Search Results (528)

Rice, as one of the world’s three major staple crops, provides a food source for nearly half of the global population. Timely and accurate acquisition of rice cultivation information is crucial for optimizing spatial distribution, guiding production practices, and safeguarding food security. Taking Bishan District of Chongqing as the study area, NDVI values were derived from Sentinel-2 satellite imagery to construct standard NDVI time-series curves for typical land-cover types, including paddy fields, dryland, water bodies, construction land, and forest and grassland. These curves were then used in the NDVI time-series characteristics method to identify paddy fields. First, the Euclidean distance between the standard NDVI time series of paddy fields and those of other land-cover types was calculated. The sum of these element-wise differences was used to determine the upper threshold for paddy field extraction. Second, the mean absolute deviation between elements of the rice sample dataset and the standard NDVI time series was calculated for each time step. The sum of these average deviations was used as the lower threshold to extract the initial paddy field data. On this basis, an extreme-value constraint was introduced to reduce the interference of mixed pixels from forest and grassland and construction land, effectively eliminating anomalous pixels and improving the accuracy of paddy field identification. Finally, the results were validated and compared with those from other extraction methods. The results indicate that: (1) Paddy fields exhibit distinct NDVI time-series characteristics throughout the entire growing season, which can serve as a reference standard. By calculating the Euclidean distance between the NDVI curves of other land-cover types and those of paddy fields, similarity can be quantified, enabling rice identification. (2) The extraction method based on NDVI time-series characteristics successfully identified paddy fields through the appropriate setting of thresholds. The overall accuracy and Kappa coefficient remained high, while the F1-score consistently exceeded 0.8, indicating a good balance between precision and recall. Furthermore, the bootstrap uncertainty analysis revealed narrow 95% confidence intervals across all metrics, confirming the robustness and statistical reliability of the results. Overall, the proposed method demonstrated excellent performance in paddy field classification and significantly outperformed traditional machine learning methods implemented on the GEE platform. (3) Mixed pixels considerably affected the accuracy of rice classification; however, the introduction of the extreme-value constraint effectively mitigated this influence and further improved classification results. Full article

Ecological restoration of mine wastelands is central to biodiversity conservation and ecosystem recovery worldwide. However, the long-term ecological consequences of active restoration versus natural regeneration remain debated, particularly in mountainous karst landscapes. Using a space-for-time substitution, we established a five-stage chronosequence—recently abandoned, 10 years, 20 years, 30 years, and a late-successional forest (>35 years)—in a typical underground coal-mine wasteland in eastern Yunnan, southwest China. Each age class contained paired active restoration and natural regeneration sites; the late-successional forest served as a reference. We surveyed nested vegetation plots (20 × 20 m with shrub and herb subplots) in summer and autumn, recorded vertebrate species with camera traps, and quantified α-diversity (species richness, Shannon–Wiener diversity, Simpson’s diversity, Pielou’s evenness) and β-diversity (Bray–Curtis dissimilarity, non-metric multidimensional scaling). Overall plant α-diversity was highest in natural regeneration and lowest in active restoration, whereas tree-layer diversity was highest in active restoration and shrub and herb layers were richer under natural regeneration. Preliminary data from our camera traps suggested that animal species richness ranked late-successional forest > natural regeneration > active restoration, but evenness peaked in active restoration, suggesting early-stage homogenization. Plant β-diversity indicated stronger compositional divergence among active restoration sites and greater similarity between natural regeneration and the reference forest; both modes converged toward the reference forest over time but followed distinct patterns. These findings suggest that active restoration accelerates structural development yet increases between-site heterogeneity, whereas natural regeneration maintains higher overall diversity and compositional similarity to reference communities. Our results provide preliminary empirical guidance for selecting restoration strategies in similar karst coal-mine landscapes. Full article

With the rapid advancement of urbanization, urban heat environment issues have become increasingly severe, presenting significant challenges to sustainable urban development. Although previous research has demonstrated the substantial impact of urban morphology on land surface temperature (LST), there is still a lack of comprehensive research on the non-stationary effects of urban morphology on seasonal LST at the block scale. Therefore, this study establishes a comprehensive research framework, utilizing urban functional zones in the core area of Chongqing as the primary research unit, to investigate the seasonal fluctuations in the spatial distribution of LST across various functional zones. Combining Random Forest (RF) with multiscale geographically weighted regression methods (MGWR), the study systematically analyzes the numerical and spatial distribution characteristics of how urban morphology factors influence LST from global and local perspectives. The results indicate that (1) the LST in central Chongqing exhibits marked seasonal variation and a distinct “mountain-water pattern,” with industrial zones consistently hotter and public service areas cooler; (2) biophysical surface parameters and building morphological indicators make a high relative contribution to LST changes across seasons, particularly in public service and commercial areas; (3) building density (BD) and biophysical surface parameters primarily exert local impacts on LST changes, while floor area ratio (FAR) and building height range (RBH) have a global effect. These findings provide new insights into the driving mechanisms of urban heat environments and offer scientific evidence for regulating and mitigating urban heat environment issues across different seasons and urban types. Full article

