Search Results (5,925)

Dengue virus infection is a febrile illness caused by the Orthoflavivirus Dengue, which is transmitted by the mosquitoes Aedes aegypti or Aedes albopictus. Despite the fact that Dengue virus (DENV) is present in tropical and subtropical areas, climate change with global warming has been associated with the spread of Aedes aegypti and Aedes albopictus mosquitoes in several other regions worldwide. Notably, as the presence of Aedes albopictus has been confirmed in Southern Europe, already locally transmitted cases of Dengue virus infection have been reported in Europe. Apart from Europe, Australia has reported DENV cases in the 21st century that have been associated with the transmission of Aedes aegypti in the neighboring islands. Climate change, namely increasing temperatures, higher humidity and rainfalls, together with the development of urban heat islands, uncontrollable deforestation and urbanization, travelling and trade, has contributed significantly to the spread of DENV infection. Modern diagnosis based upon the advent of “multi-omics” techniques and machinery learning programs will be of the utmost importance for the early and accurate diagnosis of DENV infection. Finally, preventive measures for controlling Dengue virus infection, such as the use of repellents, educational programs, and improvement in water storage and waste management at the community levels would be very useful. Regarding climate change, the One Health Approach by integrating collaboration of various sectors and raising public awareness seems to be of the utmost importance in this context. Further investigations regarding the development of antiviral agents and vaccines will be an important asset in our armamentarium against DENV infection. Full article

Mediterranean-type forest ecosystems are becoming increasingly vulnerable to intensifying drought, threatening the resilience of even highly adapted ecosystems such as the Northern Jarrah Forest in south-western Australia. This study quantifies multi-decadal dynamics of canopy water stress using a 36-year multispectral satellite archive (1988–2024) and the newly developed Infrared Canopy Dryness Index (ICDI). We combined this spatiotemporal dataset with a MaxEnt-based risk assessment framework to identify the biophysical drivers of drought-induced canopy loss and to delineate high-risk zones under accelerating climate-forcing changes. Our results demonstrate a systematic spatial expansion of canopy dryness, paralleling a deteriorating regional climatic water balance. Hotspot analysis revealed a transition from localized, peripheral stress to widespread, chronic drought conditions across the landscape. The modelling achieved high diagnostic accuracy (AUC = 0.952), significantly outperforming conventional assessment methods. Regolith depth was identified as the primary determinant of drought-induced canopy collapse, followed by ICDI, NDVI, and slope. Crucially, high-biomass stands exhibited disproportionately higher risk of collapse, revealing a density-dependent vulnerability that suggests productive forests are approaching critical hydraulic thresholds. Conversely, lower-stature forests to the east of the study area demonstrated greater stability, likely due to reduced evapotranspirative demand. These findings provide robust spatial evidence for transitioning from reactive monitoring to proactive forest management. We conclude that targeted interventions, such as ecological thinning and prescribed burning in identified high-risk zones, are imperative to protect the forest and preserve the structural integrity of Mediterranean ecosystems in a drying climate. Full article

Due to climate change and rapid urbanization, cities worldwide face the dual challenge of improving flood resilience and providing accessible green space within limited land resources. Sponge City parks offer a landscape-based approach for integrating stormwater management with park services. However, how park morphology structures this combined performance remains insufficiently understood. This study examines 26 Sponge City parks in Shanghai and evaluates how node-, line-, and patch-type morphologies are linked to stormwater storage and service provision. Using geospatial analysis, DEM-derived catchment delineation, land-cover interpretation, and statistical analysis, this study compares estimated stormwater storage, storage efficiency, local park availability, and land-cover composition across different park morphologies. The results show that estimated performance of stormwater management and park service provision vary across morphological types, but these differences do not follow a simple node–line–patch hierarchy. Rather, the observed patterns are jointly shaped by park morphology, catchment setting, land-cover allocation, and surrounding urban context. These findings suggest that Sponge City parks should not only be evaluated by total stormwater storage. Their contribution depends on morphology, scale, catchment setting, land-cover allocation, and urban context. The study provides a morphology–performance perspective to support more differentiated planning of multifunctional green infrastructure. Full article

