Search Results (3,902)

An extreme rainfall event that occurred from 16 to 18 December 2021 along the coastal regions of Peninsular Malaysia (PM) caused widespread flooding and substantial socioeconomic impacts. This study investigates the mechanisms leading to this event, focusing on the roles of climatic phenomena and local terrains. Two atmospheric interactions play key roles in triggering the event. Firstly, a strong cold surge (CS) associated with the East Asian winter monsoon (EAWM) interacted with the easterly surge over the southern South China Sea, leading to the formation of Borneo vortex. Secondly, a strong northeasterly and CS largely contributed to enhancing and transporting the vortex towards the PM and across the Titiwangsa mountain ranges. The phase change of the Indian Ocean Dipole (IOD) facilitated the eastward propagation of the vortex. Sumatra and PM terrains significantly modulated vortex evolution and moisture convergence over the Strait of Malacca. These findings are analyzed to shed light on interactions between large-scale climate drivers and localized terrain in generating extreme rainfall, emphasizing the necessity of multi-scale analysis for model accuracy. Full article

Overwintering peat fires are increasingly reported in the boreal regions, where they persist underground through winter and reignite in spring, intensifying greenhouse gas emissions and landscape degradation. This study investigates the conditions that enable peat fires to survive freezing and snow cover, and presents practical methods for their winter detection and suppression. We combined satellite data, UAV-based thermal imaging, time-lapse photography, and ground measurements of temperature, groundwater depth, and peat moisture to identify active overwintering hotspots. Our results show that these fires persist primarily where groundwater levels remain below 60 cm, particularly under tree roots, compacted soil, or elevated terrain that limits moisture recharge. UAV thermal imaging proved the most reliable detection tool, identifying 98% of hotspots. We developed and successfully applied a winter extinguishing method that involves mechanical disruption and dispersion of smoldering peat over frozen ground, allowing rapid cooling without re-ignition. These findings clarify the mechanisms sustaining overwintering fires and provide an effective approach for their mitigation, contributing to reduced emissions and improved management of boreal peatlands vulnerable to climate change. Full article

Soil CO₂ emissions are critical for predicting terrestrial ecosystem feedbacks to climate change, yet significant knowledge gaps persist regarding carbon flux dynamics within the deep vadose zone and during freeze–thaw processes. In this study, the Mu Us Sandy Land, a representative seasonally frozen and semi-arid region in Northwestern China, was selected as the research site. Based on in situ observation data and the XGBoost algorithm, the spatiotemporal variations of soil carbon flux and its environmental drivers were investigated. Results revealed distinct depth-dependent patterns, where carbon release reached its maximum flux in the 100–200 cm layer and carbon sequestration dominated the soil layers below 200 cm. Soil temperature and moisture were the primary controlling factors, but their impacts exhibited significant depth and seasonal heterogeneity. Notably, in the 20–50 cm soil layer, soil water content provided the highest explanatory power, reaching 55.3% and 47.8% in winter and summer, respectively. Furthermore, carbon fluxes exhibited distinct response thresholds to environmental factors, and their spatiotemporal variations were fundamentally regulated by an atmosphere-driven coupled water–vapor–heat–carbon process. These findings elucidate the complex relationship between soil carbon fluxes and the environment at different depths, providing theoretical support for deepening the understanding of regional carbon cycling. Full article

