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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

Urban wetlands are acoustic hotspots where vegetation structure, hydrological dynamics, and anthropogenic noise interact, yet multi-season assessments of how vegetation influences avian soundscapes are limited. This study explored bird soundscape dynamics across forest, open forest grassland, and meadow habitats in Nanjing Xinjizhou National Wetland Park, eastern China, using passive acoustic monitoring during spring and autumn 2023. Twelve sampling points (four per vegetation type) were established, and six acoustic indices were calculated, including the Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bioacoustic Index (BIO), Normalized Difference Soundscape Index (NDSI), and Acoustic Entropy Index (H). were calculated from 48-h recordings each season. Random forest models and redundancy analysis assessed the relationships between acoustic indices, fine-scale vegetation parameters (e.g., crown width, tree height, species richness), and anthropogenic factors (e.g., distance to roads/trails, surface hardness). Vegetation structure, particularly crown width, was the primary driver of avian acoustic diversity, with broad-crowned forests consistently exhibiting the highest acoustic complexity. In spring, anthropogenic factors such as trail and road proximity dominated soundscape variation, suppressing biological sounds. In autumn, with reduced human presence, vegetation structure emerged as the dominant factor, while bioacoustic activity remained elevated despite reduced peaks in acoustic complexity. Proximity to roads increased low-frequency (1–2 kHz) noise and suppressed mid-frequency (4–8 kHz) bird vocalizations, but trees with crown widths ≥4 m maintained higher acoustic diversity even near disturbance sources. This study demonstrates that vegetation structure mediates both resource availability and sound propagation, buffering the effects of anthropogenic disturbance in frequency-specific ways. Multi-season sampling is crucial for understanding the dynamic interplay between vegetation phenology and human activity that shapes urban wetland soundscapes. Full article

Frequent flash floods threaten human well-being, hydropower infrastructure, and ecosystems. However, the long-term evolution of flash flood patterns over recent decades remains insufficiently understood, particularly in data-scarce high-altitude regions. Using multi-source remote sensing data integrated with historical disaster records and field investigations, this study examined the spatiotemporal evolution and driving factors of flash floods across the Qinghai–Tibet Plateau (QTP). The results indicate that flash floods have increased exponentially, which may be influenced by disaster management policies, with peaks in July–August and frequent occurrences from April to September. The seasonal trajectory of the center of gravity of flash floods from April to September exhibited a clear directional pattern. Regions with the highest disaster density were concentrated in the headwaters of five major rivers, including the Yarlung Zangbo, Jinsha, Nu, Lancang, and Yellow Rivers. Shapley Additive Explanation (SHAP) and Random Forest analyses reveal that soil moisture, anthropogenic intensity, and seasonal runoff variability are the dominant driving factors. With ongoing socioeconomic development, intensified human activities have become a key contributor to the increasing frequency of flash floods. These findings highlight the value of remote sensing-based assessments for flash flood monitoring and early warning and provide scientific support for risk mitigation, loss reduction, and the advancement of water-related targets under the United Nations’ Sustainable Development Goals. Full article

Urbanization alters the hydrological and structural functioning of tropical urban streams, influencing organic matter transport and retention processes. This study investigated leaf litter retention dynamics in the Bindá Stream in central Amazonia. A six-month leaf release experiment (100 leaves per 12 trial; 1200 leaves total) was conducted alongside hydrological monitoring and floristic surveys of riparian vegetation (adult and regeneration strata). Leaf retention remained consistently low (<33%) across sampling periods. Generalized linear models indicated that flow velocity and discharge were the primary predictors of retention probability, with higher hydrodynamic intensity significantly reducing in-stream storage. Riparian vegetation exhibited moderate structural complexity (Shannon H′ = 1.80; Structural Complexity Index = 3.80), yet limited channel roughness and physical obstructions constrained retention efficiency. Anthropogenic debris locally increased retention, but represents a structurally altered retention mechanism. Hydrodynamic forcing, rather than precipitation totals alone, governed organic matter transport dynamics. Reduced retention capacity suggests limited buffering of downstream material export under high-flow conditions. Although direct water-quality or epidemiological indicators were not measured, findings align with ecohydrological frameworks linking structural simplification and flow flashiness to diminished ecosystem regulation. These results inform riparian restoration and urban stormwater management strategies aimed at enhancing ecosystem regulation and water-quality buffering in tropical cities. Full article