Climate change and human activities profoundly impact forest biodiversity, with effects projected to intensify. The Symplocos genus, a diverse assemblage of flowering plants prevalent in the subtropical and tropical forests of the Yangtze River in China, holds substantial economic and medicinal value. However, the impacts of climate change and human activities on the habitat ranges of Symplocos species in China remain unclear. This study employed an optimized Maxent model to predict potential habitats for four key Symplocos species—Symplocos setchuensis, Symplocos chinensis, Symplocos groffii, and Symplocos sumuntia under current and multiple future climate scenarios (SSP1-2.6 and SSP5-8.5 during the 2070s and 2090s). Moreover, we assessed the relative importance of various predictors, including climatic, topographic, soil, and anthropogenic factors, in shaping their habitat range patterns. Currently, the habitat ranges of the four Symplocos species are mainly concentrated in southern China, exhibiting notable differences in areas of high habitat suitability. Furthermore, the habitat ranges of S. setchuensis, S. chinensis, S. groffii, and S. sumuntia were primarily influenced by the mean temperature of the driest quarter (bio9), the minimum temperature of the coldest month (bio6), the temperature annual range (bio7), and precipitation seasonality (bio15), respectively. Notably, the habitat suitability of S. setchuensis, and S. sumuntia increased at a progressively slower rate with human footprint. Under future climate scenarios, S. groffii and S. sumuntia are projected to expand their ranges significantly northward, while S. chinensis is expected to maintain stable habitat, and S. setchuensis may face considerable contractions. Our results underscore the importance of climate and human activities in shaping the habitat ranges of Symplocos species, revealing distinct adaptive responses among the four species under future climate change. Full article

Ordovician marine red beds (OMRBs) are widely developed along the margins of Gondwana and represent distinctive limestone facies. These red beds are known for their diverse sedimentary structures and have been described by scholars as the “fashionable facies” in geological history. However, their characteristics and classification remain controversial. Multiple hypotheses about their origin have also hindered a clear understanding of these strata. Therefore, this study focuses on the Xiangxi area (South China) and presents a detailed analysis of the sedimentary structures of marine red beds, building on previous research on OMRBs in South China. Based on genetic features, we divide the most debated “nodule-like” and “cracked” structures—previously identified by earlier researchers—into ten subtypes. Three key genetic end-members are identified among these subtypes: breccia, patch, and argillaceous band. Detailed studies using microslab analysis, scanning electron microscopy, geochemistry, and paleontology were carried out on these three end-members. The results confirm that the Ordovician marine red beds were mainly deposited in a shallow marine environment, with the red coloration primarily derived from continental sources. As the sea level rose, the color of the red beds lightened, and the dominant sedimentary structures shifted from breccia end-members to argillaceous band end-members. Additionally, this study identified a vertically penetrating argillaceous band controlled by syndepositional compressive stress, which may be linked to NW-directed compression from the Kwangsian Orogeny. Evidence from tectonic styles, biofacies migration, and chronostratigraphy supports this hypothesis. Full article

The fragile karst ecosystem in Southwest China faces severe water scarcity. Since 2000, large-scale ecological restoration programs (e.g., the “Grain for Green” Program) have substantially increased vegetation coverage. Concurrently, climate change has manifested as a distinct warming trend and heightened drought risk in recent decades. Therefore, understanding the synergistic and competing effects of climate change and vegetation restoration on regional evapotranspiration (ET) is critical for projecting water budgets and ensuring the sustainability of ecosystems and water resources within this vital ecological barrier region. This study employs a dual-scenario PT-JPL model (simulating natural vegetation dynamics versus constant coverage) integrated with Sen + MK trend analysis to quantify the spatiotemporal patterns of ET and its components—canopy transpiration (ETc), interception evaporation (ETi), and soil evaporation (ETs)—in Southwest China’s karst region (2000–2018). Furthermore, multiple regression analysis and SEM were utilized to investigate the driving mechanisms of vegetation and climatic factors (temperature, precipitation, radiation, and relative humidity) on changes in ET and its components. The key results demonstrate the following: (1) Vegetation restoration exerted a net positive effect on total ET (+0.44 mm/a) through enhanced ETi (+0.22 mm/a) and ETs (+0.37 mm/a), despite reducing ETc (−0.08 mm/a), revealing trade-offs in water allocation. (2) Radiation dominated ET variability (66.45% of the area exhibiting >50% contribution), while temperature exhibited the most extensive spatial dominance (44.02% of the region), and relative humidity exhibited drought-mediated dual effects (promoting ETi while suppressing ETc). (3) Precipitation exhibited minimal direct influence. Vegetation restoration and climate change collectively drive ET dynamics, with ETc declines indicating potential water stress. These findings elucidate the synergistic regulation of vegetation restoration and climate change on karst ecohydrology, providing critical insights for water resource management in fragile ecosystems globally. Full article

