Search Results (2,989)

Karst aquifers, vital freshwater resources, are highly vulnerable to agricultural pollution, yet their hydro-geochemical responses remain poorly understood due to high spatial heterogeneity. This study aimed to unravel these complex responses in a subtropical karst agricultural catchment to provide a basis for its sustainable management. We employed high-frequency monitoring at a headwater spring (background), a depression well (hotspot), and the catchment outlet (integrated) in Southwest China. Using hydrological and geochemical data from 2017, we applied Principal Component Analysis (PCA) to apportion natural and anthropogenic sources. The main findings revealed significant spatial heterogeneity, with the depression well acting as a contamination hotspot characterized by rapid hydrological responses and elevated SO₄²⁻ and Cl⁻ concentrations. PCA successfully decoupled an “anthropogenic factor” (PC1, 40.5%) from a “natural weathering factor” (PC2, 25.2%). Critically, agricultural SO₄²⁻ at the hotspot was counter-intuitively higher during the wet season than the dry season, opposing the typical dilution pattern of background ions and revealing that depressions act as contaminant-concentrating pathways, whose risks are severely underestimated by traditional outlet monitoring. The anomalous sulfate dynamics reveal a cross-seasonal “storage-and-release” mechanism (legacy effect) within the karst Critical Zone, demonstrating that these systems can buffer and “remember” contaminants. Full article

This study investigates the influence of urban greenery on microclimate conditions in Novi Sad, a city characterized by a temperate oceanic climate, by integrating high-resolution remote sensing data with in situ measurements from 12 urban climate stations. Sentinel-2 imagery was used to capture vegetation patterns, including tree lines and small green patches, while air temperature data were collected across two climatically contrasting years. Vegetation extent and structural characteristics were quantified using NDVI thresholds (0.6–0.8), capturing variability in vegetation activity and canopy density. Results indicate that high-activity vegetation, particularly dense tree canopies, exerts the strongest cooling effects, significantly influencing air temperatures up to 750 m from measurement sites, whereas total green area alone showed no significant effect. Cooling effects were most pronounced during summer and autumn, with temperature reductions of up to 2 °C in areas dominated by mature trees. Diurnal–nocturnal analyses revealed consistent spatial cooling patterns, while seasonal variability highlighted the role of evergreen and deciduous composition. Findings underscore that urban heat mitigation is driven more by vegetation structure and composition than by green area size, emphasizing the importance of preserving high-canopy trees in urban planning. This multidimensional approach provides actionable insights for optimizing urban greenery to enhance microclimate resilience. Full article

Motivated by the strong seasonality of East Asian meteorology and its control on pollution episodes characterized by fluctuation level, we model the season-resolved climatology of the regional PM_2.5 connectivity over the Korean Peninsula. Using daily AirKorea data for 2016–2020, we (i) remove daily climatology and the peninsula-wide background (empirical orthogonal function; EOF1) to obtain residual signals; (ii) compute the sign-preserving multifractal detrended cross-correlation coefficient MFDCCA-$\rho \left(q,s\right)$; (iii) apply iAAFT surrogate significance across scales; and (iv) construct signed, weighted networks aggregated over short (5–15 d) and mid (15–30 d) bands for DJF/MAM/JJA/SON. Our analysis targets the seasonal climatology of fluctuation-level ($q$-dependent) connectivity by pooling seasons across years; this approach increases statistical robustness at 5–30-day scales and avoids diluting season-specific organization. We find negligible connectivity for $q<0$ (small fluctuations) but dense, seasonally organized networks for $q>0$ (strongest in winter–spring and at 15–30 days). After removing the EOF1, positive subgraphs form assortative regional backbones, while negative subgraphs reveal a northwest–southeast anti-phase dipole; the connectivity around Baengnyeongdo (B) highlights a transboundary sentinel role in cool seasons. These results demonstrate that a season-resolved, fluctuation-level framework effectively isolates regional connectivity that would otherwise be masked in annual aggregates or by the peninsula-wide background. Full article

