Search Results (106)

Karst groundwater systems are critical to water supply and ecological sustainability in northern China, yet their heterogeneity poses challenges for flow characterization. The Yuquan Mountain (YM) Spring, historically a major karst spring in western Beijing, has experienced persistent drying, raising concerns about its recharge and flow mechanisms. This study integrates published isotope data, spatial distributions of Na⁺ and Cl⁻ as hydrochemical tracers, groundwater age estimates, and geophysical survey results to assess the recharge sources and flow pathways within the YM Spring catchment area. The analysis identifies two major recharge zones: the Tanzhesi area, primarily recharged by direct infiltration of precipitation through exposed carbonate rocks, and the Junzhuang area, which receives mixed recharge from rainfall and Yongding River seepage. Three potential flow pathways are proposed, including shallow flow along faults and strata, and a deeper, speculative route through the Jiulongshan-Xiangyu syncline. The synthesis of multiple lines of evidence leads to a refined conceptual model that illustrates how geological structures govern recharge, flow, and discharge processes in this karst system. These findings not only enhance the understanding of subsurface hydrodynamics in complex geological settings but also provide a scientific basis for future spring restoration planning and groundwater management strategies in the regions. Full article

Understanding groundwater quality in karst environments is essential, particularly in semi-arid regions where water resources are highly vulnerable to both climatic variability and anthropogenic pressures. The Ghar Boumaaza karst aquifer, located in the semi-arid Tlemcen Mountains of Algeria, represents a critical yet understudied water resource increasingly threatened by climate change and human activity. This study integrates hydrochemical analysis, multivariate statistical techniques, and predictive modeling to assess groundwater quality and characterize the relationship between total dissolved solids (TDSs) and discharge (Q). An analysis of 66 water samples revealed that 96.97% belonged to a Ca²⁺–HCO₃⁻ facies, reflecting carbonate rock dissolution, while 3% exhibited a Cl⁻–HCO₃⁻ facies associated with agricultural contamination. A principal component analysis identified carbonate weathering (40.35%) and agricultural leaching (18.67%) as the dominant drivers of mineralization. A third-degree polynomial regression model (R² = 0.953) effectively captured the nonlinear relationship between TDSs and flow, demonstrating strong predictive capacity. Independent validation (R² = 0.954) confirmed the model’s robustness and reliability. This study provides the first integrated hydrogeochemical assessment of the Ghar Boumaaza system in decades and offers a transferable methodological framework for managing vulnerable karst aquifers under similar climatic and anthropogenic conditions. Full article

Elevational gradients in temperature, moisture, and vegetation strongly influence soil nutrient content and stoichiometry in mountainous regions. However, exactly how total, microbial, and enzymatic carbon (C), nitrogen (N), and phosphorus (P) stoichiometry vary with elevation in karst peak-cluster depressions remains poorly understood. To address this, we studied soil total, microbial, and enzymatic C:N:P stoichiometry in seasonal rainforests within karst peak-cluster depressions in southwestern China at different elevations (200, 300, 400, and 500 m asl) and depths (0–20 and 20–40 cm). We found that soil organic carbon (SOC), total nitrogen (TN), and the C:P and N:P ratios increased significantly with elevation, whereas total phosphorus (TP) decreased. Microbial phosphorus (MBP) also declined with elevation, while the microbial N:P ratio rose. Activities of nitrogen- (β-N-acetylglucosaminidase and L-leucine aminopeptidase combined) and phosphorus-related enzymes (alkaline phosphatase) increased markedly with elevation, suggesting potential phosphorus limitation for plant growth at higher elevations. Our results suggest that total, microbial, and enzymatic soil stoichiometry are collectively shaped by topography and soil physicochemical properties, with elevation, pH, and exchangeable calcium (ECa) acting as the key drivers. Microbial stoichiometry exhibited positive interactions with soil stoichiometry, while enzymatic stoichiometry did not fully conform to the expectations of resource allocation theory, likely due to the functional specificity of phosphatase. Overall, these findings enhance our understanding of C–N–P biogeochemical coupling in karst ecosystems, highlight potential nutrient limitations, and provide a scientific basis for sustainable forest management in tropical karst regions. Full article

