Search Results (180)

Current research on heritage corridors predominantly focuses on linear heritage in Europe and America, while studies in Asia urgently need to be expanded. This study investigates China’s linear heritage. Based on the minimum cumulative resistance (MCR) model, it conducts heritage corridor construction for the Henan section of the Sui–Tang Grand Canal, and reveals the following: (1) A total of 252 heritage sites were classified into three categories: canal hydraulic heritage (13.5%), canal settlement heritage (21.4%) and related heritage (65.1%), exhibiting a “local clustering under global dispersion” pattern with a core–secondary–edge structure. (2) The influence of natural–social resistance factors was ranked as follows: elevation > roads > land use > slope. Interwoven corridors were simulated by GIS and optimized to four primary corridors with multiple secondary corridors. (3) The transverse zone of the primary corridors was stratified into core area (0–10 km from the centerline), buffer area (10–25 km), and influence area (>25 km) with a total width of 25–30 km. The longitudinal section was partitioned into four subsections based on hydrological continuity and heritage density. Then, a tripartite conservation framework characterized by “heritage clusters–holistic corridor–transverse stratification and longitudinal section” was proposed. It aimed to provide insights into methodologies and content structuring for transnational linear heritage (e.g., the Silk Road and the Inca Trail). Full article

Per- and polyfluoroalkyl substances (PFASs) have attracted global attention due to their persistence and biological toxicity, becoming critical emerging contaminants in river and lake environments worldwide. Building upon existing studies, this work aims to comprehensively understand the pollution patterns, environmental behaviors, and potential risks of PFASs in freshwater systems, thereby providing scientific evidence and technical support for precise pollution control, risk prevention, and the protection of aquatic ecosystems and human health. Based on publications from 2002 to 2025 indexed in the Web of Science (WoS), bibliometric analysis was used to explore the temporal evolution and research hotspots of PFASs, and to systematically review their input pathways, pollution characteristics, environmental behaviors, influencing factors, and ecological and health risks in river and lake environments. Results show that PFAS inputs originate from both direct and indirect pathways. Direct emissions mainly stem from industrial production, consumer product use, and waste disposal, while indirect emissions arise from precursor transformation, secondary releases from wastewater treatment plants (WWTPs), and long-range atmospheric transport (LRAT). Affected by source distribution, physicochemical properties, and environmental conditions, PFASs display pronounced spatial variability among environmental media. Their partitioning, degradation, and migration are jointly controlled by molecular properties, aquatic physicochemical conditions, and interactions with dissolved organic matter (DOM). Current risk assessments indicate that PFASs generally pose low risks in non-industrial areas, yet elevated ecological and health risks persist in industrial clusters and regions with intensive aqueous film-forming foam (AFFF) use. Quantitative evaluation of mixture toxicity and chronic low-dose exposure risks remains insufficient and warrants further investigation. This study reveals the complex, dynamic environmental behaviors of PFASs in river and lake systems. Considering the interactions between PFASs and coexisting components, future research should emphasize mechanisms, key influencing factors, and synergistic control strategies under multi-media co-pollution. Developing quantitative risk assessment frameworks capable of characterizing integrated mixture toxicity will provide a scientific basis for the precise identification and effective management of PFAS pollution in aquatic environments. Full article

Although mountain vertical vegetation belts are key in revealing the response to climate change and the maintenance mechanism of biodiversity, traditional field surveys and remote sensing methods face significant limitations in the structurally complex tropical humid mountainous regions of Hainan Island. As bryophytes are good microclimate indicators and characteristic components of the structure of the tropical rainforest, they may be useful tools for the construction of a general scheme of the altitudinal zonation of tropical rainforests. We surveyed bryophyte communities across eight elevations and three vegetation types at LiMu Mountain, southern China. Bryophyte species alpha diversity increased significantly as elevation increased, while beta diversity showed the contrasting pattern. Bryophyte community composition differed significantly along elevation gradients and the distribution of vegetation types was clearly distinguished by three significantly different bryophyte assemblages with specific elevational range. Hierarchical partitioning revealed that microclimate outweighed topography in structuring communities, aligning with global patterns of bryophyte thermal sensitivity. Bryophytes are effective bioindicators for tropical rainforest elevational zonation, reflecting fine-scale environmental gradients. Their sensitivity to microclimate supports their utility in monitoring vegetation shifts under climate change, particularly in topographically complex regions. Full article

