Search Results (210)

Severe heavy metal contamination affects the karst landscapes of Guangxi Zhuang Autonomous Region, China, which are highly polluted and complex. However, integrated assessments of heavy metal sources, distribution, ecological risks, and speciation in karst agricultural soils remain limited. Additionally, there is a gap regarding the interactions between cadmium (Cd), zinc (Zn), and selenium (Se) in natural rice fields. This study employed the pollution load index (PLI), ecological risk index (RI), and Positive Matrix Factorization (PMF) models to evaluate the sources and characteristics of heavy metal contamination in farmland soils. The results showed significant pollution in agricultural soils of Guangxi karst due to Cd, chromium (Cr), copper (Cu), and nickel (Ni). Among these, Cd poses the highest ecological risk. Heavy metal accumulation in the surface soil far exceeds that in deeper layers, and the main sources of Cd were contributed from soil parent material and agricultural activities. Speciation analysis revealed the high bioavailability of Cd, while Zn and Se existed in more stable forms. Despite elevated soil Cd levels, rice grains remained within the safety limits. Using transmission electron microscopy (TEM), Cd was primarily detected in the cell walls of rice stems and husks, which was attributed to Zn’s competitive uptake, reducing Cd absorption and Se forming complexes with Cd to enhance its fixation. Statistical correlations revealed positive associations between Cd in soil and rice. Cd also demonstrated a positive correlation with Se, but a negative correlation with Zn, suggesting a synergistic mechanism between Zn and Se that acts to mitigate the absorption of Cd. This study provides practical guidance for managing farmland soil heavy metal contamination and protecting agricultural soil resources in the karst areas. Full article

Caves are fragile subterranean ecosystems whose conservation depends on accurate microclimatic zonation. Traditional fixed-distance sampling often overlooks non-linear thermodynamic transitions at geomorphological thresholds, hindering sustainable management of subterranean biodiversity. This study introduces the Adaptive Morpho-Statistical Protocol (AMSP), a novel, resource-efficient framework for functional cave profiling. The methodology integrates high-precision atmospheric monitoring with adaptive spatial positioning to identify three distinct sectors (S1–S3) based on thermodynamic homeostasis rather than linear distance. Validated across five diverse cave archetypes in the Vratsa Karst Region (Bulgaria), the AMSP demonstrated exceptional predictive power using second-order polynomial regressions (R² > 0.92). A key finding is the definition of a standardized reference threshold for deep-reach stability (Sector 3), consistently characterized by a Dew Point Standard Deviation (SD_DP < 0.40) and stabilized thermal coupling (∆T → 0). Furthermore, the adaptive strategy successfully captured extreme hygrometric jumps at morphological bottlenecks—critical inflection points for protecting sensitive biota. By providing a cost-effective and replicable standard, the AMSP bridges the gap between spatial resolution and logistical feasibility in challenging environments. These results confirm that morphological isolation is the primary driver of microclimatic inertia, offering a robust tool for sustainable subterranean heritage management and high-precision ecological monitoring in protected karst landscapes. Full article

Secondary succession in tropical forests is traditionally described as a linear process driven by time since disturbance. However, growing evidence suggests that recovery pathways depend strongly on historical and environmental contexts. We evaluated how disturbance legacies and edaphic constraints interact to shape successional trajectories in a tropical karst landscape of the Maya Forest, Mexico. We sampled 100 plots along a chronosequence, quantifying vegetation structure, floristic diversity, biomass (NDVI), disturbance legacies, and soil properties. Using unsupervised clustering (K-means) and multivariate ordination, we identified four contrasting ecological typologies that represent distinct successional states rather than transient stages. Our results show a pronounced dichotomy in vegetation dynamics following the abandonment of land-use practices: while some sites are experiencing diverse development due to positive forest legacies (Typology B), others remain stalled (Typology C), dominated by lianas, where biotic barriers inhibit tree regeneration despite decades of abandonment. Additionally, we documented an asynchronous recovery between floristic recovery and vertical development; in sites with edaphic constraints, forests reach high diversity and biomass but exhibit stunted growth (Typology D). This suggests that severe abiotic constraints—specifically high rockiness and shallow soils—limit the dominance of highly competitive species, thereby acting as a filter that maintains high levels of diversity despite structural limitations. Edaphic analysis confirmed that chemical fertility and physical constraints (rockiness and shallow depth) act as orthogonal filters. This explains the persistence of structurally constrained yet functionally mature forests as stable, edaphically determined outcomes. Overall, secondary succession in tropical karst is nonlinear and path-dependent, governed by a hierarchical filtering model where historical land use dictates community identity and physical substrate limits structural architecture. These findings highlight the need for trajectory-specific management and the abandonment of uniform expectations of forest recovery in karst landscapes. Full article