Mediterranean regions are forecasted to be increasingly threatened by climate change, leading to the occurrence of extreme events. One strategy to improve the resilience of agricultural systems is to introduce rotations that combine legumes and crops with high intraspecific diversity such as evolutionary populations (EPs). These cropping systems may be characterized by lower external input needs and higher buffering capacity than traditional ones. Our objective was to test if the introduction of wheat EPs impacts soil microbial functions—including microbial biomass, community structure, and enzymatic activity—and soil organic matter composition within a crop rotation framework. We conducted a two-year field experiment at two sites in Italy comparing a modern bread wheat variety to two EPs, evolved in different areas, in rotation with legumes. The composition and processes of rhizosphere microbial communities were characterized using EL-FAME and enzyme activities. In addition, rhizosphere soil organic matter signatures were measured by mid-infrared spectroscopy, and their relationships with microbial parameters were investigated using principal component analyses. The results showed that the EP–rhizosphere relationship, as well as its influence on microbial abundance and activity, is dependent both on the site of origin and local pedoclimatic conditions, although no consistent response was observed across the two sites. These effects may be buffered by the choice of the preceding crop in rotation. Full article

Climate hazards increasingly unfold as information crises alongside physical impacts, producing rapid shifts in what people search for and discuss online. This case study demonstrates how AI-supported analysis of online data can complement conventional disaster intelligence by providing a scalable social sensing layer for climate hazard resilience in Galicia. It integrates Google Trends as a proxy for changing public attention and information demand, and YouTube videos and comment threads to capture public sensemaking and resilience-relevant signals. Monthly Google Trends series were used for eight hazards, with floods showing the highest mean interest, followed by wildfires and heatwaves. For the three highest-salience hazards, the study analyzed YouTube comments using gpt-5-mini to extract sentiment, emotions, topics, institutional trust cues, collective efficacy cues, calls to action, impacts, vulnerable groups, and coping actions. The corpus included 184 heatwave comments, 20,427 wildfire comments, and 4882 flood comments. Across hazards, discourse is predominantly negative but differs in structure. Heatwave threads skew toward mockery and normalization, wildfire threads center on anger, governance and low institutional trust, and flood threads combine solidarity with demands for localized warnings and guidance. The study translates comment-level signals into traceable policy recommendations emphasizing actionable risk communication, early warning and response capacity, and trust-building practices. The study concludes with an operational pipeline concept for continuous monitoring and dashboard-based decision support, while emphasizing limitations related to Google Trends sampling and normalization, platform and API biases, and model-mediated uncertainty. Full article

Remote-sensing land surface deformation (LSD) is a powerful and effective approach for investigating regional alpine permafrost variations. However, alpine permafrost is often distributed in areas characterized by earthquakes, and the LSD of alpine permafrost is potentially contaminated or diminished by earthquake-related LSD. Therefore, this study aimed to derive the effective LSD in the alpine permafrost of the Source Area Yellow River (SAYR) by removing LSD originating from the M_w 7.4 Maduo earthquake in 2021-05-22 and analyzing the spatiotemporal variations in LSD during 2017–2024. Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) was used to obtain the initial LSD time series from Sentinel-1 images acquired during 2017–2024. The LSD of the M_w 7.4 Maduo earthquake, its aftershocks and the post-seismic relaxation in SAYR was simulated separately by considering its temporal process and removed from the LSD time series in SAYR. The final LSD was validated against in situ Global Navigation Satellite System (GNSS) measurements, and the spatiotemporal variations in LSD in SAYAR were subsequently analyzed. The study found the following: (1) the removal of the earthquake-related LSD was successful both spatially and temporally and the final LSD has mean absolute error (MAE) of 3.22 mm and root mean squared error (RMSE) of 3.92 mm; (2) during 2017–2024, the vertical LSD in SAYR was mostly −8–8 mm/y; (3) soil moisture determined the spatial distribution of the LSD direction in SAYR as a result of local drainage conditions, air temperature, precipitation and snow melt. This study demonstrated the necessity of removing the earthquake-related LSD when investigating the alpine permafrost LSD in tectonically active areas. The strategy adopted in this study serves as a technical reference for future investigations of this kind. The findings in this study provide insight for a thorough understanding of permafrost evolution on the Tibetan Plateau in the context of climate change. Full article