Urban systems are the spatial carriers of social and economic relations at the regional level, and their relational and structural resilience are key to regional coordination and sustainable development, attracting widespread attention from scholars. In order to analyze the internal relationships of urban agglomerations in underdeveloped mountainous regions and optimize their spatial resource allocation and resilience, this study takes the urban agglomeration of Qiandongnan in China as an example and researches their internal relationships, development potential, and influencing factors based on quantitative methods such as social network analysis. The results show that the urban cluster in Qiandongnan presents “large dispersion and small aggregation” distribution characteristics, with the karst landscape as the main influencing factor; the spatial network exhibits a scale-free morphology with an obvious core–periphery structure, demonstrating moderate stability but poor completeness, weak equilibrium, and low overall resilience; only 15.61% of nodes demonstrate high competitiveness; urban units with functional roles serve as critical network nodes; urban units’ development potential is divided into three tiers (with 47.31% being medium-high), although overall levels remain low; and the development potential, overall network, individual network, and network resilience of urban units are all positively correlated, with economic and transportation development conditions being the main influencing factors. Based on the abovementioned findings, this study proposes a “multi-level resilience promotion path for network structure optimization”, which provides a theoretical basis and optimization control methods for the reconstruction and synergistic development of urban agglomerations. It also serves as a reference for the development planning of urban systems in other underdeveloped mountainous regions. Full article

As a core karst region in Southwest China, Guanling County plays a crucial role in regional ecological governance. This study integrates the InVEST model, landscape pattern index analysis, and the MGWR spatial model to systematically explore the dynamic mechanisms of habitat quality in Guanling’s karst mountains. Key findings include: (1) Landscape pattern alterations exhibit significant impacts on habitat quality, characterized by strong spatial heterogeneity; (2) Expansion of forest and grassland effectively buffers the negative effects of construction land expansion, forming an ecological compensation mechanism through enhanced landscape connectivity; (3) Between 2000 and 2020, the proportion of high-importance habitat quality zones increased from 54.79% to 56.16%, with moderate-importance zones stabilizing at approximately 7.80% and general-importance zones growing to 2.46%. The results provide a multi-scale analytical framework for habitat protection and land use optimization in fragile karst ecosystems. Full article

Karst mountain areas, as complex geological systems formed by carbonate rock development, possess unique three-dimensional spatial structures and hydrogeological processes that fundamentally influence regional ecosystem evolution, land resource assessment, and sustainable development strategy formulation. In recent years, through the implementation of systematic ecological restoration projects, the ecological degradation of karst mountain areas in Southwest China has been significantly curbed. However, the research on the fine-grained land use mapping and quantitative characterization of spatial heterogeneity in karst mountain areas is still insufficient. This knowledge gap impedes scientific decision-making and precise policy formulation for regional ecological environment management. Hence, this paper proposes a novel methodology for land use mapping in karst mountain areas using very high resolution (VHR) remote sensing (RS) images. The innovation of this method lies in the introduction of strategies of geographical zoning and stratified object extraction. The former divides the complex mountain areas into manageable subregions to provide computational units and introduces a priori data for providing constraint boundaries, while the latter implements a processing mechanism with a deep learning (DL) of hierarchical semantic boundary-guided network (HBGNet) for different geographic objects of building, water, cropland, orchard, forest-grassland, and other land use features. Guanling and Zhenfeng counties in the Huajiang section of the Beipanjiang River Basin, China, are selected to conduct the experimental validation. The proposed method achieved notable accuracy metrics with an overall accuracy (OA) of 0.815 and a mean intersection over union (mIoU) of 0.688. Comparative analysis demonstrated the superior performance of advanced DL networks when augmented with priori knowledge in geographical zoning and stratified object extraction. The approach provides a robust mapping framework for generating fine-grained land use data in karst landscapes, which is beneficial for supporting academic research, governmental analysis, and related applications. Full article