Lakes on the Inner Mongolia–Xinjiang Plateau (IMXP) are increasingly vulnerable to eutrophication under climate change and human pressure, yet long-term monitoring remains limited by sparse field sampling. Here, we reconstruct multi-decadal trophic dynamics across the IMXP using Landsat time series and temporally transferable machine-learning models and further quantify the underlying natural and anthropogenic drivers. We compiled monthly in situ water-quality observations (chlorophyll-a, Chl-a; total phosphorus, TP; total nitrogen, TN; Secchi depth, SD; and permanganate index, COD_Mn;) and calculated the trophic level index (TLI). After rigorous quality control and monthly aggregation, we compiled a dataset of 1345 matched lake–month samples spanning 2000–2024, and divided it into a training set (n = 1076; ≤2019) and an independent test set (n = 269; 2020–2024) to evaluate temporal transferability. We utilized Google Earth Engine to generate monthly surface reflectance composites from Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2. Four supervised regression algorithms—ridge regression (RR), support vector regression (SVR), random forest (RF), and eXtreme Gradient Boosting (XGBoost)—were trained to estimate TLI. On the independent test period, XGBoost performed best (R² = 0.780, RMSE = 3.290, MAE = 1.779), followed by RF (R² = 0.770, RMSE = 3.364), SVR (R² = 0.700, RMSE = 3.842), and RR (R² = 0.630, RMSE = 4.267); we then used XGBoost to reconstruct monthly and yearly TLI for 610 perennial grassland lakes from 2000 to 2024. From 2000 to 2024, the annual mean TLI (48–49) across the IMXP exhibited a statistically significant upward trend (slope = 0.0158 TLI yr⁻¹; 95% confidence interval (CI) = 0.0050–0.0267; p = 0.006). Meanwhile, spatial heterogeneity was distinct (TLI: 41.51–59.70). High values concentrated in endorheic and desert–oasis basins (e.g., Eastern Inner Mongolia Plateau, >51), whereas lower values characterized high-altitude regions (e.g., Yarkant River, <45). Overall, trends ranged from −0.49 to 0.51 yr⁻¹, increasing in 54% of lakes (15.6% significantly) and decreasing in 46% (15.4% significantly). Attribution analyses identified NDVI (33.92%) and temperature (21.67%) as dominant drivers (55.59% combined), followed by precipitation (13.99%) and human proxies (30.42% combined: population 10.66%, grazing 10.31%, built-up 9.45%). Across 53 sub-basins, NDVI was the primary driver in 28, followed by temperature (11), population (7), precipitation (3), grazing (3), and built-up land (1); notably, the top two drivers explained 56.6–87.1% of variations. TWFE estimates revealed bidirectional NDVI effects (significant in 31/53): positive associations in 22 basins were linked to nutrient retention, contrasting with negative effects in nine basins associated with agricultural return flows. Temperature effects were significant in 15 basins and predominantly negative (14/15), except for the Qiangtang Plateau. Overall, eutrophication risk across the IMXP lake region reflects the combined influences of climatic conditions, vegetation conditions, and human activities, with their relative contributions varying among basins. 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

Siltation in irrigation canals adversely affects overflow capacity and accessibility, making its identification crucial for dredging, prevention, and maintenance, among other purposes. In this study, the siltation risks of Golmud irrigation canals were assessed from three perspectives: hydrodynamic impact, anthropogenic impact, and greening impact. The assessment factors included sediment deposition risk, bed erosion risk, proximity to public administration and services, proximity to residential areas, proximity to commercial services, and proximity to green spaces. The entropy weight method and TOPSIS method were employed to calculate the comprehensive siltation risk level, with model validation confirming a high overall accuracy of 94%. The results showed that among the six factors, proximity to public administration and services had the greatest influence on siltation, with a weight of 0.29. Additionally, the most vulnerable siltation locations were primarily in the city center, reflecting the susceptibility of urban areas to anthropogenic activities. This study develops a rapid and objective risk-scanning tool that couples hydrodynamics with land-use factors, providing a standardized technical pathway for the checking of large-scale urban infrastructure. Full article