In the context of dynamic environmental changes, accurate geospatial information is fundamental for evidence-based decision-making in land-use planning. As urban areas undergo rapid structural transformations, characterizing their spatial morphology becomes essential for assessing ecosystem conditions and identifying pressure points within the urban–rural gradient. Drawing on the indicators for ecosystem condition and pressure recommended by the Mapping and Assessment of Ecosystem Services (MAES) framework, reflecting their trends, this study presents a methodology for comprehensive geospatial mapping of urban and peri-urban morphology, using the Functional Urban Area (FUA) of Burgas, Bulgaria, as a case study. The approach enables multi-scale spatial analysis (regional and local), integrates the structure and functions of urban ecosystems, and reveals the spatial heterogeneity of complex socio-economic systems. At the regional level, ecosystems within the FUA were identified using the national land-use/land-cover database. At the local level, within the city of Burgas, urban morphology was classified by combining building and land-cover types into 14 distinct urban morphological zones (local climate zones—LCZs) using high-resolution unmanned aerial vehicle (UAV)-based orthophotos. This precise spatial data allowed for a detailed assessment of the balance between pervious and impervious surfaces within each LCZ. By integrating Google Earth Engine (GEE) data, the appropriate conditions and pressure indicators in the case study are assessed. Regional ecosystem pressure is effectively captured through the spatial distribution of the Final Pressure Index (IPr). Concurrently, the Urban Ecosystem Performance Index (UEPI) highlights sharp spatial polarization, with critical stress concentrated in the industrial and port zones of the urban core. The results provide policy-makers and stakeholders with critical insights into current pressures and environmental changes in urban and peri-urban ecosystems, offering a robust foundation for evidence-based management and climate change adaptation strategies. Full article

Compact urban form can reduce road transportation GHG emissions and mitigate resource supply bottlenecks associated with mass EV adoption. Global databases from Climate TRACE and the Global Human Settlement Layer are utilized to develop the Compact Urban Form Estimation Tool or CUFET for calculating the reduction in VKT and road transportation GHGs from shifting toward CUF. The CUFET does not explicitly account for mechanistic changes in driving (e.g., modal shift) but rather uses settlement density as a coarse proxy for walking and transit urban fabrics. VKT was modeled using weighted least squares regression from the independent variables settlement population, settlement population density, and country fixed effects. Population size banding was introduced to the model to improve explanatory power. The model was developed using 10,495 settlements in the 2021 Climate TRACE dataset. The CUFET VKT model was able to explain 78% (p < 0.001) of the variation in the VKT of test settlements and improved with the addition of a country fixed effect. The CUFET on average gave estimates of VKT within 24% of Climate TRACE-calculated VKT for countries with a GDP per capita between $20,000 and $45,000 and average estimates within 20% for countries with a GDP per capita above $45,000. Increased settlement density was associated with more substantial reductions in VKT in small (50,000 to 88,335) and medium (88,335 to 329,480) sized settlements relative to large (>329,480) settlements. Higher variability was observed in VKT estimates of small settlements. The CUFET VKT was validated by backcasting historical VKT data from 1960 to 2000. The backcasting exercise used historical administrative boundaries and only included high economic output nations (GDP per capita above $20,000 in 2021 USD). Despite these limitations, backcasting achieved a % difference of ~20% for settlements after 1990, suggesting the model can make useful estimates within 30 years of the model calibration year for high economic output nations. The VKT model was used to calculate emissions using a settlement-specific emissions factor. Settlements with annual road transportation emissions per capita greater than 2 t CO₂eq have the lowest population densities relative to their populations and are mostly located in the United States, Japan, Canada, and Australia. The nations with the highest transportation emissions are also nations where the CUFET provides the most accurate VKT estimates. The CUFET aims to bridge the gap between academic consensus and local decision-making practice by reducing the barriers to estimate VKT and transportation GHG reduction from shifting to compact urban form. Full article