Predicting how vegetation–debris interactions reshape alternate sandbars under a steady subcritical flow remains poorly understood in laboratory-to-field scaling. This study quantified how vegetation density and layout interact with debris geometry to control scouring and deposition and developed an empirical tool to predict normalized bed-level changes. Flume experiments investigated how vegetation–debris interactions regulate the hydromorphodynamics of non-migrating alternate sandbars under a steady subcritical flow (Q = 0.003 m³/s; slope = 1/200). Vegetation patches were configured in two spatial layouts—upstream (apex) and river line (edge), at varying densities, with and without debris (I-type: wall-like; U-type: horseshoe-shaped). Results indicated that dense upstream vegetation combined with I-type debris produced the strongest morphodynamic response, generating maximum scour, corresponding to the maximum bed-elevation changes (Δz) normalized by water depth (h) (dimensionless Δz/h) values of −1.55 and 1.05, and sustaining more than 70% of the downstream morphodynamic amplitude. In contrast, U-type debris promoted distributed deposition with a milder scour, while sparse vegetation yielded weaker, more transient responses. Debris geometry-controlled flow partitioning: the I-type enhanced frontal acceleration, whereas the U-type facilitated partial penetration and redistribution. To integrate these findings into predictive frameworks, an empirical regression model was developed to estimate Δz/h from the vegetation density, distribution, and debris geometry, with an additional blockage index to capture synergistic effects. The model achieved 87.5% prediction within ±20% error, providing a practical tool for anticipating scour and deposition intensity across eco-hydraulic configurations. These insights advance intelligent water management by linking morphodynamic responses with predictive modeling, supporting flood-resilient river engineering, adaptive channel stability assessments, and nature-based solutions. Full article

A modified Johnson–Mehl–Avrami–Kolmogorov (JMAK) model, including the heating rates, was proposed in this study to improve the accuracy of isothermal austenite formation kinetics prediction. Since the ultrafast heating process affects the behavior of ferrite recrystallization and austenite formation before the isothermal process, which in turn influences the subsequent isothermal austenite formation kinetics, the effects of varying austenitization temperatures and heating rates on isothermal austenite formation in cold-rolled quenching and partitioning (Q&P) steel, which remain insufficiently understood, were systematically investigated. Under a constant heating rate, the austenite formation rate initially increases and subsequently decreases as the austenitization temperature rises from formation start temperature A_c1 to finish temperature A_c3, and complete austenitization is achieved more quickly at elevated temperatures. At a given austenitization temperature, an increased heating rate was found to accelerate the isothermal transformation kinetics and significantly reduce the duration required to achieve complete austenitization. The experimental results revealed that both the transformation activation energy ($Q$) and material constant ($k_0$) decreased with increasing heating rates, while the Avrami exponent ($n$) showed a progressive increase, leading to the development of the heating-rate-dependent modified JMAK model. The model accurately characterizes the effect of varying heating rates on isothermal austenite formation kinetics, enabling kinetic curves prediction under multiple heating rates and austenitization temperatures and overcoming the limitation of single heating rate prediction in existing models, with significantly broadened applicability. Full article

This study investigates H13 steel through Q-P-T (quenching–partitioning–tempering) heat treatment experiments, focusing on the effects of quenching and tempering temperatures on its microstructure and mechanical properties. Experimental results demonstrate that elevated heat treatment temperatures induce grain coarsening and increased hardness. Under the optimized thermal processing parameters of 1020 °C quenching followed by 530 °C tempering, H13 steel achieves an optimal balance between strength and toughness. This balanced performance effectively addresses the issue of insufficient toughness and susceptibility to fracturing when H13 steel is utilized as shank material. Full article