Wildfires are a major natural hazard causing extensive ecological damage and endangering human survival. Previous studies on wildfires in China have mostly focused on specific regions or individual drivers, with limited systematic assessments at the long-term and national scales. The spatiotemporal patterns of wildfires and their multiple driving mechanisms under China’s diverse climatic regimes remain insufficiently understood. To bridge this gap, we combined MCD64A1 burned area data (2001–2023) with multi-source natural (meteorological, vegetation, and topographic) and anthropogenic factors, using random forest models at both the national and regional scales to examine the spatiotemporal patterns, dominant drivers, and response mechanisms of wildfires in China. The results revealed that: (1) Spatially, wildfires were concentrated in northeastern and southern China, which accounted for 86.20% of the total burned area. Temporally, northern wildfires were primarily a spring-dominated fire regime, with peak activity in March and April, whereas southern wildfires were winter-dominated, peaking in February. (2) At the national scale, elevation was the key topographic factor influencing wildfire occurrence (relative importance = 0.49), with low-elevation and gentle-slope areas being more fire-prone. At the regional scale, the driving factors exhibit spatial differentiation, forming a spatial pattern of topography-dominated and climate-dominated. (3) Partial dependence plot analysis revealed nonlinear and threshold responses. Fire probability increases rapidly when the soil moisture is below 20 mm, while extremely high land surface temperatures in arid regions suppress fire occurrence due to fuel limitations. This study enhances the understanding of spatially heterogeneous wildfire drivers in China and provides a scientific basis for region-specific wildfire prevention and management strategies. Full article

Global climate change is reshaping Central European conifer forests, affecting growth and ecosystem dynamics. At the same time, tree species differ in their productivity and responses to climatic conditions. Across mid-elevation monocultures of European yew (Taxus baccata L.), Norway spruce (Picea abies [L.] Karst.), Scots pine (Pinus sylvestris L.), silver fir (Abies alba Mill.), and European larch (Larix decidua Mill.), we quantified stand structure, volume, biomass carbon sequestration, and growth–climate responses (1971–2023). Silver fir reached the highest stand volume (711 m³ ha⁻¹), with lower productivity in pine (−17.0%), larch (−22.9%), spruce (−26.0%), and yew (−70.6%). In contrast, larch maximised biomass carbon sequestration (267.7 t ha⁻¹), whereas yew had the lowest value (87.7 t ha⁻¹), but the greatest stand diversity (except high differentiation), while pine showed the lowest diversity. Radial growth was most constrained by warm Junes and dry Julys; an early-season multi-month drought compounded by heat further suppressed radial increments, and severe winter frosts added stress. Among the studied species, spruce was the most climate-sensitive, whereas fir and pine showed comparatively more resilience. From a practical forestry perspective, promoting structurally diverse stands with high production potential and prioritising climate-resilient tree species, especially fir, can help sustain production and stability at mid elevations under climate warming. Our results provide species-specific benchmarks for adaptive silviculture and identify the seasonal windows when growth is most vulnerable. Full article

Hurricanes routinely damage forests across the North Atlantic Basin, yet efforts to characterize their impacts have had mixed subregional success. To elucidate these challenges, this study analyzed pre- and post-hurricane land surface phenology (LSP) for 44 moderate and strong hurricanes over 22 years using the Enhanced Vegetation Index (EVI). We statistically grouped storms based on their long-term climate attributes, then compared subregional impacts with wind speed and land cover. After accounting for wind speed, responses differed among the six subregions. The Southeast U.S. showed declines in EVI for the first winter and first year post storm, but this response was weak or absent elsewhere. The Central America region declined in the first winter but not in the subsequent growing season, while four other regions showed no increased impact with wind speed in either season. We then examined six category 4 hurricanes using a forest mask. In dry areas, drought-sensitive vegetation explained weak responses, whereas in the humid tropics, rapid refoliation or sprouting was common. These factors complicate optical remote sensing assessments. Rapid evaluations can mistake defoliation for more substantial damage, and delayed assessments can confuse EVI recovery with structural recovery. Results underscore the need for ecologically tailored monitoring approaches. Full article

Climate change is intensifying winters in temperate regions, posing a serious threat to Apis mellifera health. The gut microbiome, a distinct community of core bacterial species, is central to overwintering success by supporting immune function, nutrient assimilation, and pathogen resistance, but is highly sensitive to environmental stressors such as cold temperatures and dietary shifts. Stress-induced perturbations can reshape the composition and relative abundance of the gut microbiome in honey bees, leading to adverse effects on host health, physiological functions, and overwinter survival. Cold temperatures and additional stressors further destabilize the microbiome, compounding these effects. This review is the first to synthesize current knowledge on how extrinsic factors, such as diet, antibiotics, and pathogens, and intrinsic factors, including age and strain, influence the composition and function of the honey bee gut microbiota during the overwintering period. Given the increasing severity of winter conditions under climate change, a deeper understanding of microbiome–host–environment interactions is essential for improving honey bee resilience. By integrating evidence on the microbiome’s roles in nutrient utilization, immune modulation, and pathogen defense, this review outlines a framework to guide future research aimed at sustaining pollinator health and nutrition in a changing global climate. Full article

