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14 pages, 3081 KiB  
Article
Habitat Distribution Pattern of François’ Langur in a Human-Dominated Karst Landscape: Implications for Its Conservation
by Jialiang Han, Xing Fan, Ankang Wu, Bingnan Dong and Qixian Zou
Diversity 2025, 17(8), 547; https://doi.org/10.3390/d17080547 - 1 Aug 2025
Viewed by 135
Abstract
The Mayanghe National Nature Reserve, a key habitat for the endangered François’ langur (Trachypithecus francoisi), faces significant anthropogenic disturbances, including extensive distribution of croplands, roads, and settlements. These human-modified features are predominantly concentrated at elevations between 500 and 800 m and [...] Read more.
The Mayanghe National Nature Reserve, a key habitat for the endangered François’ langur (Trachypithecus francoisi), faces significant anthropogenic disturbances, including extensive distribution of croplands, roads, and settlements. These human-modified features are predominantly concentrated at elevations between 500 and 800 m and on slopes of 10–20°, which notably overlap with the core elevation range utilized by François’ langur. Spatial analysis revealed that langurs primarily occupy areas within the 500–800 m elevation band, which comprises only 33% of the reserve but hosts a high density of human infrastructure—including approximately 4468 residential buildings and the majority of cropland and road networks. Despite slopes >60° representing just 18.52% of the area, langur habitat utilization peaked in these steep regions (exceeding 85.71%), indicating a strong preference for rugged karst terrain, likely due to reduced human interference. Habitat type analysis showed a clear preference for evergreen broadleaf forests (covering 37.19% of utilized areas), followed by shrublands. Landscape pattern metrics revealed high habitat fragmentation, with 457 discrete habitat patches and broadleaf forests displaying the highest edge density and total edge length. Connectivity analyses indicated that distribution areas exhibit a more continuous and aggregated habitat configuration than control areas. These results underscore François’ langur’s reliance on steep, forested karst habitats and highlight the urgent need to mitigate human-induced fragmentation in key elevation and slope zones to ensure the species’ long-term survival. Full article
(This article belongs to the Topic Advances in Geodiversity Research)
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19 pages, 15746 KiB  
Article
Description of a New Eyeless Cavefish Using Integrative Taxonomic Methods—Sinocyclocheilus wanlanensis (Cypriniformes, Cyprinidae), from Guizhou, China
by Yewei Liu, Tingru Mao, Hiranya Sudasinghe, Rongjiao Chen, Jian Yang and Madhava Meegaskumbura
Animals 2025, 15(15), 2216; https://doi.org/10.3390/ani15152216 - 28 Jul 2025
Viewed by 787
Abstract
China’s southwestern karst landscapes support remarkable cavefish diversity, especially within Sinocyclocheilus, the world’s largest cavefish genus. Using integrative taxonomic methods, we describe Sinocyclocheilus wanlanensis sp. nov., found in a subterranean river in Guizhou Province. This species lacks horn-like cranial structures; its eyes [...] Read more.
China’s southwestern karst landscapes support remarkable cavefish diversity, especially within Sinocyclocheilus, the world’s largest cavefish genus. Using integrative taxonomic methods, we describe Sinocyclocheilus wanlanensis sp. nov., found in a subterranean river in Guizhou Province. This species lacks horn-like cranial structures; its eyes are either reduced to a dark spot or absent. It possesses a pronounced nuchal hump and a forward-protruding, duckbill-shaped head. Morphometric analysis of 28 individuals from six species shows clear separation from related taxa. Nano-CT imaging reveals distinct vertebral and cranial features. Phylogenetic analyses of mitochondrial cytb and ND4 genes place S. wanlanensis within S. angularis group as sister to S. bicornutus, with p-distances of 1.7% (cytb) and 0.7% (ND4), consistent with sister-species patterns within the genus. Sinocyclocheilus wanlanensis is differentiated from S. bicornutus by its eyeless or degenerate-eye condition and lack of bifurcated horns. It differs from S. zhenfengensis, its morphologically closest species, in having degenerate or absent eyes, shorter maxillary barbels, and pelvic fins that reach the anus. The combination of morphological and molecular evidence supports its recognition as a distinct species. Accurate documentation of such endemic and narrowly distributed taxa is important for conservation and for understanding speciation in cave habitats. Full article
(This article belongs to the Section Aquatic Animals)
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34 pages, 31153 KiB  
Article
Study on Urban System Relationships and Resilience Promotion Strategies in Underdeveloped Mountainous Areas Based on Social Network Analysis: A Case Study of Qiandongnan Miao and Dong Autonomous Prefecture
by Huayan Yuan, Jinyu Fan, Jie Luo, Rui Ren and Hai Li
Land 2025, 14(7), 1500; https://doi.org/10.3390/land14071500 - 19 Jul 2025
Viewed by 335
Abstract
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 [...] Read more.