Plant sucrose transporters (SUTs) are essential membrane proteins that mediate sucrose phloem loading in source tissues and unloading in sink tissues. In addition to their role in carbohydrate partitioning, SUTs have been implicated in plant responses to both biotic and abiotic stresses. Our previous research demonstrated that silencing StSUT2 in potatoes (Solanum tuberosum) affects plant growth, flowering time, and tuber yield, with transcriptomic analysis suggesting its involvement in cell wall metabolic pathways. In this study, we further investigated the effects of StSUT2 inhibition on the cell wall structure and biotic stress response of potatoes. Transmission electron microscopy revealed that the tuber cell wall thickness of the StSUT2 RNA interference (RNAi) line RNAi-2 was reduced by 7.8%, and the intercellular space was increased by 214% compared with the wild-type plants. Biochemical analyses showed that StSUT2 silencing significantly decreased cellulose, hemicellulose, and lignin contents in both the leaves and tubers, e.g., tuber cellulose reduced by up to 20.1%, while pectin levels remained unaffected, with distinct effects on source leaves and sink tubers’ organs. Additionally, activities of cellulase, xyloglucan glycosyltransferase/hydrolase XTH, and polygalacturonase were elevated in RNAi lines, e.g., leaf cellulase increased by 43.3%, whereas the pectinase activity was unchanged. Pathogen inoculation assays demonstrated that StSUT2 RNAi lines were more susceptible to Ralstonia solanacearum bacterial wilt and Fusarium sulphureum dry rot, showing larger leaf lesions, wider tuber necrotic plaques, and severe seedling wilting. These findings demonstrate that silencing StSUT2 regulates the cell wall structure, composition, and the activity of cell wall-degrading enzymes, thereby reducing the plant’s resistance to fungal and bacterial pathogens. Full article

Groundwater fluoride contamination poses a significant threat to sustainable water resources and public health, yet conventional water quality analysis is both time-consuming and costly, making large-scale, sustainable monitoring challenging. Machine learning methods offer a promising, cost-effective, and sustainable alternative for assessing the spatial distribution of fluoride. This study aimed to develop and compare the performance of Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN) models for predicting groundwater fluoride contamination in the Datong Basin with the help of satellite embeddings from the AlphaEarth Foundation. Data from 391 groundwater sampling points were utilized, with the dataset partitioned into training (80%) and testing (20%) sets. The ANOVA F-value of each feature was calculated for feature selection, identifying surface elevation, pollution, population, evaporation, vertical distance to the rivers, distance to the Sanggan river, and nine extra bands from the satellite embeddings as the most relevant input variables. Model performance was evaluated using the confusion matrix and the area under the receiver operating characteristic curve (ROC-AUC). The results showed that the SVM model demonstrated the highest ROC-AUC (0.82), outperforming the RF (0.80) and MLP (0.77) models. The introduction of satellite embeddings improved the performance of all three models significantly, with the prediction errors decreasing by 13.8% to 23.3%. The SVM model enhanced by satellite embeddings proved to be a robust and reliable tool for predicting groundwater fluoride contamination, highlighting its potential for use in sustainable groundwater management. Full article

Alfalfa (Medicago sativa L.), as a globally crucial high-quality forage crop, frequently suffers from yield reduction and quality deterioration due to environmental stressors such as drought and salt. Nano-selenium (NSe) offers a viable solution to mitigate this challenge. However, the multi-level regulatory mechanisms of NSe in alfalfa remain unclear. Foliar NSe modulates nitrogen metabolism, antioxidant defense, and rhizosphere microbial community collaboration to enhance alfalfa yield and quality. Pot experiments demonstrated that foliar NSe (1–20 mg/L) enhanced seedling growth, elevated nutrient biosynthesis (soluble protein, amino acids), and boosted antioxidant capacity via activation of superoxide dismutase and glutathione peroxidase. Metabolomics in field trials revealed shoot-root metabolic partitioning: shoots were upregulated in α-linolenic acid metabolism (jasmonic acid, methyl jasmonate), while roots enriched amino acid biosynthesis (proline, arginine), achieving a synergistic enhancement between aboveground and belowground processes. Microbial community analysis indicated Actinobacteria enrichment and elevated soil urease activity in NSe-treated groups. These findings demonstrate that NSe coordinates carbon-nitrogen metabolism with antioxidant pathway activation to synergistically enhance alfalfa growth performance and nutritional quality. Full article