Understory vegetation, particularly dwarf bamboo, plays a crucial role in regulating forest nutrient cycles by intercepting litter and altering decomposition processes, yet its overall impacts remain understudied and insufficiently quantified. This study employs a combination of field surveys and decomposition bag experiments to investigate how understory dwarf bamboo (Fargesia decurvata) alters the spatial–temporal patterns of leaf litter production and decomposition. We found that the dwarf bamboo intercepted more than 25% of canopy litterfall, altering its spatial distribution and reducing decomposition efficiency in the bamboo crown (BC). Leaf trait-decomposition relationships differed strongly across habitats, being positive for saturated fresh weight (SFW), leaf thickness (LFT), and leaf area (LA) and dry weight (DW) in bamboo habitats but weaker in the bamboo-free habitat (NB). Potassium release was significantly higher in the BC treatment, whereas carbon release showed the opposite trend. In contrast, nitrogen and phosphorus exhibited net enrichment across all treatments, with phosphorus enrichment being slower in BC than in bamboo-covered ground surface (BG) and NB. Our results demonstrate that the understory dwarf bamboo reshapes the spatial distribution of litter and nutrient release dynamics during decomposition, resulting in element-specific nutrient release patterns. These findings provide mechanistic insights into how understory dwarf bamboo mediates nutrient cycling dynamics in forest communities. Full article

Significant uncertainties persist across different Leaf Area Index (LAI) products due to multiple factors; therefore, the accuracy assessment of the global LAI products is an indispensable step before their application. In this study, comprehensive validation of multi-scale LAI products including Sentinel-2, Landsat-8/9, and MCD15A3H was implemented utilizing fine-resolution LAI maps which were based on UAV images and field-measured LAI data. The validation results demonstrated a consistent, systematic underestimation across all the LAI products within the study area, the RMSE of these products ranged from 0.56 to 1.63, and the coarse-resolution MCD15A3H LAI product demonstrated highest accuracy (RMSE = 0.56, R² = 0.69). The Sentinel-2 products exhibited intermediate accuracy among all those products (RMSE: 1.16–1.36). The Landsat-8/9 LAI product showed markedly lower accuracy relative to Sentinel-2; its RMSE (1.63) exceeded that of Sentinel-2 10 m LAI and 20 m LAI by 40.52% and 21.64%, respectively. In addition, all these LAI products showed consistent seasonal variation patterns with the reference LAI maps. Moreover, Sentinel-2 10 m LAI products showed serious underestimation for all vegetation types, with forests providing the highest RMSE = 0.89. This study serves as a valuable reference for the application of multi-scale LAI products in heterogeneous terrain and provides directions for the improvement of fine-resolution LAI retrieval algorithms. Full article

Ecological stoichiometry, as a discipline investigating plant elemental coupling mechanisms, has become a research focus across various ecosystems. However, few studies have examined plant stoichiometric characteristics in the water–land ecotone of plateau karst lake wetlands. It remains unclear whether foliar nutrient contents and stoichiometric ratios in this transitional zone vary with flooding intensity. This study established three sampling gradients (near-water area, middle area, and far-water area) within the water–land ecotone of Caohai Lake wetland in Guizhou Plateau, measuring nutrient concentrations along with their stoichiometric ratios in leaves of three dominant plant species. The results revealed significant interspecific differences in leaf nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) concentrations and N:P ratios among the three dominant species, while significant spatial variations were observed in N concentration and the C:N ratio across sampling locations. Correlation analysis demonstrated significant positive relationships among leaf N, P, and K concentrations, all showing negative correlations with C concentration. Phragmites australis exhibited significantly lower C:N and N:P ratios compared to Scirpus validus and Juncus effusus, suggesting its growth advantage through rapid nutrient acquisition. This species may serve as an efficient phytoremediator for N and P absorption from both soil and water. These findings provide valuable references for vegetation selection in constructed wetlands. Full article