The African jacana (Actophilornis africanus, family Jacanidae) is a sex-role-reversed waterbird inhabiting tropical and subtropical open wetlands across Africa. Identifying environmental factors that influence nest site distribution and suitable nesting habitats is crucial for protecting species and habitat management; however, studies addressing these factors remain limited for this species. This study aimed to map suitable nesting habitats and identify the main environmental variables influencing the nest site distribution of the African jacana in Lake Hawassa, Ethiopia. We mapped nesting habitat suitability using a Maximum Entropy (MaxEnt) model and ArcGIS Pro 3.2.2 based on 78 field-collected nest data points and ten environmental variables. The model predicted a total suitable nesting habitat area of 1.25 km² with high accuracy (AUC = 0.90, CBI = 0.8, and omission rate = 0.22), representing about 1.2% of Lake Hawassa’s total area. In general, suitable nesting habitats were relatively small, fragmented, and mainly clustered along the southeastern shore of Lake Hawassa. The mean precipitation and temperature during the breeding season, slope, elevation, and distance to shoreline were the main predictors of the African jacana’s nesting habitat suitability. The results of the present study provide valuable insights into local wetland management and the conservation of African jacanas and other breeding waterbirds in Lake Hawassa. Moreover, this study establishes baseline information for assessing how future climate and habitat changes may influence breeding habitat suitability in similar Ethiopian wetlands. The present study was limited to nesting habitat suitability based on limited environmental factors and did not include nest success, pollution parameters or predation; future studies incorporating these factors may improve ecological interpretation. Full article

Rapid urbanization and climate change have severely exacerbated the urban heat island (UHI) effect in high-density subtropical megacities. Traditional linear models often fail to capture the complex, non-linear thermal responses driven by three-dimensional (3D) urban morphology and socio-ecological interactions. This study proposes a data-driven analytical framework explicitly tailored for macro/mesoscale climate-resilient urban planning to deconstruct the non-linear associations of Land Surface Temperature (LST) in Shenzhen, China. Integrating multi-source spatial data into a 500 m grid, we utilized the eXtreme Gradient Boosting (XGBoost) algorithm for high-precision LST modeling (R² = 0.7851, MAE = 1.1381 °C) and applied the SHapley Additive exPlanations (SHAP) approach for spatial interpretability. The results reveal critical non-linear thresholds: vegetation (NDVI) cooling efficiency saturates at 0.8, while impervious surfaces (ISA) transition into dominant heating drivers beyond 0.7. Notably, a synergistic effect indicates that high building volume density (BVD) significantly amplifies the marginal cooling benefits of vegetation. Furthermore, local SHAP attribution combined with K-Means clustering facilitated the delineation of four distinct thermal management zones. This framework shifts UHI mitigation from broad, uniform policies to precise, data-driven spatial diagnostics, offering actionable “one zone, one policy” strategies for sustainable architectural and climate-resilient urban planning. Full article

