Search Results (8,122)

Climate-change-induced drought can increase domestic water shortage not only by reducing runoff but also by exposing weaknesses in local sources, reservoirs, and wide-area transfer networks. This study simulates domestic water shortage in the Seomjin River water system, South Korea, using the Korea-Water Evaluation and Planning system (K-WEAP), and proposes an integrated eXtreme Gradient Boosting (XGBoost)–Shapley Additive exPlanations (SHAP) framework to diagnose the explanatory factors of the simulated shortage. Representative drought scenarios were selected from an ensemble of climate projections using a dryness score based on precipitation-related extreme climate indices. K-WEAP was used to simulate shortage for eleven administrative districts, and XGBoost (version 3.2.0) models were trained for districts with sufficient shortage samples. SHAP analysis and shortage-event clustering were then applied to identify dominant explanatory factors and recurrent shortage patterns. The XGBoost models reproduced the simulated shortage rates well, with test R² values exceeding 0.91. Wide-area water supply was the dominant explanatory factor in three inland districts, whereas reservoir supply was more influential in the southern coastal district. The dependence analysis revealed threshold-type responses, in which shortage risk increased sharply once key supply variables fell below district-specific critical ranges. The results indicate that domestic water shortage is governed by district-specific supply pathways and threshold-type system responses rather than by uniform basin-wide drought effects. Full article

Nature-based Solutions (NbS) are increasingly recognised as effective approaches for enhancing coastal resilience while simultaneously supporting biodiversity, ecosystem services, and, where appropriate, climate-change mitigation. Their importance is particularly evident in the Mediterranean Basin, a climate-change hotspot exposed to sea-level rise, coastal erosion, land subsidence, sediment deficits, and intense anthropogenic pressures. This review provides a structured evidence synthesis of NbS for Mediterranean coastal adaptation, integrating ecological, hydrodynamic, geomorphological, biodiversity, governance, and implementation perspectives. We examine the principal NbS typologies, including vegetated habitats, biogenic reefs, sediment-based interventions, and hybrid approaches, with particular attention to vulnerable microtidal systems such as coastal lagoons and subsiding shorelines, including the Venice Lagoon and the Emilia-Romagna coast. Drawing on peer-reviewed literature together with evidence from European LIFE projects and restoration initiatives, the review highlights how process-based interventions can restore ecosystem functioning, strengthen coastal resilience, and provide multiple ecosystem services. At the same time, the analysis emphasises that NbS are inherently context-dependent, with their effectiveness influenced by local geomorphology, sediment availability, hydrodynamic conditions, governance capacity, and long-term management. Although important scientific uncertainties remain, wider implementation is increasingly constrained by economic, institutional, and governance barriers. The review concludes that NbS should not be regarded as stand-alone alternatives to conventional engineering, but as key components of integrated and adaptive hybrid coastal management strategies capable of supporting resilient Mediterranean coastal systems under future climate change. Full article

Climate change poses severe threats to agricultural systems in the Mediterranean Basin. Portugal is particularly exposed and vulnerable to projected warming and drying trends. This study provides a high-resolution bioclimatic characterisation of six Portuguese crops: grapevine, olive, wheat, maize, potato and tomato. Bioclimatic indicators (BIOCLIM) based on the CHELSA V2.1 km scale data for the historical period (1981–2010), as well as ensemble mean projections for 2041–2070, under SSP1-2.6 and SSP5-8.5, are used for this purpose. For each crop, all 19 BIOCLIM variables were extracted over the present cultivated area and subjected to Principal Component Analysis (PCA) to characterise the multivariate bioclimatic space. Future suitability was assessed using a multivariate envelope criterion requiring the PCA space to remain within the present observed range. In addition to area loss within current cultivated extents, potential gain areas, which refer to locations outside current cultivation but within the bioclimatic envelope, were identified across mainland Portugal. Under SSP1-2.6, losses ranged from 37 to 41% of the present cultivated area, whereas, under SSP5-8.5, losses ranged from 52 to 61%, with all six crops losing more than half of their present bioclimatic niche. Concurrent gains were, however, identified in northern Portugal and, at higher elevations, reflecting a northward and altitudinal shift in bioclimatic suitability. Once these gains are offset against losses, the net change in the suitable area ranged from −12% to −29% under SSP1-2.6, with maize alone expanding (+17%), and from −15% to −49% under SSP5-8.5. These projections do not account for future crop adaptation through physiological acclimation, cultivar improvement, or changes in management practices. Nonetheless, these results provide an impact assessment framework to support climate adaptation planning in Portuguese agriculture. Full article