The natural regeneration of planted forests in karst landscapes is severely constrained by extreme substrate heterogeneity and fragile edaphic conditions. However, the relative importance and interaction pathways of environmental versus stand structural drivers remain poorly quantified. In this study, 54 plots (10 m × 10 m) were surveyed across Cupressus funebris plantations in the karst landscape of the Lijiang River Basin, southern China. To identify the key factors and causal pathways governing regeneration, redundancy analysis (RDA), variation partitioning, partial least squares structural equation modeling (PLS-SEM), and threshold analyses were applied. Regeneration exhibited pronounced spatial heterogeneity, with 42.6% of plots showing complete recruitment failure and a characteristic inverted J-shaped size class distribution. The analysis identified soil rock fragment content (as a negative constraint) and canopy gap area (as a positive driver) as the two dominant predictors. PLS-SEM revealed that environmental factors influence regeneration primarily through an indirect pathway mediated by stand structure ($R^2=0.683$) rather than through direct effects. Threshold analyses identified quantitative benchmarks for key drivers, including a gap area breakpoint of approximately 10 ${\mathrm{m}}^2$ and a presence–absence effect of soil rock fragments. These findings contribute to a more sophisticated mechanistic understanding of forest regeneration in karst ecosystems and provide an empirical foundation for silvicultural management that aims to encourage natural regeneration and ecological restoration of degraded karst plantations. Full article

The Lijiang River is a typical karst landscape river and an important drinking water source for Guilin City. To evaluate its contamination of metals and metalloids, water, surface sediment and four sediment profiles were systematically collected from the Guilin urban segment in April 2023, and the distribution, mobility and potential sources of nine elements (Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb) were analyzed. Results show that metal and metalloid concentrations in the river water are low and water quality is good, whereas sediment concentrations of Cd, Zn, As and Pb are markedly higher than the background values. Compared with other elements, Ni, Cu, As and Cd are more readily mobilized in the aqueous phase and exhibit higher bioavailability. Vertical variation coefficients of all elements in the sediment profiles are mostly below 15%, indicating a relatively stable depositional environment. Correlation analysis and positive matrix factorization identify four main sources: industrial discharge (12.5%), mixed agricultural–geogenic origin (34.3%), traffic emissions (11.9%) and geological background (41.3%). Overall, metal and metalloid contamination in the urban Lijiang River is controllable, but accumulation of Cd and other elements in sediments requires continued attention. Full article

Understanding nitrogen distribution in spring-fed karst rivers is important for interpreting ecosystem responses in populated Mediterranean landscapes. Nitrogen, in its various forms, is a key physicochemical quality element influencing biological communities and ecological quality of freshwater ecosystems. Elevated nitrogen availability may trigger eutrophication and other processes associated with biodiversity loss, posing risks to both aquatic ecosystem integrity and drinking water quality. However, translating nitrogen measurements into effective monitoring and management strategies remains challenging. Monitoring programs are often resource-intensive and require site-specific adaptation, particularly in heterogeneous systems such as karst catchments. General guideline values may not fully capture local hydrological variability, groundwater–surface water interactions, or combined stressors, including nutrient mixtures and salinity intrusion. These factors introduce uncertainty and complicate the interpretation of nitrogen dynamics. This pilot-scale exploratory study assessed total nitrogen (TN) across four environmental matrices—water and sediments, as well as tissue TN in aquatic bryophytes, and in benthic macroinvertebrates—at four spring-fed sites within the Koiliaris River Basin (Crete, Greece). The Koiliaris Critical Zone Observatory (CZO) is a representative karst watershed with highly permeable carbonate geology and long-term human pressures. TN concentrations were low in water (0.9–1.4 mg/L) and sediments (0.2–1.1 g/kg) but substantially higher in biotic compartments, particularly in macroinvertebrates (29.8–47.1 g/kg), while moss tissue TN ranged between 16.9 and 20.4 g/kg. Spatial variability among sites was observed, with consistently higher TN values at the coastal spring influenced by seawater intrusion. Although the limited sample size precluded formal statistical inference, exploratory analyses indicated positive associations between water TN and tissue TN in mosses and macroinvertebrates. These preliminary findings suggest that dissolved nitrogen may represent an important pathway of nitrogen availability to aquatic biota in this karst system. The study provides an exploratory framework for integrating abiotic and biotic nitrogen measurements and may inform the design of future, larger-scale investigations in Mediterranean spring-fed rivers. Full article