Subterranean ecosystems represent some of the most unique and fragile habitats on Earth, yet they remain poorly understood and highly vulnerable to human-induced disturbances. Despite their ecological significance, these systems are rarely integrated into conservation planning, and surface-level protected areas alone are insufficient to safeguard their biodiversity. In southeastern Brazil, a karst landscape spanning approximately 1200 km², recognized as the region with the highest cave density in South America (approximately 2600 caves), is under increasing pressure from urban expansion, agriculture, and mining, all of which threaten the ecological integrity of subterranean habitats. This study sought to identify caves of high conservation priority by integrating species richness of non-troglobitic invertebrates, occurrence of troglobitic species, presence of endemic troglobitic taxa, and the degree of anthropogenic impacts, using spatial algebra and polygon-based mapping approaches. Agriculture and exotic forestry plantations (54%) and mining operations (15%) were identified as the most prevalent disturbances. A total of 32 troglobitic species were recorded, occurring in 63% of the 105 surveyed caves. Notably, seven caves alone harbor 25% of the region’s known cave invertebrate diversity and encompass 50% of its cave-restricted species. The findings highlight the global significance of this spot of subterranean biodiversity and reinforce the urgent need for targeted conservation measures. Without immediate action to mitigate unsustainable land use and resource exploitation, the persistence of these highly specialized communities is at imminent risk. Full article

Seasonally dry tropical forests (SDTFs) are shaped by strong climatic and edaphic constraints, including pronounced rainfall seasonality, extended dry periods, and shallow karst soils with limited water retention. Understanding how tree species respond to these pressures is crucial for predicting ecosystem resilience under climate change. In the Yucatán Peninsula, we characterized sixteen tree species along a spatial and seasonal precipitation gradient, quantifying wood density, predawn and midday water potential, saturated and relative water content, and specific leaf area. Across sites, diameter classes, and seasons, we measured ≈4 individuals per species (n = 319), ensuring replication despite natural heterogeneity. Using a principal component analysis (PCA) based on individual-level data collected during the dry season, we identified five functional groups spanning a continuum from conservative hard-wood species, with high hydraulic safety and access to deep water sources, to acquisitive light-wood species that rely on stem water storage and drought avoidance. Intermediate-density species diverged into subgroups that employed contrasting strategies such as anisohydric tolerance, high leaf area efficiency, or strict stomatal regulation to maintain performance during the dry season. Functional traits were strongly associated with precipitation regimes, with wood density emerging as a key predictor of water storage capacity and specific leaf area responding plastically to spatial and seasonal variability. These findings refine functional group classifications in heterogeneous karst landscapes and highlight the value of trait-based approaches for predicting drought resilience and informing restoration strategies under climate change. Full article

Nitrogen (N) is a key nutrient for sustaining ecosystem productivity and agricultural sustainability; however, achieving high-precision monitoring in wetlands with highly heterogeneous surface types remains challenging. This study focuses on Caohai, a representative karst plateau wetland in China, and integrates Sentinel-2 multispectral and Zhuhai-1 hyperspectral remote sensing data to develop a soil nitrogen inversion model based on spectral indices, texture features, and their integrated combinations. A comparison of four machine learning models (RF, SVM, PLSR, and BPNN) demonstrates that the SVM model, incorporating Zhuhai-1 hyperspectral data with combined spectral and texture features, yields the highest inversion accuracy. Incorporating land-use type as an auxiliary variable further enhanced the stability and generalization capability of the model. The study reveals the spatial enrichment of soil nitrogen content along the wetland margins of Caohai, where remote sensing inversion results show significantly higher nitrogen levels compared to surrounding areas, highlighting the distinctive role of wetland ecosystems in nutrient accumulation. Using Caohai Wetland on the Chinese karst plateau as a case study, this research validates the applicability of integrating spectral and texture features in complex wetland environments and provides a valuable reference for soil nutrient monitoring in similar ecosystems. Full article