Environmental disclosure and environmental, social, and governance assessments are gaining importance, using Corporate Disclosure Project (CDP) scores to evaluate corporate environmental disclosure. However, scarce evidence links CDP scores with performance and value among Japanese manufacturing firms. This study examines these associations using panel data from 2018 to 2023, combining financial data from Nikkei NEEDS Financial QUEST with CDP scores for climate change, water security, and forests. CDP ratings were converted into ordered numerical values, and regression models were estimated with firm-level controls, firm age, applicable fixed effects, and an annual macroeconomic control variable. Robustness checks included categorical score specifications, propensity score matching, and two-step system generalized method of moments estimation. The results indicate that the overall CDP score is positively associated with Tobin’s Q, whereas the evidence for return on assets and return on equity is weaker. Improvements in the overall score are also linked to increases in Tobin’s Q. By contrast, individual climate change, water security, and forest sub-scores show weak and inconsistent statistical significance. These findings should be interpreted as associations, not definitive causal effects. The study extends environmental accounting research beyond carbon-focused analyses, suggesting that aggregate CDP evaluations are more value-relevant than disaggregated sub-scores. Full article

Climate change is increasingly recognized as a defining global health crisis, yet its impacts on brain health, encompassing neurological function, mental health, cognitive abilities, and psychosocial behavior, and the resulting implications for planetary health more broadly remain under-recognized, fragmented, and insufficiently translated into action. Emerging evidence links climate-related stressors, including extreme heat, air pollution, environmental toxins, food insecurity, and vector-borne diseases, to neurological and mental health outcomes across the lifespan. At the same time, brain health and planetary health are interconnected, as brain health plays a critical role in shaping how individuals and societies respond to planetary crises through cognition, behavior, and decision-making. Addressing these interconnected challenges requires new models of collaboration that move beyond disciplinary research silos toward integrated, solution-oriented, and community-engaged approaches. In this Perspective, we argue that advancing brain and planetary health demands global, transdisciplinary networks capable of bridging science, policy, and lived experience. We present the International Neuro Climate Working Group (NCWG) as a case study of such a model, an action-oriented, globally distributed network that integrates research, policy translation, advocacy, and community engagement, with a strong focus on low- and middle-income countries (LMICs). Through transdisciplinary research initiatives such as the Brain-CLIMA project in Latin America, emerging work in South Asia, and global resilience frameworks, NCWG provides an example of how multi-factor, mechanism-informed, and policy-integrated approaches may generate actionable insights and equitable solutions. We propose that scaling similar collaborative models may provide a promising approach to addressing the complex, multidimensional challenges at the intersection of climate change, planetary health, and brain health. Full article

This study presents a proof-of-concept framework for multi-criteria assessment of civil-infrastructure risk under extreme environmental hazards. The framework combines fuzzy transformation, the Analytic Hierarchy Process (AHP), and a specified artificial intelligence (AI)-assisted weight-calibration module. It considers five dimensions: structural performance, environmental exposure, functional importance, emergency-response capacity, and maintenance condition. Quantitative indicators are normalized according to whether they increase or reduce risk, whereas qualitative indicators are converted using explicit fuzzy membership functions. The methodological contribution is a transparent separation between indicator processing, expert-derived AHP weighting, and optional data-driven calibration. The optional calibration module is specified to use projected gradient descent while maintaining non-negative, normalized weights. Because no historical outcome dataset or expert panel was available, the module was not trained or tested, and no improvement in predictive performance is claimed. The illustrative reinforced-concrete bridge calculation produced a Comprehensive Risk Index (CRI) of 0.686 (approximately 0.69), corresponding to the High Risk category. Sensitivity analysis showed that the High Risk classification remained unchanged when the two dominant dimension weights were varied by up to ±30% and the remaining weights were proportionally renormalized. The application is therefore presented as a reproducible proof of concept rather than an external demonstration. The framework can support future infrastructure maintenance prioritization and climate-resilience planning once it is calibrated and tested using independent asset data. Full article