The Strait of Gibraltar (SG) is a key biogeographic and ecological corridor connecting the Mediterranean Sea and the Atlantic Ocean, enabling the seasonal migrations of fin whales (Balaenoptera physalus). The objective of this study was to characterize, for the first time, the spatial and temporal exposure of the species to maritime traffic during its migration through the SG, quantifying movement patterns, individual composition, and collision risk to identify critical areas for conservation. Validated observations collected between April 2016 and October 2024, with additional records in January and March 2025, were integrated with EMODnet vessel density layers to assess monthly distributions of sightings, individuals, calves, migration patterns, and behavior. A total of 347 sightings comprising 692 individuals were recorded, revealing predominantly westward movements between June and August. Spatial overlap analyses indicated that the highest exposure occurred both near the Bay of Algeciras/Gibraltar and in the northern half of the Central SG, where cargo ship and tanker traffic coincides with dense migration routes and where injuries have been documented in the field. These findings delineate high-risk areas for fin whales throughout the SG and provide an empirical basis for spatial management measures, including speed reduction zones, adaptive route planning, and the possible designation of the area as a cetacean migration corridor. The proposed measures aim to mitigate collision risk and ensure long-term ecological connectivity between the Mediterranean and the Atlantic. Full article

Landslide disasters pose severe threats to mountainous regions, where accurate monitoring and scientific prediction are crucial for early warning and risk mitigation. This study addresses this challenge by focusing on the Outang Landslide, a representative large-scale bank slope in the Three Gorges Reservoir area known for its significant deformation responses to rainfall and reservoir-level fluctuations. The landslide’s behavior, characterized by notable hysteresis and nonlinear trends, poses a significant challenge to accurate prediction. To address this, we derived high-precision time-series deformation data by applying atmosphere-corrected Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) to Sentinel-1A imagery, with validation from GNSS measurements. A systematic analysis was then conducted to uncover the correlation, hysteresis, and spatial heterogeneity between landslide deformation and key influencing variables (rainfall, water level, temperature). Furthermore, we proposed a Spatio-Temporal Enhanced Convolutional Neural Network (STE-CNN), which innovatively converts influencing variables into grayscale images to enhance spatial feature extraction, thereby improving prediction accuracy. The results indicate that: (1) From June 2022 to March 2024, the landslide showed an overall downward displacement trend, with maximum settlement and uplift rates of −49.34 mm/a and 21.77 mm/a, respectively; (2) Deformation exhibited significant correlation, hysteresis, and spatial variability with environmental factors, with dominant variables shifting across seasons—leading to intensified movement in flood seasons and relative stability in dry seasons; (3) The improved STE-CNN outperforms typical prediction models in forecasting landslide deformation.This study presents an integrated methodology that combines InSAR monitoring, multi-factor mechanistic analysis, and deep learning, offering a reliable solution for landslide early warning and risk management. Full article

Accurate and nondestructive monitoring of tomato growth is essential for large-scale greenhouse production; however, it remains challenging for small-fruited cultivars such as cherry tomatoes. Traditional 2D image analysis often fails to capture precise morphological traits, limiting its usefulness in growth modeling and yield estimation. This study proposes an automated phenotyping framework that integrates deep learning-based instance segmentation with high-resolution 3D point cloud reconstruction and ellipsoid fitting to estimate fruit size and ripeness from daily video recordings. These techniques enable accurate camera pose estimation and dense geometric reconstruction (via SfM and MVS), while Nerfacto enhances surface continuity and photorealistic fidelity, resulting in highly precise and visually consistent 3D representations. The reconstructed models are followed by CIELAB color analysis and logistic curve fitting to characterize the growth dynamics. When applied to real greenhouse conditions, the method achieved an average size estimation error of 8.01% compared to manual caliper measurements. During summer, the maximum growth rate (g_max) of size and ripeness were 24.14%, and 95.24% higher than in winter, respectively. Seasonal analysis revealed that winter-grown tomatoes matured approximately 10 days later than summer-grown fruits, highlighting environmental influences on phenological development. By enabling precise, noninvasive tracking of size and ripeness progression, this approach is a novel tool for smart and sustainable agriculture. Full article