The surface fragmentation of karst landscapes leads to a high degree of coupling between fire scar site boundaries and topographic relief. However, the applicability of spatio-temporal data fusion methods for fire scar extraction in such geomorphological areas remains systematically unevaluated. This study developed a spatial–temporal adaptive fusion model integrating Landsat 30-m data with MODIS daily observations to generate continuous high-precision dNBR datasets. Using a typical karst fire region in Guizhou and Yunnan, China, as a case study, we validated the method’s effectiveness for fire trace extraction in fragmented landscapes. The proposed fusion technique addresses cloud cover limitations in humid climates by constructing continuous NBR time series, enabling precise fire boundary delineation and severity quantification. We comparatively implemented multiple fusion approaches (FSDAF, STARFM, and STDFA) and evaluated their performance through both spectral (RMSE, AD, and PSNR) and spatial (Edge, LBP, and SSIM) metrics. Key findings include the following: (1) FSDAF outperformed other methods in spectral consistency and spatial adaptation, particularly for heterogeneous mountainous terrain with fragmented vegetation. (2) Comparative experiments demonstrated that pre-calculating vegetation indices before temporal fusion (Strategy I) produced superior results to post-fusion calculation (Strategy II). Moreover, in our karst landscape study area, our proposed Hybrid Strategy selection framework can dynamically optimize the fusion process of multi-source satellite data, which is significantly better than a single fusion strategy. (3) The dNBR-based extraction achieved 90.00% producer accuracy, 69.23% user accuracy, and a Kappa coefficient of 0.718 when validated against field data. This study advances fire monitoring in karst regions by significantly improving both the spatio-temporal resolution and accuracy of burn scar detection compared to conventional approaches. The framework provides a viable solution for fire impact assessment in topographically complex landscapes under cloudy conditions. Full article

[Objective] This study aims to assess and predict the risks of water inrush and leakage during tunnel excavation in karst regions, where groundwater intrusion poses serious threats to construction safety and long-term hydrogeological sustainability. [Study area] This study is conducted in the Qigan Mountain, involving detailed hydrogeological surveys and hydrochemical analyses to understand the subsurface conditions. [Methods] Numerical simulation methods are employed to model the regional seepage field distribution under natural conditions and two excavation conditions, using MODFLOW. [Challenges] One of the main challenges is accurately estimating tunnel water inflow under varying geological and hydrological conditions. [Results] The simulation results indicate that under excavation with blocking conditions, tunnel water inflow reaches 31,932 m³/d, whereas without blocking, inflow surges to 359,199 m³/d. In contrast, the theoretical calculation estimates a water inflow of 131,445 m³/d, revealing considerable discrepancies between the methods. [Recommendations] These findings highlight an important point of reference for the prevention of water influx in karst tunnel construction. Full article