The escalating demand for rural domestic wastewater treatment necessitates environmentally sustainable and cost-effective technologies. This study investigated the enhancement of a micro/nano aeration biofilter (MABF) through electric field coupling (E-MABF), evaluating pollutant removal efficacy and associated bacterial community dynamics. The results showed that the electric field significantly enhanced removal efficiency with respect to total phosphorus (TP), phosphate (PO₄³⁻-P), ammonium nitrogen (NH₄⁺-N), and chemical oxygen demand (COD) (p < 0.05). The TP, PO₄³⁻-P, NH₄⁺-N, and COD removal efficiencies for E-MABF reached 89.79%, 88.69%, 57.29%, and 57.96%, significantly exceeding those of MABF (26.50%,33.41%, 35.49%, and 45.75%). Electric field application markedly altered bacterial diversity and community composition. Core phyla, including Pseudomonadota, Chloroflexota, and Cyanobacteriota, exhibited significant positive correlations with pollutant removal efficiencies, indicating electric field facilitation of functional bacterial enrichment. KEGG pathway analysis suggested that electric field stimulation potentially enhanced metabolic functions, particularly in terpenoid and polyketide metabolism, and xenobiotics biodegradation. The Mantel’s test and structural equation model identified dominant bacterial composition as the primary factor influencing pollutant removal, followed by microenvironmental indicators and bacterial diversity. These findings elucidate the mechanisms underpinning the electric field augmentation of micro/nano aeration biofilter performance and provide a foundation for future research. Full article

Karst landscapes, characterized by ecological constraints such as thin soil layers, severe rock desertification, and fragile habitats, require a clear understanding of the mechanisms regulating carbon storage and the impacts of ecological restoration measures. However, current research lacks detailed insights into the specific effects of ecological restoration measures. This study integrates multi-source remote sensing data and adjusts InVEST model parameters to systematically reveal the spatiotemporal evolution of carbon storage and its driving mechanisms in typical karst plateau regions of southwest China under ecological restoration measures. The results indicate: (1) From 2000 to 2020, the carbon stock in the study area increased by 6.09% overall. However, from 2020 to 2025, due to the rapid conversion of forest land into building land and grassland, the carbon stock decreased sharply by 7.69%. (2) Severe rock desertification constrains carbon stock, and afforestation provides significantly higher long-term carbon sink benefits. (3) The spatial heterogeneity of carbon storage is primarily influenced by the combined effects of natural factors (rock desertification, elevation, NDVI) and human factors (POP). Based on the research findings, it is recommended that measures to promote close forests be prioritized in karst regions to protect and restore forest ecosystems. At the same time, local habitat improvement and the establishment of ecological compensation mechanisms should be implemented, and the expansion of building land should be strictly controlled to enhance the stability of ecosystems and their carbon sink functions. These research findings provide a solid scientific basis for enhancing and precisely regulating the carbon sink capacity of fragile karst ecosystems, and are of great significance for formulating scientifically sound and reasonable ecological protection policies. Full article

This study investigated how moss species identity and coverage density influence soil organic carbon (OC), total nitrogen (TN), total phosphorus (TP), cation exchange capacity (CEC), and stoichiometric ratios (C/N, C/P, N/P ratios) across soil depths in karst ecosystems of northern Guangxi, China. Spectral responses to moss cover were concurrently analyzed. Soil properties under moss crusts and bare controls were quantified through chemical assays. Coverage effects were compared via bar charts (sparse) and point-line plots (dense) with fitted curves and 95% confidence intervals. Spectral reflectance (250–2500 nm) was measured to characterize surface optical properties. Statistical correlations between variables were established. Research has shown the following: (1) Moss coverage significantly enhanced OC, TN, and CEC versus bare soil (B. dichotomum showed the strongest improvement: dense crust increased OC/TN/TP by 6.37/1.73/0.45 g kg⁻¹ and doubled CEC). (2) All nutrients and CEC decreased with depth, most sharply for G. humillimum OC (22.38% reduction at 3–6 cm) and P. yokohamae CEC (9.97% reduction). (3) Stoichiometric ratios exhibited species-specific responses: B. dichotomum had the smallest inter-layer differences in C/N/P ratios, while G. humillimum increased C/N by 34.33% at 3–6 cm. Sparse coverage elevated N/P ratios up to 59.38% (G. humillimum, 0–3 cm). (4) Spectral analysis revealed the following: Sparse coverage boosted reflectance via edge scattering and soil background contributions. Dense coverage suppressed reflectance due to water absorption (1450/1900 nm) and limited scattering. Bare soil exhibited persistently low reflectance from hematite absorption (500–700 nm). Moss biocrusts—particularly dense B. dichotomum—optimize topsoil fertility and CEC in karst soils, though effects diminish sharply below 3 cm. Spectral signatures provide non-invasive indicators of coverage density and erosion resistance. These insights highlight the crucial role of species-specific moss selection in promoting sustainable restoration practices and long-term ecological recovery in rocky desertification regions. Full article