Sustainability certification schemes (SCSs) such as LEED, BREEAM, etc., are widely accepted as an effective tool for the promotion of sustainable design principles and lifecycle carbon reduction in building projects. Greece, despite having a relatively small real estate market, presents solid activity in this field, but the related research remains extremely limited. Following a comprehensive quantitative data analysis regarding the use of SCSs in Greece and Europe, this paper examines adoption determinants, challenges, and prospects in the Greek construction sector, drawing on semi-structured interviews. The findings show that LEED dominates the Greek market, and although the SCS benefits are well documented in the literature, the overall market demand is largely confined to office and commercial developments and constrained by affordability concerns, low market awareness, supply chain constraints, administrative complexity, and project coordination challenges. Nevertheless, as future prospects are positive overall, the research provides recommendations towards targeted actions for policy-makers, industry professionals, and other stakeholders. This can encourage supply chain development and accelerate certification uptake, thereby supporting national sustainability objectives and the implementation of European climate and energy policies. Full article

Understanding the spatiotemporal dynamics of dominant desert-steppe species under climate change is critical for sustainable management of arid ecosystems. Sophora alopecuroides L., a perennial drought-tolerant leguminous herb with substantial medicinal and forage value, is an important component of these ecosystems. Based on 137 occurrence records and 10 environmental variables, we applied the MaxEnt model and ArcGIS to simulate suitable habitats and range shifts of S. alopecuroides across multiple periods, including the Last Interglacial (LIG), Last Glacial Maximum (LGM), Mid-Holocene (MH), present, and the 2050s and 2070s under four representative concentration pathways (RCP 2.6, 4.5, 6.0, and 8.5). The model showed high predictive performance, with an area under the receiver operating characteristic curve (AUC) greater than 0.9. Temperature annual range (Bio7), elevation, precipitation of the warmest quarter (Bio18), mean temperature of the driest quarter (Bio9), and annual mean temperature (Bio1) were identified as key environmental drivers, indicating that the distribution of this species is mainly shaped by temperature regimes, seasonal water availability, and topography. Under current conditions, the total suitable habitat accounts for 28.9% of China’s territory, closely matching the known distribution. Since the LIG, the total suitable area has fluctuated slightly, being larger during the LIG and LGM, smaller during the MH, and close to the present level thereafter. The distribution centroid remained within the Jinta Basin of the Hexi Corridor, Gansu Province, with only limited displacement from the LIG to the present, suggesting that this area, together with the Tianshan–Junggar Basin margins and the Alxa Plateau–Helan Mountain region, constitute key topographically and climatically inferred potential refugial areas for S. alopecuroides. Future projections indicate that suitable habitat may expand slightly under low-emission scenarios but contract under medium- to high-emission scenarios, with centroid shifts varying among pathways. These findings highlight the potential importance of such bioclimatically inferred putative refugia in maintaining the distribution of dominant dryland herbs and provide a spatially explicit basis for monitoring, germplasm conservation, and adaptive management of S. alopecuroides under ongoing climate change. Full article

Climate variability and land use/land cover changes (LULCC) can intensify soil erosion. This study evaluated the relative influence of LULCC and climate change on soil water erosion in an Andean watershed in Ecuador. Soil erosion was assessed using the RUSLE model for 1996, 2023, and 2040. Future erosion was predicted for 2040 using projected land use/land cover (LULC) and two climate scenarios under the Shared Socioeconomic Pathways SSP585 (pessimistic) and SSP126 (optimistic). Meanwhile, LULC was projected until 2040 through a Cellular Automata Markov model (CA-Markov). Climate scenarios for 2021–2041 were generated through statistical downscaling of the MPI-ESM-1-2-HR climate model. Results showed that erosion increased by 17.8% from 1996 to 2023; meanwhile, by 2040, it is projected to increase by up to 65.1% under both climate scenarios. A factorial sensitivity analysis revealed that LULCC is the primary driver of erosion, accounting for over 82% of the total variation in erosion, while the contribution of climate change remains secondary. These findings suggest that in tropical mountain zones, loss of vegetation cover has a greater impact on erosion rates than climatic variability, regardless of the climate scenario, confirming that the effect of climate change on soil erosion remains marginal. Full article