Landslides pose a significant threat to the safety and stability of settlements in karst regions worldwide. The long-standing tight balance state of settlement funding and infrastructure makes it difficult to allocate disaster prevention resources effectively against landslide impacts. There is an urgent need to fully leverage the landscape resources of karst settlements and develop landslide risk prevention strategies that balance economic viability with local landscape adaptability. However, limited research has explored the differential resilience characteristics and patterns of landslide disaster risk and settlement landscapes from a spatial coupling perspective. This study, based on landslide disaster and disaster-adaptive landscape data from a typical karst province in China, employs the frequency ratio-random forest model and weighted variance method to construct landslide disaster risk (LDR) and disaster-adaptive landscape (DAL) base maps. The spatial characteristics of urban, urban–rural transition zones, and rural settlements were analyzed, and the resilience differentiation and driving factors of the LDR–DAL coupling relationship were assessed using bivariate spatial autocorrelation and geographical detector models. The key findings are as follows: (1) Urban and peri-urban settlements exhibit a high degree of spatial congruence in the differentiation of LDR and DAL, whereas rural settlements exhibit distinct divergence; (2) the Moran’s I index for LDR and DAL is 0.0818, indicating that urban and peri-urban settlements predominantly cluster in H-L and L-L types, whereas rural settlements primarily exhibit H-H and L-H patterns; (3) slope, soil organic matter, and profile curvature are key determinants of LDR–DAL coupling, with respective influence strengths of 0.568, 0.555, and 0.384; (4) in karst settlement development, augmenting local vegetation in residual mountain areas and parks can help maintain forest ecosystem stability, effectively mitigating landslide risks and enhancing disaster-adaptive capacity by 6.77%. This study helps alleviate the contradiction between high LDR and weak disaster-adaptive resources in the karst region of Southwest China, providing strategic references for global karst settlements to enhance localized landscape adaptation to landslide disasters. Full article

The accelerating conversion of agricultural land to non-agricultural uses poses critical threats to food security and sustainable land management, particularly in ecologically fragile karst mountainous regions. This study investigated the spatiotemporal patterns and driving mechanisms of cropland non-agricultural conversion (CNAC) in the Qian-Gui karst region (Guangxi and Guizhou, China) from 2000 to 2020, employing land use datasets and socioeconomic indicators through geographically weighted regression (GWR) modeling. The results showed that (1) from 2000 to 2020, the CNAC rate in the Qian-Guizhou karst mountainous region reached 2.03%. The area of CNAC increased by 14.60 × 10⁴ hm², increasing 1.74 times in 2010–2020 compared to 2000–2010, showing a trend of rapid growth. Specifically, the growth rate of the CNAC area was the highest in apparent mountainous (110.36%) and quasi-mountainous counties (100.5%), followed by semi-mountainous counties (95.28%), while entirely mountainous (40.89%) and pure hilly counties (37.68%) experienced the lowest growth, revealing distinct regional disparities. (2) Spatially, CNAC exhibited a pattern of “high in the north and south, low in the central region”, and the overall level of CNAC displayed significant regional imbalances, with extreme grades distributed in provincial capitals, high and medium grades concentrated in prefecture-level city districts, and light and low grades mainly located in counties and districts (accounting for more than 55.56% of the total number of research units in the two time periods). (3) There was significant spatial heterogeneity in the driving effect of factors influencing CNAC. Agricultural output and population density showed the strongest positive correlations; effectively irrigated areas exhibited a growing influence over time (except for pure hilly counties); rocky desertification areas exerted a strengthened influence on CNAC in pure hilly counties, while their impact was relatively lower in other regions compared to other indicators. Therefore, when formulating policies to protect farmland, it is essential to take into account the specific conditions of different types of counties in mountainous areas and adopt management measures tailored to these regional characteristics. Full article