Climate change and its impacts on precipitation patterns have intensified the occurrence of prolonged dry periods in agricultural regions of Brazil, particularly in the MATOPIBA region (comprising the states of Maranhão, Tocantins, Piauí, and Bahia). This study analyzes the seasonal variability and trends of the Consecutive Dry Days (CDDs) index in the MATOPIBA region from 1981 to 2023. Daily precipitation data from the Brazilian Daily Weather Gridded Data (BR-DWGD) dataset were used for the analysis. The novelty of this work lies in its focus on the seasonal characterization of CDD across the entire MATOPIBA field of agriculture, addressing the following main research question: how have the frequency and persistence of dry spells evolved during the rainy and dry seasons over the past four decades? The methodology involved trend detection using the Mann–Kendall test and Sen’s Slope estimator. The results indicated that during the rainy season, the average CDD ranged from 20 to 60 days, with higher values concentrated in the states of Piauí and Bahia. In contrast, during the dry period, averages exceeded 100 days across most of the region. Trend analysis revealed a significant increase in CDD over extensive areas, particularly in Tocantins and Southern Bahia. The increasing trends were estimated at 1 to 4 days per decade during the rainy season and 4 to 14 days per decade in the dry period. Although a decreasing CDD trend was observed in small areas of Northern Maranhão, possibly associated with the influence of the Intertropical Convergence Zone, the overall scenario indicates a greater persistence of long dry spells. This pattern suggests an increase in vulnerability to water scarcity and agricultural losses. These findings highlight the need for implementing adaptation strategies, such as the use of drought-tolerant cultivars, conservation management practices, irrigation expansion, and public policies aimed at promoting climate resilience in the MATOPIBA region. Full article

Urban trees are exposed to multiple co-occurring stressors, including heat, drought, and pollution driven by intensified urbanization and climate change. These environmental pressures can compromise tree vitality by disrupting photosynthetic performance and oxidative balance. In this study, we assessed the structural, physiological, and biochemical responses of three common urban tree species (Tilia platyphyllos, Celtis occidentalis, and Platanus × hispanica) growing under urban environmental conditions in Novi Sad, Serbia. Leaf traits were measured during June and August to capture seasonal stress variation. Structural indicators (SPAD, leaf thickness, leaf temperature differential), chlorophyll fluorescence traits (Φ_II, Φ_NPQ, F_v′/F_m′), oxidative stress biomarkers (TBARS, proline, GSH), and antioxidant enzyme activities (APX, CAT) were quantified. The Tree Health Risk Index (THRI) was calculated to integrate multilevel responses. Results revealed species-specific differences, with Tilia exhibiting the highest sensitivity, characterized by notable photochemical declines and oxidative stress under urban conditions. Celtis showed moderate resilience, while Platanus demonstrated the most robust performance and emerged as a promising candidate for climate-resilient urban sites. Heatmap clustering and trait contribution analyses confirm oxidative stress biomarkers and chlorophyll fluorescence traits as key indicators of urban stress. This study emphasizes the importance of integrating functional trait-based approaches for assessing tree health in urban greening. Full article

China is developing renewable energy bases (REBs) in the desert and Gobi regions. However, the intermittency of renewable energy and the temporal mismatch between peak renewable generation and peak load demand severely disrupt the power supply reliability of these REBs. Hydrogen storage technology, characterized by high energy density and long-term storage capability, is an effective method for enhancing the power supply reliability. Therefore, this paper proposes a REB planning model in the desert and Gobi regions considering seasonal hydrogen storage introduction as well as electricity-carbon-hydrogen markets trading. Furthermore, a combination scenario generation method considering extreme scenario optimization is proposed. Among which, the extreme scenarios selected through an iterative selection method based on maximizing scenario divergence contain more incremental information, providing data support for the proposed model. Finally, the simulation was conducted in the desert and Gobi regions of Yinchuan, Ningxia Province, China, primarily verifying that (1) the REB incorporating hydrogen storage can fully leverage hydrogen storage to achieve seasonal and long-term electricity transfer and utilization. The project has a payback period of 10 years, with an internal rate of return of 13.30% and a return on investment of 16.34%, thus showing significant development potential. (2) Compared to the typical battery-involved REB, the hydrogen-involved energy storage facility achieved a 59.39% annual profit, a 10.98% internal rate of return, a 14.93% return on investment, and a 1.51% improvement in power supply reliability by sacrificing a 52.49% increase in construction cost. (3) Compared to REB planning based only on typical scenarios, the power supply reliability of REBs based on the proposed combination scenario generation method improved by 8.58%. Full article