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
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22 pages, 3260 KiB  
Article
Evaluation of Habitat Quality in Karst Mountainous Areas of Guanling County Based on InVEST and MGWR Models
by Shuanglong Du, Zhongfa Zhou, Denghong Huang, Fei Dong, Xiandan Du, Yining Luo, Qingqing Dai and Yue Yang
Land 2025, 14(7), 1445; https://doi.org/10.3390/land14071445 - 10 Jul 2025
Viewed by 369
Abstract
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 [...] Read more.
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
(This article belongs to the Topic Nature-Based Solutions-2nd Edition)
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20 pages, 11158 KiB  
Article
Fine-Grained Land Use Remote Sensing Mapping in Karst Mountain Areas Using Deep Learning with Geographical Zoning and Stratified Object Extraction
by Bo Li, Zhongfa Zhou, Tianjun Wu and Jiancheng Luo
Remote Sens. 2025, 17(14), 2368; https://doi.org/10.3390/rs17142368 - 10 Jul 2025
Viewed by 363
Abstract
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 [...] Read more.
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
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32 pages, 13821 KiB  
Article
Spatiotemporal Evolution and Driving Factors of Karst Rocky Desertification in Guangxi, China, Under Climate Change and Human Activities
by Jialei Su, Meiling Liu, Qin Yang, Xiangnan Liu, Zeyan Wu and Yanan Wen
Remote Sens. 2025, 17(13), 2294; https://doi.org/10.3390/rs17132294 - 4 Jul 2025
Cited by 1 | Viewed by 385
Abstract
Guangxi is among China’s regions most severely affected by karst rocky desertification (KRD). Over the past two decades, global climate change and human activities have jointly led to significant changes in the extent and intensity of KRD in Guangxi. Given this context, it [...] Read more.
Guangxi is among China’s regions most severely affected by karst rocky desertification (KRD). Over the past two decades, global climate change and human activities have jointly led to significant changes in the extent and intensity of KRD in Guangxi. Given this context, it is crucial to comprehensively analyze the spatiotemporal evolution of KRD in Guangxi and its driving forces. This study proposed a novel three-dimensional feature space model for monitoring KRD in Guangxi. We then applied transition matrices, dynamic degree indices, and landscape metrics to analyze the spatiotemporal evolution of KRD. We also proposed a Spatiotemporal Interaction Intensity Index (STII) to quantify mutual influences among KRD patches. Finally, we used GeoDetector to analyze the driving factors of KRD. The results indicate the following: (1) The three-dimensional model showed high applicability for large-scale KRD monitoring, with an overall accuracy of 92.86%. (2) KRD in Guangxi exhibited an overall recovery–deterioration–recovery trend from 2000 to 2023. The main recovery phases were 2005–2015 and 2020–2023. During these phases, both severe and moderate KRD showed strong signals of recovery, including significant declines in area, number of patches, and Landscape Shape Index, along with persistently low STII values. In contrast, from 2015 to 2020, KRD predominantly deteriorated, primarily characterized by transitions from no KRD to potential KRD and from potential KRD to light KRD. (3) For severe KRD patches, the intensity of interaction required from neighboring patches to promote recovery exceeded that which led to deterioration, indicating the difficulty of reversing severe KRD. (4) Slope, land use, and elevation were the main drivers of KRD in Guangxi from 2000 to 2023. Erosive rainfall exhibited a higher explanatory power for KRD than average precipitation. Two-factor interactions significantly enhanced the driving forces of KRD. These findings provide a scientific basis for KRD management. Full article
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20 pages, 3653 KiB  
Article
Perceptions and Adaptive Behaviors of Farmers
by Jiaojiao Wang, Ya Luo, Yajie Ruan, Shengtian Yang, Guotao Dong, Ruifeng Li, Wenhao Yin and Xiaoke Liang
Water 2025, 17(13), 1993; https://doi.org/10.3390/w17131993 - 2 Jul 2025
Viewed by 212
Abstract
A clear understanding of drought perceptions and adaptation behaviors adopted by farmers is an important way to cope with climate change and achieve sustainable agricultural development. Karst is a type of landscape where the dissolving of the bedrock has created sinkholes, sinking streams, [...] Read more.
