the Iberian Peninsula, with a total area of 12,192.42 × 10⁴ km². The Temperature Annual Range and Precipitation of Warmest Quarter were identified as key environmental determinants that shaped its distribution. Under the future RCP4.5 climate scenario projected for the 2050s, the total suitable area for C. dilutus is projected to contract. Specifically, high-, medium-, and low-suitability areas are projected to decline by 52.77%, 62.39%, and 24.02%, respectively. While the total area of the very low zones is expected to increase, the total area of the suitable region has been reduced to 11,891.17 ×10⁴ km². Future climate change is expected to drive the distribution northward to high-altitude areas and inland areas. Model projections indicate a poleward expansion of the fundamental climatic niche, with climatic suitability increasing in high-latitude and high-altitude regions, such as Northern Europe and western North America. Conversely, current core tropical habitats in the Indian subcontinent and the Amazon Basin are projected to face significant habitat degradation due to thermal stress. Agricultural regions previously considered relatively safe due to climatic constraints, such as northern China, the midwestern United States, and Eastern Europe, may face new challenges from pest infestation. These findings underscore the importance of proactive monitoring and implementation of preventive measures. This provides crucial decision support for countries and regions to formulate precise pest control strategies and offers a theoretical basis for early monitoring and prevention of cross-border invasions on a global scale. Full article

Gastronomic tourism heritage represents a significant segment of intangible cultural heritage, reflecting traditional knowledge, local identity, and long-standing culinary practices. The contemporary development of digital technologies, particularly artificial intelligence (AI), opens new possibilities for its preservation, documentation, and sustainable interpretation within cultural tourism. The aim of this research is to examine the role of artificial intelligence as a tool for preserving gastronomic tourism heritage from the perspective of local community members in Bosnia and Herzegovina, Serbia, and North Macedonia, regions characterised by shared gastronomic and cultural traditions. The study was conducted using a quantitative research design based on a structured questionnaire administered to 571 respondents. A convenience sampling approach was applied, targeting individuals involved in the preparation, transmission, or promotion of traditional gastronomy. Data were collected through a combination of field-based and online survey distribution. The analysis focuses on respondents’ perceptions of AI applications in documenting traditional recipes, interpreting gastronomic heritage, and promoting it within tourism, as well as on attitudes related to authenticity and cultural identity preservation. The findings indicate that, within the surveyed sample, artificial intelligence is generally perceived as a useful tool for safeguarding gastronomic heritage. At the same time, respondents emphasise the importance of transparent governance, community participation, and culturally sensitive implementation in order to minimise risks of commodification and loss of authenticity. Full article

Land resources constitute the fundamental basis for human survival and a core element of social development. The quantity, quality, and ecological condition of land resources are crucial for human well-being and sustainable development, and they make significant contributions to achieving the United Nations Sustainable Development Goals (SDGs). However, the influence of land ecological quality on the implementation of the SDGs has not yet been fully clarified. This study utilizes 1 km spatial resolution geospatial data and statistical data to construct a land ecological environment quality evaluation index system based on the Pressure–State–Response (PSR) model, analyzing the spatiotemporal dynamics of land ecological environment quality in China from 2010 to 2020 (with five-year intervals). In addition, the Spearman correlation coefficient was employed to examine the relationships between the land ecological environment quality index (LEEQI), pressure index (PI), state index (SI), response index (RI), and the implementation of SDGs 6, 11, 12, and 15, and to further explore how geographical economic zones influence the effects of these indices on the achievement of the SDGs. The results indicate that land ecological quality in China shows a strong north–south gradient, while the east–west differentiation is relatively weak, and the overall trend is increasing. The LEEQI values ranged from 0.16 to 0.48; the PI values ranged from 0.00 to 0.24; the SI values ranged from 0.03 to 0.29; and the RI values ranged from 0.01 to 0.26. The LEEQI gap between the western and northeastern regions narrowed significantly, from 0.10 to 0.07. LEEQI and RI promote the achievement of all four SDGs, whereas PI and SI mainly promote the realization of SDGs 6, 11, and 12. The synergistic effects of the four indices on the SDGs are observed in the central, eastern, and western regions, with the most significant effects occurring in western China. Specifically, LEEQI shows the strongest correlation with SDG 6; both PI and SI exhibit synergistic effects with SDGs 12 and 15; and RI demonstrates synergistic effects with all four SDGs. These findings suggest that improving land ecological quality is crucial for advancing the achievement of the SDGs. Furthermore, given that land ecological environment quality and its dimensions exert different influences on the implementation of the SDGs across geographical economic regions, it is necessary to develop tailored and region-specific strategies, particularly in western China, where maximizing improvements in land ecological quality is crucial for promoting sustainable development. Full article