Seasonal ice is typically present in the southern Gulf of Saint Lawrence from December through March; however, climate change is predicted to reduce this season and alter local ecosystems, geomorphologies, and infrastructure. This impact assessment ascertains the influence of climate change on the ice coverage along Prince Edward Island’s coast. Ice concentration data from 50 study sites were logarithmically correlated with cumulative freezing degree days (FDDs). Correlations were generally good (mean R² = 0.63), although poorer values were observed in areas with greater exposure to wind and waves. An ensemble of the CMIP6 models’ forecasts of future temperatures showed that FDD will drop from an average of 487 °C days during the historical period (1981–2025) to less than 164 °C days in the 2090s under a low-emission scenario, SSP1-2.6. For the same study period, a high-emission scenario (SSP5-8.5) projects FDD to drop to 28 °C days by the end of the century, while a moderate-emission scenario (SSP2-4.5) forecasts 97 °C days annually. Seasonal ice indices demonstrated a similarly substantial decrease, from an average historical value of 11.1 to 3.8, 3.2, and 0.8 for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The length of the ice season was also analyzed, with mean season lengths for the 2090s ranging from 3 to 24 days, depending on the emission scenario, representing a 70–96% reduction in season length from the baseline observation. Mild variations were measured in the rate of ice loss throughout the province; however, significant differences in the ice coverage’s baseline values, due to local currents and wave exposure, led to a broad range in the relative proportions of ice loss, with areas along the eastern coastline projecting zero ice winters. Over the next 80 years, projections point to a considerable decline in ice coverage around Prince Edward Island. Full article

Wildfires at the wildland–urban interface (WUI) have increased in frequency and severity under global warming and intensified human activities. As a representative high-altitude mountainous region in southwestern China, Yunnan features complex topography, steep climatic gradients, and dispersed settlements interwoven with wildlands, making it a fire-prone area where wildfire management is particularly challenging. However, a fine-scale WUI dataset is currently lacking for this region. To address this gap, we refined WUI classification thresholds using a one-factor-at-a-time (OFAT) method and generated the first fine-resolution WUI map of Yunnan. Seasonal wildfire driving factors from 2004 to 2023 were quantified, and machine learning models were applied to produce seasonal susceptibility maps. SHapley Additive exPlanations (SHAP) were employed to interpret the dominant contributing factors. The resulting WUI covers 25,730.67 km², accounting for 6.5% of Yunnan’s land area. Random forest models effectively captured seasonal wildfire susceptibility patterns, with AUC values exceeding 0.83 across all seasons. High susceptibility zones (>0.5) comprised 30.09% of the WUI in spring, 25.74% in winter, 22.61% in autumn, and 13.74% in summer. SHAP analysis revealed that anthropogenic factors consistently drive wildfire occurrence, while climatic conditions in the preceding season influence vegetation status and subsequently affect wildfire likelihood in the current season. By integrating static “where” mapping with dynamic “when” susceptibility analysis, this study establishes a comprehensive “When–Where” framework that supports both long-term WUI planning and short-term seasonal early warning. The integration of fine scale WUI mapping with seasonal susceptibility modeling enhances wildfire risk management in complex high-altitude regions. These findings provide a scientific basis for location-specific, time-sensitive, and full-chain wildfire management in mountainous landscapes and contribute to cross-border ecological security governance in the Indo-China Peninsula. Full article