Under the combined effects of climate change and anthropogenic activities, the dry–wet pattern of the Yellow River Basin is undergoing substantial reconfiguration, yet its long-term evolution and driving mechanisms remain unclear. This study constructs a Terrestrial Water Storage Anomaly-based Drought Severity Index (TWSA-DSI) using 1995–2014 as the historical period to characterize spatiotemporal dry–wet heterogeneity. Future changes during 2026–2100 are projected for the near future (2026–2060) and far future (2061–2100) under the SSP126, SSP245, and SSP585 scenarios. A comprehensive driving factor system incorporating vegetation cover, land use, meteorological conditions, and socio-economic factors is established, and dominance analysis is applied to quantify the controlling mechanisms of terrestrial water storage change (TWSC). Results indicate that the basin experienced a historical transition from aridification to humidification. Future dry–wet conditions differ markedly from the historical period, with the basin shifting toward overall humidification as emissions increase. The driving mechanisms of aridification and humidification are significantly different and precipitation is the decisive driving factor influencing the dry–wet evolution of the Yellow River Basin. Especially in the far future under the SSP585 scenario, the proportion of precipitation is as high as 54.9%. These findings provide scientific support for sustainable water-resource management under climate change. Full article

The genus Juniperus species is widely distributed in the Northern Hemisphere of the planet Earth. These species are notable for their ability to adapt to extreme environmental conditions, playing a crucial role in ecosystem structure and function. Currently, their expansion is being driven by anthropogenic activities and climate change, posing significant challenges for both control and conservation. The objective of this review was to synthesize the available evidence regarding the ecological importance and impacts of Juniperus on ecosystems, promoting a holistic perspective that contributes to the achievement of the United Nations 2030 Agenda for Sustainable Development. A systematic literature search was conducted using the Scopus database, and only the documents published between 2001 and 2025 were considered for the investigation. The results showed that these species possess a high ecological versatility, favoring their invasive success in disturbed ecosystems, particularly under the influence of climate change and land-use changes. Conversely, Juniperus species facilitate positive ecological outcomes by providing essential ecosystem services that benefit both the human population and the flora and fauna present in these ecosystems. Nevertheless, their expansion also causes negative effects, such as the suppression of herbaceous shrubs and understory cover, alteration of the hydrological function, and accelerated soil erosion, among others. Consequently, the genus Juniperus exhibits a dual ecological role, acting as a hero to many species within these ecosystems, yet a villain to others. In this sense, given its remarkable adaptive dynamism under scenarios of climate change and continuous anthropogenic alterations, it is imperative to promote comprehensive conservation and restoration strategies. These should include ecological monitoring, invasive species control, genetic management, and habitat restoration. Such efforts must be supported by long-term interdisciplinary research to understand and mitigate the ecological, genetic, and social impacts resulting from its expansion. Furthermore, these investigations and strategies must be flexible and locally contextualized to promote genuine ecosystem resilience in the face of the ongoing environmental transformations. Full article