While dissolution dominates the genesis of karst systems, physical erosion processes also play a significant role in their development. Lowering of the water table exposes caves to vadose conditions, reducing roof-supporting buoyancy and potentially leading to catastrophic conduit ceiling failure and cave collapse. The locations and extents of collapse areas are not always identifiable at the landscape surface. High-resolution topographic data derived from LiDAR were used to develop a digital elevation model (DEM) that isolates areas that may have sustained episodes of cave collapse and improves our understanding of past hydrogeological and geomorphological conditions of the system. Cave level delineation from LiDAR data was used to assign elevations to cave entrances. Spatial susceptibility to past collapse was evaluated using a weighted multi-criteria analysis that integrated terrain slope, proximity to mapped cave entrances, and distance to surface streams. Areas identified as having a high likelihood of collapse spatially coincide with cave level contacts and known karst windows and terraces, indicating that this replicated methodology is effective as an initial survey tool for identifying collapse-prone areas in karst landscapes. Full article

The 1st International Online Conference on Taxonomy (IOCTX2025) serves as a critical interdisciplinary nexus for addressing the contemporary “taxonomic impediment” through the lens of integrative systematics and computational innovation. By synthesizing research spanning from Paleozoic fossil records to extant microbial biodiversity, the conference illuminates the evolving methodology of species delimitation, moving beyond traditional morphometrics to incorporate multi-locus molecular phylogenetics, bioacoustics, and high-resolution 3D imaging. Key thematic clusters across the program examine the floristic complexity of Karst landscapes, the resolution of cryptic animal species complexes through genomic and proteomic data, and the role of machine learning in automating the identification of both fossil and living taxa. Furthermore, the proceedings underscore a paradigm shift toward “integrative taxonomy,” where the fusion of morphological rigor with eDNA metabarcoding and automated genomic scanning provides a more robust framework for understanding global biodiversity hotspots. Ultimately, IOCTX2025 reaffirms taxonomy as a high-technology discipline essential for conservation biology and evolutionary theory, providing a standardized scientific language to describe the complexities of the tree of life across deep time and modern ecosystems. Full article

Reliable cropland mapping in Karst landscapes is hindered by high topographic heterogeneity and landscape fragmentation. Focusing on the Yunnan–Guizhou Plateau in Southwest China, this study evaluates the accuracy and spatial consistency of seven global land cover products (i.e., GlobeLand30, CLCD, GLC_FCS30, CACD, ESA WorldCover, Esri Land Cover, and FROM-GLC10) against the Third National Land Survey released by China’s Ministry of Natural Resources. Furthermore, we employed Multiscale Geographically Weighted Regression (MGWR) to diagnose key impact factors. The results reveal that the 10 m ESA WorldCover offers superior reliability (OA = 0.81, $R^2$ = 0.84), whereas GLC_FCS30 exhibits the weakest performance among the evaluated datasets (OA = 0.72, $R^2$ = 0.29), highlighting significant uncertainty in this complex terrain. Crucially, MGWR diagnostics (adjusted $R^2=0.923$) uncover how mapping uncertainty is driven by spatially non-stationary environmental constraints. Landscape fragmentation was identified as the primary global driver, exhibiting a consistent negative correlation with accuracy and indicating that the mixed pixel dilemma is the pervasive error source. In contrast, topographic slope operated as a dominant local constraint, with its inhibitory effect intensifying specifically in high-relief gorges where terrain shadowing compromises optical signals. Based on these mechanism diagnostics, we propose a region-adaptive decision framework integrating multi-source fusion and temporal logic to specifically target these topography- and fragmentation-induced uncertainties in future mapping. Full article