To quantify the spatiotemporal patterns of the water-level variations in the study area, we conducted cluster analysis of the temporally varying measurements across multiple hydrological stations. The temporal trends and change points were analyzed, followed by IHA-RVA quantification of the water-level alterations before and after change points. Cluster analysis demonstrated the following. (1) Hydrological stations segregate into two distinct groups at the Euclidean distance threshold d = 5, and into three clusters at d = 4, confirming the pronounced west–east heterogeneity in the lake. (2) The hydrological alteration degrees exhibit considerable variation across the lake’s sub-lakes (Qili, Muping, South Dongting, East Dongting), with marked heterogeneity persisting even among representative monitoring stations within individual sub-lakes. The water-level regimes in Qili Lake can be partitioned into two distinct periods, before and after the change point, exhibiting the highest hydrological alteration degree across the lake. Representative stations of the other sub-lakes fall into three periods. During the first phase of hydrological alteration, Zhouwenmiao, Jinshi, and Chenglingji exhibit moderate alteration. Throughout the second alteration phase, all the representative stations consistently exhibit moderate alteration, although significant heterogeneity emerges across hydrological indicators among the sub-lakes. (3) Downstream of Yangliutan station, the longitudinal profile exhibits terraced morphology, segmented into three distinct levels by two hydraulic knickpoints. This geomorphic configuration primarily controls both the localized stage reductions and the maintenance of elevated upstream water levels during dry seasons. Confronting the persistent dry-season stage declines at Yingtian Station, enhanced monitoring and conservation of terraced transition zones in South Dongting Lake must be prioritized, with implementation of the zoned control principle for water-level governance and lake management. This study establishes a scientific foundation for the protection and governance of Dongting Lake, thereby advancing sustainable utilization of its water resources. Full article

The Yellow River Delta region is not only a concentrated area of human activities in coastal zones, but also a zone strongly influenced by regional environmental changes, where land cover changes are significantly affected by natural factors. Current historical LUCC datasets overlook the importance of partitioning to obtain accurate information on the potential maximum distribution range, which may lead to uncertainties in climate and environmental predictions. This study aims to reconstruct historical cropland changes in the Yellow River Delta via a region-adapted allocation model, supporting improved LUCC data accuracy and related research. Based on historical river course, settlement, and cropland survey data, this study identifies natural factors using historical settlement density through correlation analysis. Subsequently, a reclamation suitability model conforming to regional characteristics was constructed, and it obtains the cropland changes in the Yellow River Delta Basin at a spatial resolution of 0.5′ × 0.5′ over five time periods since 1855. The research indicates the following: (1) Through the method of analyzing the correlation between historical settlement density and natural factors, it is found that elevation (−), soil pH (+), soil organic carbon density (−), and NDVI (+) are the primary natural factors influencing the distribution of farmland in the Yellow River Delta. (2) The amount of farmland in the Yellow River Delta increased initially and then decreased after 1885; the average reclamation rate increased from 5.65%, peaked at 23.46% in the early 20th century, and then fell back to 7.68%. Spatially, the reclamation area expanded from scattered local areas along the Yellow River towards the sea, with a distinct coastal distribution. (3) Evaluation through absolute difference analysis shows that, compared with the HYDE 3.2 data, our reconstruction reflects the impacts of coastal changes, river distribution, and regional policy history on the allocation results. Based on the findings of this study, relevant issues can be improved from two aspects: first, by correlating settlement density with natural factors to identify key regional natural factors, which can then be applied to the update of LUCC data in small spatial units and similar regions to enhance data accuracy; second, by referring to the historical laws of cropland reclamation and suitability conditions, to optimize the current land planning of the Yellow River Delta and balance cropland utilization with ecological protection. Full article

Understanding how environmental factors regulate photosynthetic energy partitioning is crucial for enhancing crop resilience in future climates. This study investigated the light-response dynamics of sweet sorghum (Sorghum bicolor L. Moench) leaves under combinations of CO₂ concentrations (250, 410, and 550 μmol mol⁻¹) and temperatures (30 °C and 35 °C), using integrated chlorophyll fluorescence measurements and mechanistic photosynthesis modeling. Our results revealed that elevating CO₂ from 250 to 550 μmol mol⁻¹ significantly increased the maximum electron transport rate (J_max) by up to 57%, and enhanced the effective light absorption cross-section (σ′_ik) by 64% under high light and elevated temperature (35 °C), indicating improved photochemical efficiency and light-harvesting capability. Concurrently, these adjustments reduced PSII down-regulation. Increased temperature stimulated thermal dissipation, reflected in a rise in non-photochemical quenching (NPQ) by 0.13–0.26 units, accompanied by a reduction in the number of excited-state pigment molecules (N_k) by 20–33%. The strongly coordinated responses between quantum yield (Φ_PSII) and σ′_ik highlight a dynamic balance among photochemistry, heat dissipation, and fluorescence. These findings elucidate the synergistic photoprotective and energy-partitioning strategies that sweet sorghum employs under combined CO₂ enrichment and heat stress, providing mechanistic insights for optimizing photosynthetic performance in C₄ crops in a changing climate. Full article