Surface water–groundwater interactions within oasis–desert ecotones of arid regions play a pivotal role in sustaining regional water security and ecological stability. Taking the Niya River Basin in Xinjiang, Northwest China, as a representative inland watershed, this study systematically elucidates the mechanisms and seasonal dynamics of surface water–groundwater coupling under the combined influences of natural processes and anthropogenic activities. A total of 68 surface water and groundwater samples were collected during the dry, normal, and wet hydrological periods. Integrated hydrochemical characterization, mineral saturation index analysis, and stable isotope (δ²H and δ¹⁸O) mass balance modeling were employed to quantify recharge contributions and unravel hydrogeochemical evolution pathways. Results indicate that the waters in the study area are predominantly brackish to saline, with consistent dominant ionic assemblages (SO₄²⁻ and Na⁺) across all hydrological periods, highlighting evaporite dissolution as the primary control on solute composition. Hydrochemical evolution is jointly regulated by evaporation concentration, water–rock interactions, and cation exchange processes. Surface water chemistry reflects the combined effects of silicate weathering and evaporite dissolution, whereas groundwater chemistry is mainly governed by evaporite dissolution coupled with pronounced cation exchange. Stable isotope signatures reveal substantial secondary evaporation of regional precipitation prior to recharge. Frequent bidirectional recharge between surface water and groundwater was observed, exhibiting distinct seasonal transitions. During the dry period, groundwater provides significant baseflow support to surface water (48.6% in the oasis zone and 54.3% in the desert zone). In the normal period, recharge direction reverses, with surface water becoming the dominant source of groundwater recharge (99.0% in the oasis zone and 76.6% in the desert zone). In the wet period, spatial heterogeneity becomes evident: surface water continues to dominate groundwater recharge in the oasis zone (92.7%), whereas groundwater recharge to surface water prevails in the desert zone (50.5%). This study identifies a seasonally dynamic “discharge–infiltration–zonal regulation” bidirectional recharge pattern in arid inland river systems. The findings advance the mechanistic understanding of hydrological connectivity reconstruction within oasis–desert ecotones and provide a scientific basis for optimized regional water resource allocation and groundwater salinization risk mitigation. Full article

The Black Sea harbour porpoise (Phocoena phocoena relicta Abel, 1905) is an endemic cetacean with poorly understood spatial ecology in Bulgarian waters. This study aimed to update knowledge on its distribution, abundance, and habitat use throughout the Bulgarian Exclusive Economic Zone (EEZ). We conducted systematic aerial line-transect surveys in all four seasons between October 2022 and October 2023, combined with distance sampling and MaxEnt habitat modelling. Porpoises were present year-round across the EEZ, with marked seasonal shifts in distribution and habitat preferences. Highest densities were observed in spring, while winter distributions were concentrated offshore. Habitat suitability was dynamic, with key high-use areas identified near Cape Emine and in southern offshore waters near the Turkish border. Overall, about 40% of the EEZ represented high-suitability habitat. These findings provide the first comprehensive, year-round baseline for P. p. relicta in Bulgarian waters, highlighting the species’ flexible habitat use and seasonality. The study was conducted under extraordinary conditions due to regional military activity, which may have influenced porpoise behaviour and spatial patterns. The provided results are critical for designing effective conservation and management measures in the face of both natural and anthropogenic pressures and threats. Full article

Modern changes in natural and anthropogenic conditions in mountain ecosystems highlight the growing need to assess the status of medicinal plant populations and factors influencing their resilience. This study presents findings from a comprehensive investigation of three previously undocumented wild populations of Chelidonium majus L., discovered in the gorges of Kaindy, Shet-Merke, and Kolsai in the eastern part of the Kungey Alatau range. The research included analysis of phytocenotic conditions, population age structure, morphometric and morpho-anatomical traits of plants, along with physicochemical properties of soils. It was found that C. majus is associated with meadow-type moisture regimes and occurs spottily, mainly in moist microhabitats within open and semi-shaded plant communities. Population sizes ranged from 264 to 296 individuals, with average densities between 5.1 and 16.3 individuals per m². All studied populations exhibited complete ontogenetic spectra, dominated by generative stages (56.1–67.2%), indicating preserved reproductive potential despite limited recruitment at early developmental phases. Morpho-anatomical analysis revealed high phenotypic plasticity: under drier, poorer soil conditions, xeromorphic features developed, whereas mesomorphic structures prevailed in more favorable habitats. Soil analysis indicated that Shet-Merke population enjoys optimal growth and regeneration conditions. These results suggest that current C. majus populations in the region remain relatively stable, though strongly dependent on edaphic–hydrological and phytocenotic factors—underscoring the necessity of integrated monitoring to ensure conservation of medicinal plant resources. Full article