Mountain ecosystems are susceptible to climate change, and alpine treeline ecotones (ATEs) represent one of the significant responsive indicators of climate-driven environmental change. This study examines long-term spatiotemporal dynamics of the ATE across the Eastern Slopes of the Canadian Rocky Mountains (ESCR) from 1984 to 2023, with the objective of assessing whether regional climate warming has influenced ATE extent and elevation across different aspects and watersheds. Multi-decadal Landsat imagery, ERA5-Land temperature data, and topographic variables were integrated within a Google Earth Engine (GEE) framework to map ATEs using the Alpine Treeline Ecotone Index (ATEI), a probabilistic approach designed to capture transitional vegetation zones. Temporal trends were evaluated using non-parametric statistics, correlation analyses, and watershed- and aspect-based comparisons. Results indicate that the total alpine treeline ecotone (ATE) area in the ESCR was approximately 13.3% larger in 2023 than in 1984. However, the temporal evolution of ATE extent and elevation was non-monotonic, and linear trend analyses did not detect statistically significant increasing or decreasing trends over the full study period. ATE elevation and expansion exhibited pronounced spatial heterogeneity, with greater changes occurring on north- and northwest-facing slopes and within selected watersheds. In contrast, summer (July–September) temperatures increased significantly (+2.84 °C), exceeding global land-only warming rates, and vegetation greenness (NDVI) showed a strong, statistically significant positive relationship with temperature. These findings show that while climate warming has clearly increased vegetation productivity, elevational ATE dynamics remain spatially heterogeneous and temporally non-synchronous with summer temperature trends. Full article

Urban air pollution during winter is a major challenge in many cities, where emissions from residential heating lead to elevated particulate matter levels. Atmospheric dispersion modelling supports the understanding of spatial and temporal pollution behavior and enables the assessment of source contributions relevant for targeted mitigation. In this study, the ADMS-Urban dispersion model was applied to simulate hourly PM_2.5 and PM₁₀ concentrations across the city of Skopje, North Macedonia. Residential heating was the focus of the analysis, while emissions from road traffic and industrial activities were also included to ensure a realistic representation of the urban emission environment. A representative winter day was analyzed to examine the influence of wind patterns and diurnal boundary-layer height variability on particulate matter dispersion. Modelled concentrations were evaluated against measurements from urban air quality monitoring stations and showed good agreement in reproducing both night-time accumulation and daytime dispersion. The results indicate that household heating using biomass is the dominant contributor to wintertime particulate matter emissions, with PM₁₀ prevailing over PM_2.5. These findings underline the need for targeted emission reduction measures in the residential heating sector and demonstrate the usefulness of short-term dispersion modelling for supporting air quality management strategies in Skopje. Full article

Hydrologic assessment within the Southeast United States is challenging, particularly in upstream basins, necessitating improved approaches to drought forecasting and water management. Within the Tennessee Valley, dense populations intensify the need for robust hydrologic management and predictive capabilities. This study integrates dendrochronological proxy data, hindcast information, and future climate projections from the Oak Ridge National Laboratory (ORNL) to evaluate May–June–July drought regimes. Holistic hydrologic conditions were attained by integrating self-calibrating Palmer Drought Severity Index data from the North American Drought Atlas, basin-scale precipitation data from ORNL hindcasts and future predictions, and streamflow data from United States Geological Survey. Development of precipitation and streamflow reconstructions were completed using Stepwise Linear Regression, then bias-corrected and temporally smoothed using five- and ten-year moving windows. The reconstructions demonstrated strong statistical skill across all three basins (Little Tennessee River, Nantahala River, South Fork Holston River). When compared only to the hindcast, future drought is predicted to be the most severe on record, but within the context of the paleo record, while still severe, these future droughts remain inside the natural variability envelope. Findings highlight the importance of novel approaches to long-term drought monitoring, specifically integrating basins where instrumental periods are limited, and water management demands are high. Full article