A clear understanding of drought perceptions and adaptation behaviors adopted by farmers is an important way to cope with climate change and achieve sustainable agricultural development. Karst is a type of landscape where the dissolving of the bedrock has created sinkholes, sinking streams, caves, springs, and other characteristic features. The study took the Huajiang karst dry-hot river valley area located in the southwestern part of Guizhou as the study area and used questionnaire survey method, the index of perception and the diversity index of adaptation strategy to explore the risk perception, adaptation perception and adaptation behavior of farmers to non-climatic droughts in the subtropical karst dry-hot valleys. A total of 530 questionnaires were distributed and 520 were returned. The results show that (1) the farmers’ risk perception of drought is stronger than adaptation perception, which shows that although farmers are well aware of the possible risks posed by drought, their subjective initiative and motivation to adapt to drought are weaker; (2) in the face of drought, farmers prioritize selected non-farm measures for adaptation, followed by crop management and finally water resource management; and (3) compared to farmers in arid and semi-arid regions, those in karst hot-dry river valleys exhibit distinct adaptive behaviors in response to drought, particularly in water resource management. Full article
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16 pages, 3885 KiB  
Article
An Interdisciplinary Perspective of the Karst Springs’ Areas as Drinking Water: Perusal from Northeastern Slovenia
by Natalija Špeh and Anja Bubik
Pollutants 2025, 5(3), 19; https://doi.org/10.3390/pollutants5030019 - 1 Jul 2025
Viewed by 647
Abstract
Karst aquifer systems are highly vulnerable due to their unique underground water flow characteristics, making them prone to contamination and abandonment. This study compares an active karst water source (Ljubija) with a previously abandoned one (Rečica) to assess freshwater quality and water protection [...] Read more.
Karst aquifer systems are highly vulnerable due to their unique underground water flow characteristics, making them prone to contamination and abandonment. This study compares an active karst water source (Ljubija) with a previously abandoned one (Rečica) to assess freshwater quality and water protection risks, especially as water scarcity becomes a concern during dry summer periods. The Ljubija and Rečica catchments, designated as water protection areas (WPAs), were monitored over a year (January–December 2020). Groundwater (GW) and surface water (SW) were analyzed twice a month during both dry and wet periods, adhering to European and national guidelines. An interdisciplinary approach integrated natural and human impact indicators, linking water quality to precipitation, hydrogeography, and landscape characteristics. After Slovene regulation standards (50 mg/L), the Ljubija source demonstrated stable water quality, with low nitrate levels (average 2.6 mg/L) and minimal human impact. In contrast, the Rečica catchment was more vulnerable, with its GW excluded from drinking use since the 1990s due to organic contamination, worsened by the area’s karst hydrogeology. In 2020, its nitrate concentration averaged 6.0 mg/L. These findings highlight the need for improved monitoring regulations, particularly for vulnerable karst water sources, to safeguard water quality and ensure sustainable use. Full article
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25 pages, 12803 KiB  
Article
Spatiotemporal Decoupling of Vegetation Productivity and Sustainable Carbon Sequestration in Karst Ecosystems: A Deep-Learning Synthesis of Climatic and Anthropogenic Drivers
by Runping Ma, Maofa Wang, Chengcheng Wang, Yibo Zhang, Xiang Zhou and Li Jiang
Sustainability 2025, 17(13), 5840; https://doi.org/10.3390/su17135840 - 25 Jun 2025
Viewed by 372
Abstract
Understanding the spatiotemporal dynamics of vegetation net primary productivity (NPP) and its drivers is critical to sustainable land -carbon management, carbon-neutral development, and ecological restoration in fragile karst landscapes. This study proposes a Pearson Correlation—Deep Transformer (PCADT) model that integrates attention mechanisms and [...] Read more.