Wildfires have become more frequent and intense worldwide due to climate change and anthropogenic activities, which is why accurate and timely burned area mapping is essential for estimating damage and effective post-fire recovery planning. Synthetic Aperture Radar (SAR) data, which operates under all weather conditions and day-night cycles, offers a reliable source for burned area mapping. In this context, several studies have explored the use of dual-polarization SAR imagery and machine learning, yet the influence of multi-date, dual-orbit pass data and texture features remained unexplored. Therefore, this study aims to assess the Sentinel-1 acquisition configurations, varying in temporal depth and orbital direction, for wildfire burned area mapping, considering the recent Palisades wildfire event as a study area. A comparative study was conducted across different scenarios to evaluate the effectiveness of using single-date versus multi-date SAR imagery, the integration of ascending and descending orbit passes, and the contribution of Grey-Level Co-occurrence Matrix texture features. The performance of Random Forest (RF) and Extreme Gradient Boosting classifiers was analyzed through the scenarios mentioned above. The single-date configuration using RF achieved an accuracy of 82.34%, F1-score of 81.43%, precision of 83.07%, recall of 80.84%, and ROC-AUC of 90.88%, whereas the multi-date approach reached 85.78%, 85.15%, 86.45%, 84.56%, and 93.28%, respectively. Our study highlights the importance of acquisition configuration and texture information for reliable SAR-based wildfire burned area assessment. Full article

Climate change brings about changes in precipitation and temperatures, significantly increasing aridity in many areas. The southeast of the Iberian Peninsula is affected by climate change and increased aridity, which, together with anthropogenic factors, has increased the area affected by erosion. It is interesting to learn about aspects of aridity, desertification, and erosion in the southeast of the Iberian Peninsula. A literature review was conducted on issues related to climate change, aridity, desertification, and erosion, focusing on the southeast of the peninsula. In addition, field visits were made to verify some of the situations described in the literature. The results highlight the relationships among climate change, aridity, desertification, and erosion, and illustrate their impacts on the landscape and territory of the southeastern Iberian Peninsula. Furthermore, the results indicated a clear anthropogenic influence on the aridity–desertification–erosion loop. There has been a notable and rapid increase in erosion and aridification. Aridity is closely linked to erosion, and its harmful effects on soils in the southeastern Iberian Peninsula have intensified significantly. Full article

Understanding the intricate interrelationships among ecosystem services (ESs) is fundamental to advancing sustainable ecological management. This study focuses on the Taihu Basin and examines five representative ESs, including water yield (WY), carbon sequestration (CS), soil retention (SR), habitat quality (HQ), and crop production (CP), for the years 2000, 2010, and 2020. Spatial distribution characteristics and spatiotemporal dynamics were quantified through the combined application of the InVEST model, a food production model, and ArcGIS. Spearman correlation analysis and K-means clustering were then applied to characterize trade-offs and synergies among ESs and to delineate ecosystem service bundles at multiple spatial scales, including 1 km × 1 km grids, 10 km × 10 km grids, and the county level, while GeoDetector was used to identify the associated driving mechanisms. The results indicated that (1) between 2000 and 2020, the spatial distribution pattern of the ESs in the Taihu Basin underwent significant changes, with WY and SR increasing by 48.97% and 51.89%, respectively, while HQ, CS, and CP decreased by 17.2%, 15.5%, and 47.6%. (2) From an overall perspective of trade-offs and synergies, the interactions among ESs shifted from trade-offs (r < 0) to synergies (r > 0) as the scale increased. From the perspective of the spatial characteristics of trade-offs and synergies, the intensity of these interactions varied significantly with increasing scale, but the trend remained relatively stable. (3) The Taihu Basin can be categorized into six ES bundles (ESBs). ESB 1, ESB 3, ESB 4, and ESB 5 have relatively stable ES structures, whereas ESBs 2 and 6 display significant variations. (4) The primary factors influencing ESs vary significantly across different spatial scales, with land use/land cover (LULC) and the proportions of arable land, forestland, and buildings exhibiting strong explanatory power. This highlights the critical role of coupled natural and anthropogenic processes in shaping the spatial patterns of ESs. This study considers the spatiotemporal variation and scale dependence of ecosystem services, providing management recommendations tailored to different regions and spatial scales, and offering a scientific basis for regional ecological planning and watershed governance. Full article