The source of sulfate in the groundwater of karst springs in the northern Taihang Mountains remains unclear due to the influence of multiple factors. To investigate this, 33 sampling points were selected in August 2022 across the exposed, covered, and buried areas of the spring basin, and water samples were collected. Hydrochemistry and sulfur–oxygen dual isotope methods were employed to examine the distribution characteristics of sulfate, δ¹⁸O_SO4, and δ³⁴S_SO4. Based on the distinct characteristics of sulfur isotopes from different sources, the sources of sulfate in various environments were qualitatively analyzed. Additionally, the contribution rates of each source were quantitatively determined using a Bayesian stable isotope mixing model. The results showed that the sulfate content in karst groundwater ranged from 16.68 to 156.84 mg/L, with an average of 62.22 mg/L, and indicated an increasing trend from exposed to covered to buried areas. The δ³⁴S_SO4 values in karst groundwater ranged from 3.1‰ to 13.5‰, with an average of 6.49‰, while the δ¹⁸O_SO4 values ranged from 2.9‰ to 10.3‰, with an average of 5.49‰. The δ³⁴S_SO4 values showed a general increasing trend across the exposed, covered, and buried areas, whereas the δ¹⁸O_SO4 values remained relatively stable across these areas. The analysis revealed that the primary sulfate sources in the exposed area were atmospheric precipitation, soil sulfate, chemical fertilizer, and sewage, contributing 19.6%, 63.5%, 9.4%, and 7.5%, respectively. In the covered area, the main sources were atmospheric precipitation, sulfide oxidation, soil sulfate, and gypsum dissolution, with contributions of 16.5%, 58.7%, 15.9%, and 8.9%, respectively. In the buried area, the sulfate primary originated from atmospheric precipitation, sulfide oxidation, and gypsum dissolution, contributing 11.6%, 78.5%, and 9.9%, respectively. This study provides critical insights into the sulfate sources in different environments, enhancing the understanding of groundwater sulfate pollution in the study area. These findings provide a scientific foundation for managing groundwater pollutants and resources in the karst regions of northern China. Full article

The epikarst (the subsurface cavernous part of karstic rock studied in the Bakony Regions, the Mecsek Mountains and the area of Pádis) was compared across several karst sample sites. Since the degree of cavity formation in the epikarst cannot be studied directly, statistical analysis of the measured resistivity values was used to determine and compare the characteristics of the epikarst at different sample sites and, thus, the associated karst areas. For this, the significance of bedrock resistivity values obtained by Vertical Electrical Sounding (VES) was determined by t-tests. The mean values and standard deviations along the profiles of the VES measurement sites were calculated and graphically represented. It was established that the epikarst of profiles with high resistivity mean values is thicker, and the epikarst is of heterogeneous cavity formation (cavity formation is of different degrees) at sites where the standard deviation of resistivity is high. The epikarst of some karst sample sites can be compared by their standard deviation fields since in areas with higher resistivity, a thicker epikarst results in more expanded cavities and a lower water table, while heterogeneous cavity formation causes different cavity sizes and different resistivities. At sites where the standard deviation fields overlap with each other, their epikarsts are similar, at those where they do not overlap, they are different, and at sites where the fields touch, their similarity is transitional. If the standard deviation fields overlap each other, those with higher mean values and higher standard deviation have more cavities and their cavity formation is more heterogeneous. The epikarst with these characteristic features is regarded as more mature because at a lower water table, a higher arithmetic mean of resistivity and a higher standard deviation can be established. The reliability of the comparisons is shown by the fact that those with a more mature epikarst are karstified to a greater degree. Full article

Territorial Space (TS) is characterized by its multifunctionality. The identification and management of Territorial Spatial Functions (TSFs) across multi-scale is crucial for achieving the SDGs. However, previous studies have primarily concentrated on the variations in TSFs within the administrative or grid units at a single scale, with multi-scale investigations remaining a challenge. This study focuses on the typical karst region of Guangxi province in China and develops a Multi-Scale Fusion model (MSF) for assessing TSFs and employs a coupling coordination degree (CCD) model to examine the TSFs relationships. Furthermore, principal component analysis (PCA) is used to classify various types of influencing factors, and the Revealed Comparative Advantage (RCA) index is employed to identify the primary types of influencing factors at the county level. The study integrates coupling coordination types and advantage factors into the zoning process. The results demonstrate: (1) Ecological function is the dominant function. At the administrative unit scale, production and living functions exhibit a spatial pattern of “high in the southeast and low in the northwest”, while ecological function shows the opposite pattern. Under grid units scale and multi-scale fusion, the high and low texture characteristics of production and ecological functions are more pronounced. (2) TSFs are primarily characterized by slight and moderate disorder. Slight disorder is widely distributed, while moderate disorder is predominantly found in the northwest karst mountainous regions. In contrast, coordinated relationships are more frequently observed in urban areas. (3) The driver types of TSFs can be categorized into four categories: Terrain-Population, Agriculture Development, Location-Economy, and Non-Agriculture Development. By integrating the TSFs relationships, six zones are delineated. Based on this, precise and differentiated optimization suggestions are proposed to promote orderly utilization and sustainable development of TS. Full article