Understanding the spatiotemporal dynamics of vegetation net primary productivity (NPP) and its drivers is critical to sustainable land -carbon management, carbon-neutral development, and ecological restoration in fragile karst landscapes. This study proposes a Pearson Correlation—Deep Transformer (PCADT) model that integrates attention mechanisms and geospatial covariates to enhance NPP estimation accuracy in Guangxi, China—a global karst hotspot. Leveraging multisource remote sensing data (2015–2020), PCADT achieves 10.7% higher predictive accuracy (R2 = 0.83 vs. conventional models) at 500 m resolution, thereby capturing the fine-scale heterogeneity essential for sustainability planning. The results reveal a significant annual NPP increase (4.14 gC·m−2·a−1, p < 0.05), with eastern areas exhibiting higher baseline productivity (1129 gC·m−2 in Wuzhou) but western regions showing steeper growth rates (5.2% vs. 2.1%). Vegetation carbon sequestration capacity, validated against MOD17A3HGF data (R2 = 0.998), demonstrates spatial consistency (east > west), with forest-dominated Wuzhou contributing 6.5 TgC annually. Mechanistic analyses identify precipitation as the dominant climatic driver (partial r = 0.62, p < 0.01), surpassing temperature sensitivity, while bimodal NPP-altitude peaks (300 m and 900 m) and land -use transitions (e.g., forest-to-cropland conversions) explain 18.5% of NPP variability and reduce regional carbon stocks by 4593 tC. The PCADT framework offers a scalable solution for precision carbon management by emphasizing the role of anthropogenic interventions—such as afforestation—in alleviating climatic constraints. It advocates for spatially adaptive strategies to optimize water resource utilization, enhance forest conservation, and promote sustainable land -use transitions. By identifying areas where water -scarcity relief and targeted afforestation would yield the highest carbon returns, the PCADT framework directly supports SDG 13 (Climate Action) and SDG 15 (Life on Land), providing a strategic blueprint for sustainable development in water-limited karst regions globally. Full article
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20 pages, 4784 KiB  
Article
Short-Term Application of Alfalfa Green Manure Increases Maize Yield and Soil Fertility While Altering Microbial Communities in Karst Yellow Clay Soil
by Xiaoye Gao, Shimei Yang, Yan He, Qiumei Zhao and Tao Zhang
Microorganisms 2025, 13(7), 1445; https://doi.org/10.3390/microorganisms13071445 - 21 Jun 2025
Viewed by 236
Abstract
Green manure effectively improves soil nutrients and crop yields, yet its partial substitution for chemical nitrogen fertilizer (CF) in maize systems remains underexplored in ecologically fragile Karst landscapes. To assess the effect of alfalfa green manure on maize yield, soil nutrients, enzymes, and [...] Read more.
Green manure effectively improves soil nutrients and crop yields, yet its partial substitution for chemical nitrogen fertilizer (CF) in maize systems remains underexplored in ecologically fragile Karst landscapes. To assess the effect of alfalfa green manure on maize yield, soil nutrients, enzymes, and microorganisms, we conducted a two-year field experiment comprising eight treatments: four CF levels (100%, 80%, 60%, and 0% of recommended CF) applied alone or combined with alfalfa green manure (CF100, AL_CF100, CF80, AL_CF80, CF60, AL_CF60, CF0, AL_CF0). The results showed that maize grain yield decreased with the sole reduction of chemical N fertilizer. Compared to the CF100 treatment, the AL_CF100 and AL_CF80 treatments significantly increased grain yield by an average of 21.8% and 16.9%, respectively. Additionally, the AL_CF60 treatment maintained maize grain yield in 2020 and significantly increased it in 2021. The AL_CF100 treatment significantly enhanced soil available N (AN) content, while soil Olsen-P (SOP) content and soil quality index (SQI) were significantly improved in the AL_CF100, AL_CF80, and AL_CF60 treatments. Alfalfa green manure application had no significant effect on soil bacterial and fungal communities. However, the CF rates positively influenced the relative abundances of bacterial phyla (Bacteroidota, Myxococcota, and Patescibacteria) and genera (Intrasporangium, Streptomyces, and Quadrisphaera), as well as fungal genera (Exophiala and Setophoma). α-Diversity analysis revealed that partial substitution of CF with alfalfa green manure did not significantly affect soil bacterial diversity (Ace, Shannon, and Sobs indices) or richness (Chao value). In contrast, chemical N fertilizer rates significantly altered the β-diversity of both bacteria and fungi. The soil AN, AK, sucrase activity, and the relative abundances of Bacteroidota, Streptomyces, and Instrasporangium showed significant positive relationship with maize grain yield. This study demonstrates that substituting 20% CF with alfalfa green manure optimizes maize productivity while enhancing soil health in Karst agroecosystems. Full article
(This article belongs to the Section Plant Microbe Interactions)
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22 pages, 6893 KiB  
Article
Spatio-Temporal Fusion of Landsat and MODIS Data for Monitoring of High-Intensity Fire Traces in Karst Landscapes: A Case Study in China
by Xiaodong Zhang, Jingyi Zhao, Guanzhou Chen, Tong Wang, Qing Wang, Kui Wang and Tingxuan Miao
Remote Sens. 2025, 17(11), 1852; https://doi.org/10.3390/rs17111852 - 26 May 2025
Viewed by 559
Abstract
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 [...] Read more.