In this paper, machine learning techniques and risk factor analyses are applied to a marine hazard potential map of the Taiwan Strait. The waters surrounding Taiwan are characterized by dense maritime traffic, including commercial cargo transportation and fishing operations. Marine accidents caused by severe weather conditions are frequently reported, leading to irreversible loss of life and property. To mitigate these risks, this study utilizes the XGBoost machine learning model in conjunction with oceanic parameters and historical accident statistics to map the risk potential distribution of maritime accidents across the Taiwan Strait on a monthly basis. To address the challenge of limited historical accident data, this research employs a TVAE (Tabular Variational Autoencoder) to generate synthetic maritime accident data. The quality of such synthetic data is evaluated by comparing the similarity of probability distributions between the original and synthetic datasets. The resulting risk potential maps indicate that risk levels are significantly higher during the winter and lower during the summer. Furthermore, the SHAP (SHapley Additive exPlanations) model is applied to analyze key risk factors, identifying wave height as the primary driver, followed by meridional (north–south) wind speed and the primary spatial modes of wave height. These findings are validated using the National Ocean Database and Sharing System (NODASS) data, providing a comprehensive explanation of the underlying physical mechanisms. This study has successfully utilized the XGBoost machine learning model together with the TVAE generative technique to develop monthly marine hazard potential distribution maps for the Taiwan Strait. The novel research flowchart employed in this study can be applied to many other marine problems. Full article

Groundwater is a critical component of the terrestrial water system, and understanding the spatiotemporal evolution of national groundwater storage is essential for ensuring water security and ecological sustainability in China. Based on GRACE and GRACE-FO satellite gravity data from January 2005 to December 2024, combined with land surface water components derived from GLDAS, this study investigates the spatiotemporal variations and driving mechanisms of groundwater storage anomalies (GWSAs) across China using parametric additive decomposition, Theil–Sen trend estimation, and the Mann–Kendall significance test. The results indicate that: (1) groundwater storage in China has experienced a persistent decline at an average rate of −1.97 mm yr⁻¹, with a cumulative depletion of 38.55 mm. This decline exhibits distinct phases, characterized by a rapid decrease during 2005–2011, a moderated decline during 2012–2017, and a renewed acceleration with increased variability during 2018–2024; (2) spatially, GWSA shows a pronounced “increase in the south and decrease in the north” pattern, with extremely significant declines concentrated in the North China Plain and arid northwestern inland regions, while significant increases are mainly observed in southwestern China and southeastern coastal areas; (3) GWSA exhibits a stable seasonal cycle of “summer surplus and spring deficit,” with groundwater replenishment driven by summer precipitation and substantial depletion caused by agricultural water demand in spring; and (4) groundwater variations in northern China are primarily controlled by intensive agricultural irrigation, resulting in sustained depletion, whereas southern China is mainly influenced by natural precipitation, maintaining a relatively dynamic equilibrium. These findings provide valuable insights for region-specific groundwater management and the sustainable utilization of water resources in China. Full article

The integration of intangible cultural heritage (ICH) and tourism development (TD) is regarded as a crucial national strategy for China’s sustainable development, as their synergistic relationship is considered pivotal for regional progress. A coupling coordination evaluation system was constructed. Kernel density estimation, entropy method, coupling coordination degree (CCD) and relative development degree (RDD) models, and a tobit model were employed to examine the spatiotemporal characteristics and influencing factors of ICH–TD integration in Sichuan Province. Key findings are as follows: (1) Sichuan is endowed with abundant ICH resources characterized by high heritage value and diverse typologies. However, the distribution is skewed toward traditional skills, exhibiting notable regional disparities. ICH demonstrates a “single-core, belt-shaped and multi-cluster” pattern, which is centered on Chengdu, extends along a north–south high-density belt, and forms several secondary high-density clusters. (2) Temporally, the CCD demonstrates a sustained upward trend, whereas the RDD transitions from ICH-lagged to TD-lagged. Spatially, the number of high coordinated cities increases annually, expanding radially from regional centers, while central-eastern regions consistently outperform the west. (3) Regarding influencing factors, comprehensive economic strength, distribution of industrial structure, overall level of urbanization, and transportation accessibility exert significant positive effects on the CCD, with comprehensive economic strength demonstrating the strongest influence. This study contributes to the theoretical understanding of ICH–TD synergy and provides policy-relevant guidance for integration. Full article