Climate change remains among the most pressing environmental challenges confronting the world, exerting profound pressure on both ecological systems and socio-economic development. To advance understanding of the evolution patterns and driving mechanisms governing hydroclimatic systems in arid and semi-arid regions, this study employed an integrated framework encompassing trend testing, change-point detection, periodicity and persistence analysis, and machine learning-based attribution. Focusing on the Mu Us Sandy Land from 1982 to 2023, we systematically investigated the spatiotemporal evolution, periodic characteristics, and driving mechanisms of hydroclimatic factors. Furthermore, future climate risks were assessed using CMIP6 multi-model data. The results showed that: (1) All four variables exhibited positive slopes, but only soil moisture showed a statistically significant long-term wetting trend (β = 0.025 × 10⁻³, p = 0.0008) and a clear global abrupt change in 2011; the upward tendencies of precipitation (p = 0.3946), potential evapotranspiration (p = 0.4970), and surface runoff (p = 0.1097) did not reach the 0.05 significance level. (2) Meteorological elements showed weak periodicity and strong anti-persistence (mean Hurst index = 0.379 for precipitation and 0.222 for PET), whereas hydrological elements exhibited clear seasonal–interannual periods and more random future variability with greater spatial heterogeneity (mean Hurst index = 0.436 for runoff and 0.414 for soil moisture). (3) Monthly changes were mainly associated with local surface processes. Vegetation dynamics were key predictors of precipitation, runoff, and soil moisture, while potential evapotranspiration was dominated by atmospheric demand, with limited influence from large-scale climate indices. (4) Under high-emission scenarios, imbalanced water–heat increases may lead to a higher likelihood of drought conditions. Full article

(1) Background: The rapid spatial expansion of the ruderal weed Chenopodium hybridum L. poses a potential challenge to agricultural production and regional ecosystems in China. However, the spatial evolution characteristics of its potential geographic distribution remain unclear under the compound scenarios of global warming and intensified human activities. (2) Methods: Utilizing an optimized MaxEnt model (regularization multiplier (RM) = 0.5, feature combination (FC) = LQ), this study integrated bioclimatic, topographic, soil, and Human Footprint (Hfp) data to predict the potential suitable habitats of C. hybridum in China under current conditions and four future Shared Socioeconomic Pathways (SSPs) emission scenarios (SSP126, SSP245, SSP370, and SSP585) for the 2050s and 2070s. Additionally, spatial turnover rate and centroid migration analyses were incorporated to elucidate its spatiotemporal dynamics. (3) Results: The results indicate that the optimized model exhibited robust predictive performance (Area Under the Curve (AUC) = 0.928). The Human Footprint (Hfp) was the environmental factor most prominently associated with the macro-spatial distribution of C. hybridum, with a relative contribution of 58.4%—significantly higher than any single natural geographic factor. Currently, potential suitable habitats are primarily concentrated in North, Central, and Southwest China, totaling approximately 205.59 × 10⁴ km². Under future climate scenarios, the highly suitable core habitats exhibit a consistent contraction trend, whereas the marginal suitable habitats shift spatially toward the arid inland regions of the northwest and the high-altitude areas of the southwest. By the 2070s under the higher-emission scenario (SSP585), the spatial turnover rate reaches a peak value (16.23%), and the distributional centroids of the potential suitable habitats exhibit localized directional shifts. (4) Conclusions: The spatial expansion trajectory of C. hybridum exhibits a high degree of spatial congruence with human activity corridors, reflecting a distinct macro-ecological niche spatial response characterized by shifts toward higher latitudes and elevations. It must be emphasized that the projections of this study reflect potential habitat suitability rather than definitive future actual distributions. The three-tier spatial management framework proposed herein—encompassing transport regulation, ecological management in core areas, and early warning in marginal zones—can serve as a scientific basis for the early monitoring and spatial management of this species under climate change. Full article

The iron and steel industry is one of the most energy- and emission-intensive industrial sectors, accounting for approximately 95% of global metal production and 7–9% of global CO₂ emissions. Its decarbonization is therefore central to climate change mitigation and has potential co-benefits for environmental quality and human health through reductions in air pollutants associated with conventional coal-based steelmaking. This review addresses the following question: which technological and systemic pathways can reduce emissions from iron and steel production, and what constraints limit their deployment across regions? The article synthesizes current knowledge on the dominant blast furnace–basic oxygen furnace and electric arc furnace routes, their emission intensities, and their role in global steel production. It then evaluates two complementary groups of decarbonization pathways: optimization of existing carbon-intensive processes and the transition to low- and near-zero-carbon technologies, including hydrogen-based direct reduction, electrification, carbon capture, utilization and storage. Particular attention is given to the dependence of these pathways on low-carbon electricity, hydrogen availability, scrap supply, infrastructure, policy frameworks, and regional economic conditions. The review highlights that technological readiness alone is insufficient to ensure deep decarbonization; implementation depends on the alignment of energy systems, industrial investment cycles, and climate policy. From a public health perspective, steel decarbonization should be understood as a climate mitigation measure with potential health co-benefits, particularly where it reduces both greenhouse gas emissions and local air pollution. Full article