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
(This article belongs to the Special Issue Remote Sensing Data Application for Early Warning System)
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17 pages, 3690 KiB  
Article
Impacts of Ecological Restoration Projects on Ecosystem Carbon Storage of Tongluo Mountain Mining Area, Chongqing, in Southwest China
by Lei Ma, Manyi Li, Chen Wang, Hongtao Si, Mingze Xu, Dongxue Zhu, Cheng Li, Chao Jiang, Peng Xu and Yuhe Hu
Land 2025, 14(6), 1149; https://doi.org/10.3390/land14061149 - 25 May 2025
Viewed by 578
Abstract
Surface mining activities cause severe disruption to ecosystems, resulting in the substantial destruction of surface vegetation, the loss of soil organic carbon stocks, and a decrease in the ecosystem’s ability to sequester carbon. The ecological restoration of mining areas has been found to [...] Read more.
Surface mining activities cause severe disruption to ecosystems, resulting in the substantial destruction of surface vegetation, the loss of soil organic carbon stocks, and a decrease in the ecosystem’s ability to sequester carbon. The ecological restoration of mining areas has been found to significantly enhance the carbon storage capacity of ecosystems. This study evaluated ecological restoration strategies in Chongqing’s Tongluo Mountain mining area by integrating GF-6 satellite multispectral data (2 m panchromatic/8 m multispectral resolution) with ground surveys across 45 quadrats to develop a quadratic regression model based on vegetation indices and the field-measured biomass. The methodology quantified carbon storage variations among engineered restoration (ER), natural recovery (NR), and unmanaged sites (CWR) while identifying optimal vegetation configurations for karst ecosystems. The methodology combined the high-spatial-resolution satellite imagery for large-scale vegetation mapping with field-measured biomass calibration to enhance the quantitative accuracy, enabling an efficient carbon storage assessment across heterogeneous landscapes. This hybrid approach overcame the limitations of traditional plot-based methods by providing spatially explicit, cost-effective monitoring solutions for mining ecosystems. The results demonstrate that engineered restoration significantly enhances carbon sequestration, with the aboveground vegetation biomass reaching 5.07 ± 1.05 tC/ha, a value 21% higher than in natural recovery areas (4.18 ± 0.23 tC/ha) and 189% greater than at unmanaged sites (1.75 ± 1.03 tC/ha). In areas subjected to engineered restoration, both the vegetation and soil carbon storage showed an upward trend, with soil carbon sequestration being the primary form, contributing to 81% of the total carbon storage, and with engineered restoration areas exceeding natural recovery and unmanaged zones by 17.6% and 106%, respectively, in terms of their soil carbon density (40.41 ± 9.99 tC/ha). Significant variations in the carbon sequestration capacity were observed across vegetation types. Bamboo forests exhibited the highest carbon density (25.8 tC/ha), followed by tree forests (2.54 ± 0.53 tC/ha), while grasslands showed the lowest values (0.88 ± 0.52 tC/ha). For future restoration initiatives, it is advisable to select suitable vegetation types based on the local dominant species for a comprehensive approach. Full article
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17 pages, 3101 KiB  
Article
Impact of Parent Rock and Land Use on the Distribution and Enrichment of Soil Selenium in Typical Subtropical Karst Regions of Southwest China
by Chunshan Xiao, Xing Xiong, Jianwei Bu, Zhongquan Hu, Jun Zhang, Chenzhou Yang and Yinhe Huang
Appl. Sci. 2025, 15(10), 5749; https://doi.org/10.3390/app15105749 - 21 May 2025
Viewed by 309
Abstract
Selenium (Se) is essential for various metabolic and physiological functions in the human body. However, the mechanisms of Se cycling in soils, particularly under different parent materials and land uses, remain understudied. This study investigates the spatial distribution and influencing factors of total [...] Read more.