Agrivoltaic systems integrate solar electricity generation with agricultural production on the same land and have emerged as a promising strategy to address land-use conflicts between food and energy systems. This PRISMA-based systematic review synthesizes evidence from 249 peer-reviewed studies published between 2010 and 2025, applying an integrated three-dimensional framework that simultaneously examines technical efficiency, environmental sustainability, and institutional governance. The results show that agrivoltaic systems consistently achieve superior land-use performance, with Land Equivalent Ratio values typically ranging between 1.2 and 1.8, indicating 20–80% greater territorial efficiency than separate agricultural and photovoltaic systems. In water-stressed regions, reported improvements in water-use efficiency commonly reach 15–30%, while life-cycle assessments indicate substantial reductions in greenhouse gas emissions and other environmental impacts. The integrated analysis also reveals important design-dependent trade-offs related to panel density, crop selection, and local agroclimatic conditions. Despite their demonstrated technical and environmental maturity, the large-scale deployment of agrivoltaic systems remains constrained by institutional barriers, including the lack of dedicated regulatory frameworks, fragmented agricultural and energy policies, and the strong geographical concentration of research in the Global North, with limited evidence from Latin America and other regions of the Global South. Overall, the findings indicate that agrivoltaic systems represent a credible component of integrated land-use and energy transition strategies, but their responsible scaling will depend primarily on advances in governance, policy alignment, and context-specific system design. Full article

Species composition is an important indicator for the condition, functioning, and ecosystem service provision of salt marshes, making the mapping of species composition valuable for their management. Previous studies have demonstrated that the combined use of unoccupied aerial vehicle (UAV)-mounted multispectral cameras and machine learning (ML) can provide effective mapping of vegetation communities in these habitats. However, to date, these studies have predominantly focused on relatively species-poor salt marshes in North America. There has been no published testing of these combined UAV-ML methods in the salt marshes of northwestern Europe, which contain different often more diverse assemblages. Consequently, this study investigated whether applying recent methodological advances can accurately map National Vegetation Classification communities in three locations in the United Kingdom, each comprising two salt marsh sites, one established and one restored. Sites consisted of a mix of established and restored salt marshes of different ages, enabling a complementary assessment of how these methods perform in communities at different stages of development. The applied random forest ML models were found to produce highly accurate maps of salt marsh vegetation communities, with a mean overall accuracy of 94.7%. No relationship was found between the age of restoration sites and the accuracy of the classifications, showing these methods may be applied at a range of stages of community development and offer wider applicability for saltmarsh management and monitoring. The findings of this study demonstrate that advances in the combined use of drones and machine learning provide a readily transferrable method for mapping standardised vegetation communities in both established and restored northwestern European salt marshes and therefore likely other salt marshes globally. Consequently, this study demonstrates that both researchers and practitioners may confidently use these methods to create improved assessments of both marsh condition and function. Full article

An increasing number of municipalities are adopting urban digital twins (UDTs) to improve urban management. Although the models differ widely, municipalities face similar challenges in their implementation. Therefore, sharing insights on UDTs provides an opportunity for collective growth. To facilitate this growth, the present exploratory study maps the characteristics, challenges, and potentials of 99 UDTs in Europe, North America, and Asia. We first estimate the UDT readiness based on established features, along with contextual and local authority involvement indicators. Next, we conduct semi-structured interviews with key individuals from eight selected cities to contextualize the review findings. The mapping results indicate that most UDTs in our sample operate at the municipal level, and that over half (57%) are not in series operation. The reviewed UDTs are mid-level in maturity, and local authority involvement is a key driver of scalability. We infer that UDT progress depends as much on common frameworks, organizational readiness, governance capacity, and relevant data as on technology. Collaborations with private companies and researchers can play a central role in the long-term sustainment and growth of UDT infrastructures. Full article

This study explored the experiences, perspectives and confidence of teaching and research staff of discussing race and ethnicity, and associated equalities matters, at a post-1992 university in North West England, UK. In particular, it studied whether colleagues, who were largely white, had the understanding and personal skills to deliver on race equity in teaching and learning in a Higher Education Institution (HEI). Further, it examined whether there was a disconnect between the intention of an HEI working towards the Race Equality Charter (REC) mark and the detrimental effects this may have on its minoritised ethnic staff. The study was based on focus groups and interviews of 43 academic staff as participants using Critical Race Theory (CRT) and Intersectionality as the theoretical lens. These address discrepancies between institutional declarations and realities within higher education, which is important, as HEIs are increasingly positioning themselves as committed to diversity and equity, while the practical implementation often remains inconsistent. The findings demonstrate that the white participants were not confident, competent or pro-active enough to effect any meaningful change in race equity. At the same time, the minoritised ethnic participants often felt the burden of having to relive the trauma and pain of racism and take the lead in any race equity initiatives. In sum, the study demonstrates that HEI initiatives that purport to tackle systemic racism through decolonisation and the REC mark have little chance of effecting institutional change if the staff do not have the confidence, competence and necessary skills to make it happen. Full article