Forests sustain high levels of biodiversity and essential ecosystem services, yet the impact of management practices on below-ground functioning remains difficult to assess. A comprehensive evaluation of ectomycorrhizal (ECM) fungal diversity is, therefore, required to better understand ecosystem dynamics. This study, conducted within the SelpiBioLife project, examined ECM community structure in two Pinus nigra J.F. Arnold forests in central Italy by integrating above- and below-ground sampling. Across 108 plots, ECM fruiting bodies (EMFb) were recorded during one fruiting season, and 54 soil cores were collected to characterize ECM root tips (EMRt) through morpho-anatomical analyses and ITS sequencing. Species richness and community composition were compared using rarefaction, PERMANOVA, NMDS, Mantel tests, and SIMPER analysis. A total of 70 EMFb species and 54 EMRt morphotypes were identified, displaying significant differences between sites and sampling types. EMFb surveys revealed greater richness, whereas EMRt reached sampling saturation only at one site, suggesting additional hidden diversity. Distinct community patterns were detected in ordination space, and weak correlations emerged between EMFb and EMRt dissimilarities, indicating complementary ecological information. These findings show that single-method monitoring underrepresents ECM diversity. Combined above- and below-ground investigations provide a more accurate basis for evaluating silvicultural impacts and maintaining forest ecosystem resilience. Full article

The soil freeze–thaw process is a dominant disturbance in the seasonally frozen ground and the active layer of permafrost, which plays a crucial role in the surface energy balance, water cycle, and carbon exchange and has a pronounced influence on vegetation phenology. This study proposes a novel density-based Freeze–Thaw Disturbance Index (FTDI) based on the identification of the freeze–thaw disturbance region (FTDR) over the Qinghai–Tibet Plateau (QTP). FTDI is defined as an areal density metric based on geomorphic disturbances, i.e., the proportion of FTDRs within a given region, with higher values indicating greater areal densities of disturbance. As a measure of landform clustering, FTDI complements existing freeze–thaw process indicators and provides a means to assess the geomorphic impacts of climate-driven freeze–thaw changes during permafrost degradation. The main conclusions are as follows: the FTDR results that are identified by the random forest model are reliable and highly consistent with ground observations; the FTDRs cover 8.85% of the total area of the QTP, and mainly in the central and eastern regions, characterized by prolonged freezing durations and the average annual ground temperature (MAGT) is close to 0 °C, making the soil in these regions highly susceptible to warming-induced disturbances. Most of the plateau exhibits low or negligible FTDI values. As a geomorphic indicator, FTDI reflects the impact of potential freeze–thaw dynamic phase changes on the surface. Higher FTDI values indicate a greater likelihood of surface thawing processes triggered by rising temperatures, which impact surface processes. Regions with relatively high FTDI values often contain substantial amounts of organic carbon, and may experience delayed vegetation green-up despite general warming trends. This study introduces the FTDI derived from the FTDR as a novel index, offering fresh insights into the study of freeze–thaw processes in the context of climate change. Full article

Corydalinae (dobsonfly) is one of the subfamilies of the megalopteran family Corydalidae. Species of Corydalinae are some of the largest freshwater insects in the world. Comparative analyses of mitochondrial genomes in Corydalinae were conducted. The evolutionary rates of 13 PCGs of fifty species in Corydalinae were estimated. The total PCGs of Corydalinae exhibited negative AT bias, ranging from −0.1810 to −0.1408. The Ka/Ks ratio of total PCGs in Corydalinae ranged from 0.1011 (Protohermes) to 0.1673 (Chloroniella). Phylogenetic analysis of Corydalinae was conducted using mitogenomes. Positive selection analyses, conducted based on the Corydalinae phylogenetic topology, revealed potential positively selected sites in the genera Acanthacorydalis, Corydalus, Neoneuromus, Nevromus, and Protohermes. These genera were distributed in areas characterized by marked seasonality and pronounced annual thermal amplitude variations. The observed divergence in potential positive selection sites and evolutionary rates might be attributed to differential adaptive evolution in response to climatic factors, potentially reflecting distinct molecular mechanisms underlying species-specific adaptation to rapid environmental shifts. Full article