Understanding how land change affects water yield is essential for sustainable land management and water security. However, previous studies often rely on a single model or spatial scale, limiting their ability to capture fine-scale land-surface heterogeneity and basin-integrated hydrological processes; consequently, cross-scale consistency in water-yield patterns and drivers remains unresolved. This study developed a dual-spatial-scale framework for the Upper Yangtze River Basin. The Patch-generating Land-Use Simulation (PLUS) model projected land patterns for 2030, the Integrated Valuation of Ecosystem Services and Tradeoffs Annual Water Yield (InVEST-AWY) model mapped grid-scale water yield, the Soil and Water Assessment Tool (SWAT) model simulated sub-basin hydrological responses, and Geodetector identified dominant drivers. Their integration links local land transitions with basin-scale hydrological consequences under consistent scenarios, thereby overcoming the limitations of single-model assessments. Results showed that high water-yield areas were concentrated in the eastern and central basin, while the two scales exhibited similar spatial patterns but locally different magnitudes and trends. Built-up land under urban development was 7.96% greater than under ecological protection. Climatic variability increased runoff by 2115.33 m³/s under ecological protection, while precipitation dominated water-yield variation, with explanatory powers of 0.81 and 0.67 at the grid and sub-basin scales, respectively. These findings advance understanding of scale-dependent responses and support land optimization and watershed planning. Full article

Climate change may redistribute understory medicinal plants, but national predictions are useful when model uncertainty and field constraints are explicit. We aimed to identify the current and future suitable habitat of Sceptridium ternatum and translate predictions into survey and conservation priorities. We compiled 187 occurrences, screened 104 candidate predictors to 9, calibrated MaxEnt with kuenm, and evaluated it using partial ROC, omission rate, AICc, random and spatial-block cross-validation, and the Boyce index. Future suitability was projected with two GCMs under SSP1-2.6 and SSP5-8.5. October precipitation had the highest permutation importance, and growing-season thermal accumulation was another major contribution. NDVI had high percent contribution but no unique permutation importance. The selected model achieved mean random-fold and spatial-block test AUCs of 0.9217 and 0.8575, respectively, and a Boyce index of 0.8211. Late-century SSP5-8.5 reduced total and highly suitable habitat by 45.06% and 89.96%, respectively. Protected areas covered only 14.77% of highly suitable habitat. The resulting framework separates regional climatic suitability from habitat compatibility and management feasibility, a distinction relevant to other data-limited understory medicinal plants. It distinguishes sites for population verification, germplasm collection, and long-term monitoring, and plot-scale decisions require measurements of canopy, moisture, substrate, population state, and mycorrhizal context. Full article

Chinese wolfberry (Lycium chinense Miller) is a vital medicinal plant and a key species for ecological restoration. While Species Distribution Models (SDMs) are commonly used to predict habitat suitability, they often rely exclusively on native occurrence data, potentially underestimating a species’ climatic niche breadth under assumptions of niche conservatism. This study aims to evaluate the global climatic tolerance of Chinese wolfberry by integrating occurrence data from both native and introduced ranges. We assess the impact of climate change on its potential range shifts in China and determine whether native-only models underestimate the species’ climatic tolerance. We compiled 984 high-quality global distribution points (536 native, 448 introduced). We compared climatic niche breadth derived from native-only data with that from global data. Using MaxEnt modeling, we projected the global niche model onto China under current conditions and under four future Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, and SSP585) for the year 2070 to analyze changes in habitat suitability and centroid migration. The study confirms that relying solely on native data significantly underestimates the climatic tolerance of Chinese wolfberry, particularly for thermal variables (e.g., mean temperature of the warmest/coldest month). The global model, driven primarily by the coldness index, annual biotemperature, and humidity index, showed excellent performance (AUC = 0.952). Currently, highly suitable habitats cover approximately 44% of China’s land area. However, future projections indicate a severe decline in habitat quality. While the total suitable area remains relatively stable, the proportion of highly suitable habitat within the total habitat is projected to drop from 62.6% to as low as 19% under high-emission scenarios. The centroid of highly suitable habitats is expected to migrate multidirectionally at an annual rate of 0.97–2.42 km·a⁻¹, while the altitudinal centroid shows a drastic upward shift of up to 7.24 m·a⁻¹ under the SSP585 scenario. Integrating global occurrence data provides a more robust estimate of the ecological tolerance of Chinese wolfberry. Future climate change poses a significant threat to the quality of suitable habitats in China, necessitating adaptive management strategies such as assisted migration to northern refugia and the implementation of climate-smart agricultural practices to sustain the economic and ecological value of this species. Full article