Climate change is altering the frequency, duration, and seasonality of low flows, which are critical for water availability, ecosystem functioning, and river management. Low-flow characteristics, defining the minimum, often seasonal, flow levels in rivers or streams primarily fed by groundwater, snow or glacier melt, or lake drainage, are essential for assessing hydrological droughts and water resource vulnerability. In the Upper Vistula River Basin, variable precipitation and rising air temperatures increase the risk of droughts, impacting both natural systems and human water use. This study analyzed long-term trends in annual low flows and associated parameters, including drought frequency, duration, and deficit volume, across 41 small- and medium-sized catchments. Two datasets were considered: 25 stations with 58-year daily discharge records (1961–2019) and 41 stations with 38-year records (1981–2019). Low flows were identified using the threshold level method (TLM) at 70% and 90% exceedance (FDC70 and FDC90). Trends were assessed with the Mann–Kendall test, and spatial drought patterns were mapped to evaluate regional variability. Deep and shallow low flows occurred at all analyzed cross-sections. For the period 1961–2019, deep low flows (FDC90) occurred almost annually in 18 of the 25 cross-sections since 2012. Statistically significant increasing trends in deep low-flow parameters were detected in five cross-sections for 1961–2019 and in seven cross-sections for 1981–2019. Shallow low flows (FDC70) occurred in all sections; four rivers exhibited annual shallow droughts during 1961–2019, whereas 12 rivers showed annual events in 1981–2019. Summer droughts predominated over winter events, reflecting enhanced evapotranspiration and higher seasonal water demand. These findings highlight the relevance of analyzing low-flow parameters for understanding hydrological droughts. Such information can support water resource management, planning, and ecosystem protection under variable climatic conditions. Full article

Fusarium head blight (FHB) is one of the most devastating diseases of cereal crops worldwide, causing yield losses and mycotoxin contamination. Traditionally associated with warm and humid climates, FHB has increasingly affected cooler and drier regions, including the Volga region of Russia—a major grain-producing area once considered low-risk. In this three-year field study, we evaluated FHB resistance in 50 winter rye accessions under natural infection and artificially enriched infectious backgrounds using high-virulence Fusarium strains from the Volga region. Post-invasive resistance to FHB was generally weak across the tested germplasm. Nevertheless, considerable variability in FHB damage was observed among accessions. Accessions showing the lowest overall FHB severity were identified as promising donors for breeding programs. Specific resistance sources to individual Fusarium species were identified, notably Fusarium sporotrichioides—previously regarded as a weak pathogen but demonstrated here as a serious food safety threat. No significant positive correlation was found between FHB severity and mycotoxin levels, confirming these as partially independent traits; several accessions maintained low mycotoxin content despite severe symptoms. Our study highlights the necessity of multi-environment screening with local pathogen strains and endorses pyramiding approaches for durable FHB resistance in winter rye breeding. Full article

Soil organic carbon (SOC) is a key indicator reflecting soil quality and management level. Understanding its spatiotemporal dynamics in cropland is necessary for sustainable land management. Revealing the relationship patterns between SOC (Sampling resolution: 1 km²; analysis resolution: 4 km²) and environmental factors in one period allows inferring SOC distribution in unsampled years, partly compensating for temporal data gaps. This study introduces a season-based crop rotation system (Winter wheat in the first season and summer corn in the next) as independent variables in a machine learning model innovatively, enriching variable selection in SOC inference and improving understanding of SOC accumulation. The Beijing–Tianjin–Hebei (BTH) region, characterized by a typical winter wheat–summer corn rotation system, was selected for analysis. The results show that in 2000, the average SOC was relatively low compared with global levels. Climatic variables were negatively correlated with SOC below the 0.8 quantile but positive above it, which corresponds to the upper 20% of the observed range of each climatic variable. Winter-wheat growth is more important on SOC distribution than summer-corn growth (two annual peaks of NDVI and EVI), showing a positive correlation with SOC, while corn showed a weak correlation and became negative above the 0.8 quantile. In the inferred results, the differences between observed and inferred mean values and their confidence intervals were approximately 0.1. This research provides a reference method for evaluating regional-scale SOC distribution patterns under data-limited conditions by integrating environmental factors and crop rotation characteristics. Full article