As coastal communities face escalating climate risks driven by climate change and biodiversity loss, integrating mangrove ecosystems into sustainability-oriented governance frameworks spanning ecological conservation, climate adaptation, and natural capital accounting has become a global priority. However, quantifying their protection values based on spatiotemporal shoreline dynamics under extreme disturbance remains challenging. Focusing on Dongzhai Harbor (China), this study integrates multi-temporal remote sensing (2010–2021), shoreline evolution analysis, and the Replacement Cost Method to assess ecosystem resilience against Super Typhoon Rammasun in 2014. Results show mangroves exhibited substantial post-disturbance resilience, with only 6.10% area loss following Typhoon Rammasun and 46% natural recovery within six years. Bootstrap confidence intervals for the mangrove-shoreline association overlapped zero across all three temporal periods, indicating that the observational data do not support a statistically confirmed causal protection effect at the landscape scale. This finding underscores that spatially co-occurring ecosystem services do not automatically imply causation, reinforcing the need for empirically grounded valuation in sustainable land-use planning. Because mangroves naturally establish in sheltered environments, the observed spatial overlap between mangroves and the shoreline cannot be interpreted as direct evidence of causal shoreline stabilization. Based on this framework, the potential protection value reached 907.65 × 10⁴ CNY yr⁻¹ across 32.57 km of weighted coastline aligned with mangroves. Notably, erosional segments contributed 50.5% of this value despite comprising only 27.3% of the length, indicating that the replacement-cost estimate is concentrated in erosional segments under the assumed parameters. While acknowledging the need for local biophysical validation and uncertainty analysis in scaling, these findings support integrating dynamic nature-based solutions into territorial planning and Gross Ecosystem Product accounting. The resulting valuation framework offers a replicable pathway for advancing multi-dimensional sustainability encompassing climate-adaptive coastal governance, natural capital integration, and evidence-based coastal spatial planning. Full article

Climate change alters not only the availability of solar radiation, but also the thermal, humidity, and cloudiness conditions under which solar energy systems operate. However, limited attention has been paid to the simultaneous comparison of photovoltaic and solar thermal responses using a common hourly climate-based framework under Central European conditions. This study evaluates long-term climate-driven changes in the operating conditions of photovoltaic (PV) panels and solar thermal collectors across five Slovak locations representing contrasting local climatic and topographic settings. Hourly ERA5-Land data for 1985–2024 were used to derive climatic indicators, photovoltaic operating indicators, and solar thermal performance indicators. The analysis combined long-term Mann–Kendall and Sen’s slope trend assessment with a comparison between the reference period 1985–1994 and the recent period 2015–2024. The results show that mean air temperature increased by 1.50–1.69 °C, global horizontal irradiance by 3.24–5.66%, and high-irradiance hours increased substantially across all sites. Photovoltaic yield increased by 2.21–4.52%, but this improvement was accompanied by higher PV cell temperature, more hot operating hours, and increased temperature losses. Solar thermal collectors showed a stronger relative response, with useful thermal gains increasing by 7.27–12.33% at 35 °C and by 9.00–15.73% at 50 °C. The Relative Solar Thermal Gain Advantage was positive at all locations, indicating that recent climatic conditions favored solar thermal gain more strongly than PV yield under the applied assumptions. The findings demonstrate that recent climatic data should be used in solar-system design and that photovoltaic and solar thermal technologies require separate interpretation because they respond differently to warming and changing radiation conditions. Full article