The fragile Karst landscapes of southwest China face persistent challenges of soil degradation and rocky desertification. While sustainable land use such as mulberry plantation can support ecological restoration, the dynamics of soil organic carbon (SOC) and its driving mechanisms across contrasting soil types remain poorly understood, limiting the development of targeted pedogenically aware carbon management strategies. A comparative field study was conducted in central Guizhou, China, over an eight-month mulberry growing season (April to November). We monitored SOC, physicochemical properties, GRSP, and enzyme activities in plantations established on two contrasting limestone-derived soils (Calcisols and Chromic Luvisols). This study aimed to clarify the relationships between SOC and key soil parameters within each soil type and to identify their dominant driving factors. Soil type significantly influenced SOC concentration, dynamics, and its regulatory mechanisms. SOC was significantly higher and exhibited greater seasonal variability in Calcisols (31.51–39.71 g·kg⁻¹) than in Chromic Luvisols (22.50–28.51 g·kg⁻¹), with Calcisols maintaining 1.28–1.57 times the SOC concentration of Chromic Luvisols. Regression analysis revealed that SOC was significantly positively correlated with TN, AN, AK, and GRSP, but significantly negatively correlated with AP. Random forest modeling further identified distinct key correlated factors in each soil type as follows: TN, T-GRSP, and Urease were primary in Calcisols, whereas TN, T-GRSP, and pH dominated in Chromic Luvisols. Partial least squares path modeling confirmed that soil type does not directly associate with SOC but exerts an indirect effect by modulating core biochemical mediators specifically (Alkaline protease, T-GRSP, and TN); The model also indicated that pH and TN exert direct positive effects on SOC accumulation. In Karst mulberry systems, pedogenically distinct soils (Calcisols vs. Chromic Luvisols) shape SOC storage, stability, and regulatory mechanisms through divergent biogeochemical pathways. SOC management should therefore be soil-type-specific, prioritizing nitrogen synergy in Calcisols and pH-mediated stabilization in Chromic Luvisols, rather than applying uniform strategies. This study thereby establishes a mechanistic framework for understanding and managing SOC in heterogeneous Karst landscapes, providing a critical foundation for developing targeted, soil-specific carbon sequestration practices in ecologically vulnerable regions. Full article

Current mainstream remote sensing approaches to forest age estimation frequently neglect interspecific differences in functional traits, which may limit the accurate representation of species-specific tree growth strategies. This study develops and validates a technical framework that incorporates multi-source remote sensing and tree species functional trait heterogeneity to systematically improve the accuracy of plantation age mapping. We constructed a processing chain—“multi-source feature fusion–species identification–heterogeneity modeling”—for a typical karst plantation landscape in southeastern Yunnan. Using the Google Earth Engine (GEE) platform, we integrated Sentinel-1/2 and Landsat time-series data, implemented a Gradient Boosting Decision Tree (GBDT) algorithm for species classification, and built age estimation models that incorporate species identity as a proxy for the growth strategy heterogeneity delineated by the Plant Economic Spectrum (PES) theory. Key results indicate: (1) Species classification reached an overall accuracy of 89.34% under spatial block cross-validation, establishing a reliable basis for subsequent modeling. (2) The operational model incorporating species information achieved an R² (coefficient of determination) of 0.84 (RMSE (Root Mean Square Error) = 6.52 years) on the test set, demonstrating a substantial improvement over the baseline model that ignored species heterogeneity (R² = 0.62). This demonstrates that species identity serves as an effective proxy for capturing the growth strategy heterogeneity described by the Plant Economic Spectrum (PES) theory, which is both distinguishable and valuable for modeling within the remote sensing feature space. (3) Error propagation analysis demonstrated strong robustness to classification uncertainties (γ = 0.23). (4) Plantation structure in the region was predominantly young-aged, with forests aged 0–20 years covering over 70% of the area. Despite inherent uncertainties in ground-reference age data, the integrated framework exhibited clear relative superiority, improving R² from 0.62 to 0.84. Both error propagation analysis (γ = 0.23) and Monte Carlo simulations affirmed the robustness of the tandem workflow and the stability of the findings, providing a reliable methodology for improved-accuracy plantation carbon sink quantification. Full article

Aspergillus fumigatus is the primary pathogen causing aspergillosis. Recent molecular population genetic studies have demonstrated that A. fumigatus exhibits high local genetic diversity, with evidence for limited differentiation among geographic populations. However, research on the impacts of geomorphological factors on shaping the population genetic diversity patterns of this species remains scarce. In this study, large-scale sampling and in-depth population genetic analysis were performed on soil-derived A. fumigatus from Guizhou Province, a representative karst landscape in southern China. This area is dominated by plateaus and mountains (accounting for 92.5% of the total area) and represents a classic example of conical karst landscapes. A total of 206 A. fumigatus strains were isolated from 9 sampling sites across Guizhou. Genetic diversity, genetic differentiation, and population structure of these strains were analyzed based on short tandem repeats (STRs) at 9 loci. The results revealed that A. fumigatus in the karst region of Guizhou harbors abundant novel alleles and genotypes, with high genetic diversity. Gene flow among geographical populations was infrequent, and significant genetic differentiation was detected between 30 of the 36 pairs of geographical populations where mountain ranges played a very important role, with the overall regional genetic differentiation reaching PhiPT = 0.061 (p = 0.001). Furthermore, the Guizhou populations showed significant differences from those reported in other regions worldwide. Surprisingly, only one of the 206 (0.49%) A. fumigatus isolates from this region exhibited resistance to the two medical triazoles commonly used for treating aspergillosis, and this resistance frequency was far lower than those reported in previous studies from other regions. We discuss the implications of our results for evolution and environmental antifungal resistance management in this important human fungal pathogen. Full article