This study investigates the spatiotemporal variability of the near-surface air temperature lapse rate (NSATLR) in Calabria, a region representative of typical Mediterranean environmental and climatic conditions. Through the integration of observational datasets and model simulations, a global sensitivity analysis using the Sobol method, and Bayesian linear regression modelling across annual, seasonal, and monthly scales, the primary drivers of near-surface air temperature (NSAT) variability were identified. Results demonstrate that altitude is the dominant factor influencing temperature distribution, with minimal contributions from other geographical parameters such as latitude, longitude, and proximity to the sea. The Bayesian models yielded robust performance for mean and maximum temperatures, while minimum temperature proved more challenging to predict. Lapse rate analyses confirmed a consistent inverse relationship between temperature and elevation, with the steepest gradients observed for Tmin. In particular, a significant long-term decline in lapse rates over the past 70 years, especially during winter and autumn, points to accelerated warming at higher elevations, primarily driven by rising Tmin values. This trend suggests a gradual homogenization of temperature across altitudes, with important implications for ecosystem dynamics, snowpack stability, and climate-sensitive sectors such as agriculture and urban planning. Full article

Rapid urbanization has intensified microclimatic deterioration in temperate monsoon cities, directly affecting human thermal comfort. This study investigates the regulatory effects of common street tree species under varying street aspect ratios (H/W) and orientations in Shenyang, China, a representative temperate monsoon city characterized by cold winters. Field surveys and questionnaire data were combined with ENVI-met simulations to quantify thermal comfort responses using the Universal Thermal Climate Index (UTCI). Results demonstrate that street geometry strongly constrains microclimate regulation: streets with H/W = 1.2 and a SE–NW orientation achieved the most favorable balance between shading and ventilation, yielding the lowest UTCI values. Significant interspecies variability was observed: Golden Elm and Chinese Willow provided the greatest cooling benefits, whereas Ginkgo exhibited limited adaptability, particularly in enclosed or highly open canyons. A comparison with subjective thermal comfort votes confirmed strong model reliability, though discrepancies emerged in dense commercial areas due to non-meteorological factors. Based on these findings, a spatially driven, species-adaptive, and human-centered framework is proposed to optimize street greening strategies in a temperate monsoon city characterized by cold winters. This research provides quantitative evidence for urban greening design, highlights the necessity of integrating spatial form with tree-species selection, and offers practical guidance for resilient thermal comfort management in rapidly urbanizing cold-region cities. Full article

The Upper Colorado River Basin (UCRB), through the process of snow accumulation, to snowmelt, to streamflow runoff, provides a critical water source to approximately 40 million residents in the Southwestern United States. Given the importance of late fall–winter–early spring (October, November, December, January, February, March, or ONDJFM), cumulative precipitation, future estimates of ONDJFM cumulative precipitation, and potential drought occurrence would provide a benefit to water managers and planners. Previous research efforts successfully reconstructed (extended the period of record) the regional April 1st Snow Water Equivalent (SWE) in the UCRB using tree-ring chronologies and reconstructed climate (El Niño–Southern Oscillation or ENSO). The current research efforts differ by (a) incorporating future [Shared Socioeconomic Pathway (SSP) 5-8.5] predictions of ONDJFM cumulative precipitation (in lieu of April 1st SWE) at a single station location (Kendall R.S.) in the UCRB; (b) reconstructing ONDJFM cumulative precipitation (in lieu of April 1st SWE) using tree-ring chronologies and ENSO; and (c) evaluating an alternative reconstructed ENSO index. The reconstructed record, recent past observations, and future (SSP 5-8.5) ONDJFM cumulative precipitation were then combined to provide a paleo perspective of future drought. Results indicate that extreme ONDJFM cumulative precipitation drought periods projected for the ~2040s were exceeded in the reconstructed record. A pattern of alternating wet and dry conditions was also identified, consisting of a wet (pluvial) period in the 2030s, followed by drought conditions in the 2040s, and another wet period in the 2050s. Many of the extreme future wet (pluvial) periods exceeded those in the recent record and reconstructed record. Full article