Accurate assessment of avian community structure and bird-strike risk within airport ecosystems is vital for balancing aviation safety with biodiversity conservation. From October 2019 to July 2020, we conducted systematic bird surveys at Lincang Boshang Airport (Yunnan, China) and its surrounding area. By integrating taxonomic, functional, and phylogenetic diversity analyses, we examined spatial–temporal patterns of bird diversity and characterized bird-strike risk. In total, 4859 individuals of 148 species were recorded, representing 51 families and 15 orders. The avifauna was dominated by broadly distributed Oriental–Palearctic species, reflecting the pronounced biogeographic transition of southwestern Yunnan. Functional diversity (FD) and phylogenetic diversity (PD) differed significantly among habitats: wetlands exhibited the highest FD and PD, indicating strong functional and lineage overdispersion driven by high environmental heterogeneity, whereas farmland showed the lowest FD and PD, consistent with stronger environmental filtering. Seasonal dynamics also shaped community structure, with the highest individual abundance in winter and the lowest species richness in spring. Standardized effect sizes (SES) revealed an overall tendency toward functional and phylogenetic clustering (SES < 0), most pronounced in forest and urban communities, while wetland assemblages consistently showed greater overdispersion across seasons. Risk evaluation indicated that low-risk species comprised 76.35% of the fauna, whereas high and very-high risk species accounted for only 3.38%, mainly large raptors (Accipitriformes) and pelicans/herons (Pelecaniformes). Integrating community patterns with risk distribution, we propose zone-specific management: remove standing water and tall grass in wetlands and farmland; optimize vegetation structure along forest–urban edges; and adopt acoustic/visual deterrents and dynamic management within core airport areas to reduce strike risk. Our findings provide a comprehensive baseline of airport bird diversity and bird-strike risk in southwestern China, offering evidence-based guidance for airport ecological safety management and regional biodiversity conservation. Full article

Although the atmospheric boundary layer height (ABLH) is a highly relevant parameter for various meteorological studies, the analysis of its behavior remains undersampled in South America, especially in Brazil. In this context, this work presents a monthly characterization of the ABLH during the convective period (Convective Boundary Layer Height-CBLH) using radiosonde data and a comparison between the monthly patterns obtained from ERA5 and COSMIC-2 data. The results demonstrate that, based on radiosonde data, the CBLH can be grouped into six regions (Northern Amazon, North, Northeast, Midwest, Southeast, and South), with seasonality varying according to the continentality and the climate to which they are exposed. The ERA5 and COSMIC-2 data show considerable agreement for most of the year [average absolute difference of [362 ± 182] m] and demonstrate the same seasonality observed in radiosondes for the North Amazon, North, Northeast, Southeast, and South regions. The highest discrepancies between ERA5 and COSMIC-2 occur during the fire season, mainly at Midwest region, reaching 802 m in July, likely linked to the sensitivity of the COSMIC-2 to fire plumes. Full article

Fungal communities inhabiting leaves are key players in ecosystem processes but remain largely unexplored in Southern Hemisphere temperate forests. We characterized the foliar mycobiota of Nothofagus pumilio, a dominant deciduous tree in Patagonian forests, using ITS1 metabarcoding across seasons and tree health conditions. We detected 426 fungal taxa, including a 40-Amplicon Sequence Variant (ASV) core mycobiome persisting year-round. Fungal richness and biomass increased significantly in autumn, coinciding with leaf senescence, and community composition shifted markedly between seasons. Spring leaves were enriched in pathogens and basidiomycetous yeasts, while autumn leaves hosted more saprotrophs, ascomycetous yeasts, and lichen-associated fungi. Tree health had limited influence on overall community structure, but symptomatic trees showed higher ASV richness and specific indicator taxa, including the pathogen Trichosporiella multisporum and members of the Taphrinaceae and Saccotheciaceae families. Despite taxonomic turnover, ecological guilds remained relatively stable, suggesting functional redundancy. These findings reveal a seasonal successional trajectory in the foliar mycobiota of N. pumilio, from early-colonizing endophytes in spring to diverse decomposer assemblages in autumn. This study provides the first high-throughput insight into the structure and dynamics of foliar fungal communities in Southern Hemisphere temperate forests, offering a baseline for understanding microbial roles in forest health and resilience. Full article