Selenium (Se) is essential for various metabolic and physiological functions in the human body. However, the mechanisms of Se cycling in soils, particularly under different parent materials and land uses, remain understudied. This study investigates the spatial distribution and influencing factors of total Se in surface soils derived from limestone and sandstone in paddy and dryland systems in a Se-rich karst region of Southwest China. The mean Se content was 0.5 mg/kg, with 100% of samples exceeding national and global background levels, confirming Zheng’an County as a newly recognized Se-rich area. Soil Se concentrations, along with environmental variables such as soil organic matter (SOM), pH, elevation, slope, and trace elements (V, Cr, and Zn), were analyzed. One-way ANOVA revealed significant differences in Se content between parent materials and land-use types. Stepwise multiple regression identified SOM as the strongest predictor of Se, while Spearman correlation showed significant associations with topographic and chemical factors. These findings highlight the complex interactions between geology, land use, and topography in Se dynamics. Given the global distribution of karst landscapes, this research provides valuable insights into Se behavior in similar environments worldwide, with implications for land management and nutritional security. Full article
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20 pages, 10355 KiB  
Article
Spatial Coupling and Resilience Differentiation Characteristics of Landscapes in Populated Karstic Areas in Response to Landslide Disaster Risk: An Empirical Study from a Typical Karst Province in China
by Huanhuan Zhou, Sicheng Wang, Mingming Gao and Guangli Zhang
Land 2025, 14(4), 847; https://doi.org/10.3390/land14040847 - 13 Apr 2025
Viewed by 386
Abstract
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 [...] Read more.
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
(This article belongs to the Topic Nature-Based Solutions-2nd Edition)
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22 pages, 4571 KiB  
Article
Long-Term Analysis and Multi-Scenarios Simulation of Ecosystem Service Values in Typical Karst River Basins
by Shishu Lian, Anjun Lan, Zemeng Fan, Bingcheng Feng and Kuisong Xiao
Land 2025, 14(4), 824; https://doi.org/10.3390/land14040824 - 10 Apr 2025
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Abstract
This study, guided by the concept hat “lucid waters and lush mountains are invaluable assets”, focuses on explicating the ecological vulnerability characteristics of the Nanpan and Beipan River Basins, a typical karst river basin in Guizhou Province. In this article, a value equivalent [...] Read more.
This study, guided by the concept hat “lucid waters and lush mountains are invaluable assets”, focuses on explicating the ecological vulnerability characteristics of the Nanpan and Beipan River Basins, a typical karst river basin in Guizhou Province. In this article, a value equivalent table was built to calculate the ecosystem service value (ESV) within the basin from 2000 to 2020. The patch landscape and urban simulation model (PLUS) was improved to forecast ecosystem changes under four scenarios in the future. The Getis-Ord Gi*statistic, a spatial analysis tool, was introduced to identify and interpret the spatial patterns of ESVs in the study area. The research indicates that: (1) from 2000 to 2020, the spatial pattern of ecosystem has significantly improved, and with a notable ESV increase in the Nanpan and Beipan River Basins, especially the fastest growth from 2005 to 2010. Forest and grassland ecosystems are the main contributors to ESV within the basin, and the spatial distribution of ESV shows a decreasing trend from southeast to northwest. (2) Under different scenarios, forest ecosystem still would have the highest contribution rate to update the ESV between 2010 and 2035. The ESV is the lowest under the cropland protection scenario, amounting to CNY 104.972 billion. Compared to other scenarios, the ESV is higher under the sustainable development scenario, reaching CNY 106.786 billion, and this scenario provides a more comprehensive and balanced perspective, relatively achieving a harmonious coexistence between humans and nature. (3) The hot spots of ESV are mainly concentrated in the southeast and along the riverbanks of the study area. Urban ecosystems are the cold spots of ESV, indicating that protecting the ecosystems along the riverbanks is crucial for ensuring the ecological security and sustainable development of karst mountainous river basins. In the future development of karst mountainous river basins, it is necessary to strengthen ecological restoration and governance, monitor soil erosion through remote sensing technology, optimize the layout of territorial space to implement the policy of green development, and promote the harmonious coexistence of humans and nature, ensuring the ecological security and sustainable development of the basins. Full article
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