A large number of cities have created semantic 3D city models, but these models are rarely used as input data for simulations, such as noise and flooding, in the urban planning process. Reasons for this are that many simulations require detailed land cover (LC) and elevation data that are often not included in the 3D city models, and that there is no linkage between the elevation and land cover data. In this study, we design, implement and evaluate methods to handle LC and elevation data in a 3D city model. The LC data is stored in 2.5D or 3D in the CityGML modules Transportation, Vegetation, WaterBody, CityFurniture and LandUse, and a complete 3D LC partition is created by combining data from these modules. The entire workflow is demonstrated in the paper: creating 2D LC data, extending CityGML, creating 2.5D/3D data from the 2D LC data, dividing the LC data into CityGML modules, storing it in a database (3DCityDB) and finally visualizing the data in Unreal Engine. The study is part of the 3CIM project where a national profile of CityGML for Sweden is created as an Application Domain Extension (ADE), but the result is generally applicable for CityGML implementations. Full article

The Qinghai-Tibetan Plateau is one of the world’s most prominent biodiversity hotspots. Understanding the spatial patterns of ecological uniqueness in its plant communities is essential for uncovering the mechanisms of community assembly and informing effective conservation strategies. In this study, we analyzed data from 758 plots across 338 sites on the Qinghai-Tibetan Plateau. For each plot, the vegetation type was classified, and all plant species present, along with their respective abundance or coverage, were recorded in the database. To assess overall compositional variation, community β-diversity was quantified, while a plot-level approach was applied to determine the influence of local environmental conditions and community characteristics on ecological uniqueness. We used stepwise multiple regressions, variation partitioning, and structural equation modeling to identify the key drivers of spatial variation in ecological uniqueness. Our results show that (1) local contributions to β-diversity (LCBD) exhibit significant geographic variation—increasing with longitude, decreasing with latitude, and showing a unimodal trend along the elevational gradient; (2) shrubs and trees contribute more to β-diversity than herbaceous species, and LCBD is strongly linked to the proportion of rare species; and (3) community characteristics, including species richness and vegetation coverage, are the main direct drivers of ecological uniqueness, explaining 36.9% of the variance, whereas climate and soil properties exert indirect effects through their interactions. Structural equation modeling further reveals a coordinated influence of soil, climate, and community attributes on LCBD, primarily mediated through soil nutrient availability. These findings provide a theoretical basis for adaptive biodiversity management on the Qinghai-Tibetan Plateau and underscore the conservation value of regions with high ecological uniqueness. Full article

Quantifying the slip rate along geometrically complex strike-slip faults is essential for understanding kinematics and strain partitioning in orogenic systems. The Karlik Tagh forms the easternmost terminus of Tian Shan and represents a critical restraining bend along the sinistral strike-slip Gobi-Tian Shan Fault System. The North Karlik Tagh Fault (NKTF) is an important fault demarcating the north boundary of the Karlik Tagh. While structurally significant, it is poorly understood in terms of its late Quaternary tectonic activity. In this study, we analyze the offset geomorphology based on interpretations of satellite imagery, field survey, and digital elevation models derived from structure-from-motion (SfM), and we provide the first quantitative constraints on the late-Quaternary slip rate using the abandonment age of deformed fan surfaces and river terraces constrained by the ¹⁰Be cosmogenic dating method. Our results reveal that the NKTF can be divided into the Yanchi and Xiamaya segments based on along-strike variations. The NW-striking Yanchi segment exhibits thrust faulting with a 0.07–0.09 mm/yr vertical slip, while the NE-NEE-striking Xiamaya segment displays left-lateral slip at 1.1–1.4 mm/yr since 180 ka. In easternmost Tian Shan, the interaction between thrust and sinistral strike-slip faults forms a transpressional regime. These left-lateral faults, together with those in the Gobi Altai, collectively facilitate eastward crustal escape in response to ongoing Indian indentation. Full article