Recognizing the evolution of landscape patterns in the Chishui River source region is essential for protecting ecosystems and sustainable growth in the Yangtze River Basin and other similar areas. However, knowledge of landscape pattern evolution within the primary channel zone remains insufficient. To address this gap, the current study used 2000–2020 land-use, geography, and socio-economic data, integrating landscape pattern indices, land-use transfer matrices, dynamic degree, the GeoDetector model, and the PLUS model. Results revealed that forest and cropland remained the prevailing land-use types throughout 2000–2020, comprising over 85% of the landscape. Grassland had the highest dynamic degree (1.58%), and landscape evolution during the study period was characterized by increased fragmentation, enhanced diversity, and stable dominance of major forms of land use. Anthropogenic influence on different landscape types followed the order: construction land > cropland > grassland > forest > water bodies. Land-use change in this region is a complex process governed by the interrelationships among various factors. Scenario-based predictions demonstrate pronounced variability in various land types. These findings provided a more comprehensive understanding of landscape patterns in karst river source regions, provided evidence-based support for regional planning, and offered guidance for ecological management of similar global river sources. Full article

Under the intensifying water shortages in the vegetation season, early identification of Ips typographus L. damage is crucial for preventing wide outbreaks, which undermine the economic potential of commercial stands of Norway spruce (Picea abies Karst.) across Europe. For this purpose, remote sensing based on satellite images is considered one of the most efficient methods, particularly in homogenous and wide forested landscapes. However, under highly heterogeneous seminatural managed forest landscapes in lowland Central and Northern Europe, as illustrated by the eastern Baltic region and Latvia in particular, the efficiency of such an approach can lack the desired accuracy. Hence, the identification of smaller damage patches by I. typographus, which can act as a source of wider outbreaks, can be overlooked, and situational awareness can be further aggravated by infrastructure artefacts. In this study, the accuracy of satellite imaging for the identification of I. typographus damage was evaluated, focusing on the occurrence of false positives and particularly false negatives obtained from the comparison with UAV imaging. Across the studied landscapes, correct or partially correct identification of damage patches larger than 30 m² occurred in 73% of cases. Still, the satellite image analysis of the highly heterogeneous landscape resulted in quite a common occurrence of false negatives (up to one-third of cases), which were related to stand and patch properties. The high rate of false negatives, however, is crucial for the prevention of outbreaks, as the sources of outbreaks can be underestimated, burdening prompt and hence effective implication of countermeasures. Accordingly, elaborating an analysis of satellite images by incorporating stand inventory data could improve the efficiency of early detection systems, especially when coupled with UAV reconnaissance of heterogeneous landscapes, as in the eastern Baltic region. Full article

Against the backdrop of rapid urbanization and land development, the degradation of regional ecosystem services and the intensification of ecological risks have become prominent challenges. This study takes the Pinglu Canal Economic Belt—a region characterized by the triple pressures of “large-scale engineering disturbance, karst ecological vulnerability, and port economic agglomeration”—as a case study. Based on remote sensing image data from 2000 to 2020, a landscape ecological risk index was constructed, and regional landscape ecological risk levels were assessed using ArcGIS spatial analysis tools. On this basis, ecological sources were identified by combining the InVEST model with morphological spatial pattern analysis (MSPA),and an ecological resistance surface was constructed by integrating factors such as land use type, elevation, slope, distance to roads, distance to water bodies, and NDVI. Furthermore, the circuit theory method was applied to identify ecological corridors, ecological pinch points, and barrier points, ultimately constructing the ecological security pattern of the Pinglu Canal Economic Belt. The main findings are as follows: (1) Ecological risks were primarily at low to medium levels, with high-risk areas concentrated in the southern coastal region. Over the past two decades, an overall optimization trend was observed, shifting from high risk to lower risk levels. (2) A total of 15 ecological sources (total area 1313.71 km²), 31 ecological corridors (total length 1632.42 km), 39 ecological pinch points, and 15 ecological barrier points were identified, clarifying the key spatial components of the ecological network. (3) Based on spatial analysis results, a zoning governance plan encompassing “ecological protected areas, improvement areas, restoration areas, and critical areas” along with targeted strategies was proposed, providing a scientific basis for ecological risk management and pattern optimization in the Pinglu Canal Economic Belt. Full article