Changes in species’ habitats provide important insights into the effects of climate change. Woonyoungia septentrionalis, a critically endangered species endemic to karst ecosystems, has a highly restricted distribution and is a key biological resource. Despite its ecological importance, the factors influencing its habitat suitability and distribution remain poorly understood. This study employed ecological niche modeling to predict the potential distribution of Woonyoungia septentrionalis across China and analyzed shifts in centroid location to explore migration pathways under current and future climate scenarios. The model exhibited high predictive accuracy (AUC = 0.988), indicating its robustness in assessing habitat suitability. Under current climatic conditions, Woonyoungia septentrionalis is predominantly found in the Guizhou–Guangxi border region, southeastern Yunnan, eastern Sichuan, southeastern Tibet, and parts of Chongqing, Hunan, and Hubei. Among these, the Guizhou-Guangxi border represents the primary suitable habitat. Temperature factors, particularly bio6 (minimum temperature of the coldest month) and bio7 (annual temperature range), were the most significant determinants of habitat suitability, contributing 43.29% and 12.65%, respectively. Soil cation exchange capacity (CEC) accounted for 15.82%, while precipitation had a relatively minor impact. Under future climate scenarios, suitable habitats for Woonyoungia septentrionalis are projected to shrink and shift toward higher altitudes and latitudes, increasing the risk of extinction due to the “mountain trap” effect, where migration is constrained by limited habitat at higher elevations. Stable habitats, particularly in Libo (Guizhou) and Huanjiang (Guangxi), are identified as critical refugia. We recommend prioritizing shrinking and stable habitats in Guizhou, Guangxi, and Yunnan for in situ conservation. Ex situ conservation efforts should focus on areas identified based on key environmental factors and predicted migration pathways to ensure the species’ long-term survival. This study provides both theoretical and practical guidance for the conservation of this species and its vulnerable habitat. Full article

Rosa roxburghii, a calciphilic species native to the mountainous regions of Southwest China, is renowned for its high vitamin C and bioactive components, making it valuable for culinary and medicinal uses. This species exhibits remarkable tolerance to the high-calcium conditions typical of karst terrains. However, the underlying mechanisms of this calcium resilience remain unclear. The Ca²⁺/cation antiporter (CaCA) superfamily plays a vital role in the transport of Ca²⁺ and other cations and is crucial for plant tolerance to metal stress. However, the roles and evolutionary significance of the CaCA superfamily members in R. roxburghii remain poorly understood. This study identified 22 CaCA superfamily genes in R. roxburghii, categorized into four subfamilies. The gene structures of these RrCaCAs show considerable conservation across related species. Selection pressure analysis revealed that all RrCaCAs are subject to purifying selection. The promoter regions of these genes contain numerous hormone-responsive and stress-related elements. qRT-PCR analyses demonstrated that H⁺/cation exchanger (CAX) RrCAX1a and RrCAX3a were highly responsive to Ca²⁺ stress, cation/Ca²⁺ exchanger (CCX) RrCCX4 to Mg²⁺ stress, and RrCCX11a to Na⁺ stress. Subcellular localization indicated that RrCAX1a is localized to the plant cell membrane, and its stable transformation in tobacco confirmed its ability to confer enhanced resistance to heavy Ca²⁺ stresses, highlighting its crucial role in the high-calcium tolerance mechanisms of R. roxburghii. This research establishes a foundation for further molecular-level functional analyses of the adaptation mechanisms of R. roxburghii to high-calcium environments. Full article