Greening urban spaces is one of the fundamental elements in strengthening urban resilience to climate change and introducing sustainable urban lifestyles. The subject of this research is innovative urban solutions, situated in the context of cities’ aspirations to attain the title of being the greenest and most sustainable city in Europe. The conducted research is based on a comparative analysis of greening initiatives in 41 cities in 13 European countries, united in the international project Green Cities Europe, carried out from 2020 to 2023. The aim of the research is to evaluate urban solutions implemented in the context of social, economic, environmental, and spatial values, as well as the use of blue–green infrastructure, renewable energy sources, and new technologies. The study employed a mixed-methods approach combining qualitative and quantitative analyses. The research included a review of planning and strategic documents, a comparative analysis of 131 urban greening projects, and an evaluation of 45 projects nominated for the Green Cities Europe Award (GCEA). The findings were synthesised using comparative statistical analyses and descriptive evaluation. Based on the conducted analysis and assessment, we demonstrate that the studied cities, which are pursuing development and climate policies, implement urban greening actions with varying, often limited, degrees of innovation. We show that the implemented solutions place significant emphasis on environmental and social values, but only minimally incorporate elements of renewable energy sources and new technologies. This study indicates the need for cities to pursue a coherent development policy that fosters the planning and implementation of innovative urban solutions. Full article

Climate change may alter the abiotic conditions associated with macrofungal occurrence, but projections for taxonomically unresolved species complexes require cautious interpretation. Here, we used an AICc-optimized MaxEnt model to characterize the climate-defined aggregate suitability envelope of records assigned to the Lyophyllum decastes (Fr.) Singer complex in Sichuan, Yunnan, and Xizang, Southwest China, under current conditions and four RCP scenarios for the 2050s and 2070s. After spatial thinning, 70 occurrence records compiled from field surveys and published sources were modeled with correlation-filtered bioclimatic variables. The optimized model showed high discrimination for the pooled occurrence dataset (mean AUC > 0.95), and mean temperature of the coldest quarter had the largest contribution (50.8%). Projected changes differed between scenarios, with increasing fragmentation and reductions in highly suitable climate space under several futures. These outputs do not represent a lineage-resolved species distribution, as the occurrence records were not uniformly verified by molecular barcodes, and the model omits host availability, vegetation, soil, land use, dispersal, and other biotic processes. We therefore interpret the maps as a hypothesis-generating, aggregate climatic envelope for the complex that can guide stratified field surveys, molecular sampling, and habitat monitoring rather than as direct evidence of taxon-specific physiological tolerances or realized distributions. Full article

Understanding vegetation dynamics and their driving mechanisms in arid regions is essential for assessing ecosystem resilience under global change. This study investigates the spatiotemporal patterns of vegetation greenness in Xinjiang, China, from 1985 to 2018, with a focus on land-use change and climatic influences. We used long-term Normalized Difference Vegetation Index (NDVI) data combined with climate variables and high-resolution land-use data. Trend analysis, residual analysis, breakpoint detection, and random forest sensitivity analysis were applied to examine vegetation dynamics and their potential driving factors. The results show that Xinjiang experienced a significant greening trend, with a pronounced turning point around 2000, coinciding with the implementation of large-scale ecological restoration projects. During 1985–1999, vegetation changes were closely related to temperature, particularly in mountain regions, while the positive effect of precipitation became more evident after 2000 due to increased vegetation cover and evapotranspiration demand. Land-use transformations, especially barren land to grassland, grassland to cropland, and grassland to forest, were strongly associated with vegetation greening. The baseline residual analysis indicated that a large proportion of vegetation greening after 2000 could not be fully explained by temperature and precipitation alone. Random forest sensitivity analysis further identified human footprint and temperature as important predictors of NDVI trends. These results suggest that human-related land-use and management activities, together with climatic factors, likely played important roles in shaping vegetation recovery in Xinjiang. Breakpoint analysis showed that many vegetation shifts occurred between 1999 and 2003, particularly in regions where ecological restoration projects were concentrated. Overall, our findings indicate that vegetation recovery in Xinjiang was jointly influenced by human-related activities and climate conditions, while this improvement remains constrained by water availability. These insights provide a scientific basis for optimizing ecological restoration strategies in arid and semi-arid regions. Full article