Search Results (1,106)

As a novel approach to address the lack of systematic studies on spatial Gross Ecosystem Product (GEP) accounting and Ecological Security Pattern construction, this study integrates GEP thresholds with Morphological Spatial Pattern Analysis (MSPA) to identify ecological sources. A resistance surface is constructed using five representative influencing factors, and the Minimum Cumulative Resistance (MCR) model is applied to extract ecological corridors, thereby establishing the Ecological Security Pattern for the Yellow River-Fronting Region of Henan in 2020. The results indicate the following: (1) GEP in the study area exhibits a spatial distribution of “high in the northwest, low in the southeast,” with regulating services accounting for more than 90% of the GEP. (2) A total of 11 ecological sources, 13 ecological corridors, and 7 ecological nodes were identified, primarily distributed in mountainous regions. (3) The Ecological Security Pattern exhibits spatial imbalance, with dense corridors in the western mountains and sparse distribution in the eastern plains. These findings provide scientific support for formulating ecological conservation measures and optimizing ecosystem management in the Yellow River Basin. Full article

Wildfires are a major natural hazard causing extensive ecological damage and endangering human survival. Previous studies on wildfires in China have mostly focused on specific regions or individual drivers, with limited systematic assessments at the long-term and national scales. The spatiotemporal patterns of wildfires and their multiple driving mechanisms under China’s diverse climatic regimes remain insufficiently understood. To bridge this gap, we combined MCD64A1 burned area data (2001–2023) with multi-source natural (meteorological, vegetation, and topographic) and anthropogenic factors, using random forest models at both the national and regional scales to examine the spatiotemporal patterns, dominant drivers, and response mechanisms of wildfires in China. The results revealed that: (1) Spatially, wildfires were concentrated in northeastern and southern China, which accounted for 86.20% of the total burned area. Temporally, northern wildfires were primarily a spring-dominated fire regime, with peak activity in March and April, whereas southern wildfires were winter-dominated, peaking in February. (2) At the national scale, elevation was the key topographic factor influencing wildfire occurrence (relative importance = 0.49), with low-elevation and gentle-slope areas being more fire-prone. At the regional scale, the driving factors exhibit spatial differentiation, forming a spatial pattern of topography-dominated and climate-dominated. (3) Partial dependence plot analysis revealed nonlinear and threshold responses. Fire probability increases rapidly when the soil moisture is below 20 mm, while extremely high land surface temperatures in arid regions suppress fire occurrence due to fuel limitations. This study enhances the understanding of spatially heterogeneous wildfire drivers in China and provides a scientific basis for region-specific wildfire prevention and management strategies. Full article

Balancing ecological conservation with agricultural production in protected areas remains a critical challenge, particularly regarding the nexus of food, water, land, and ecosystems (FWLE). Yet, the spatiotemporal trade-offs, synergies, and underlying drivers within the FWLE remain poorly understood. Focusing on the Henan Funiu Mountain National Nature Reserve (HFMNNR), we quantified water yield (WY), habitat quality (HQ), and food production (FP) using the InVEST model and statistical yearbook data. The XGBoost-SHAP framework was applied to dissect the key drivers and mechanisms governing the FWLE system. Results indicate a significant increasing trend in FP (2000–2020), contrasting with the unimodal (increase-then-decline) trajectories of HQ and WY. Pronounced trade-offs were identified between HQ and WY, and between HQ and FP. Topographic and vegetative factors predominated in shaping the spatial patterns of HQ and FP, whereas climatic factors dictated WY distribution. Specifically, HQ declined when NDVI fell below 0.87, population density surpassed 0.01, or slope was gentler than 7°. WY was constrained when precipitation dropped below 947 mm, actual evapotranspiration exceeded 752 mm, or temperature ranged between 12.5–16.2 °C. FP was suppressed under conditions of slopes > 7°, NDVI within 0–0.61 or 0.61–0.86, or DEM > 373 m. These findings underscore the necessity of spatially explicit management strategies grounded in spatial heterogeneity. We advocate for a multi-objective governance framework centered on HQ to harmonize production and ecological functions. Our findings provide critical insights for formulating policies aimed at sustainably managing protected areas facing similar ecological-production conflicts. Full article

With the intensification of human activities and climate variability, balancing ecosystem service (ES) supply and demand is critical for regional sustainable development. Existing studies predominantly focus on linear driving effects and lack integrated quantitative frameworks that link the spatiotemporal dynamics of ES supply–demand relationships (ESSDRs) with their nonlinear driving mechanisms, and few have systematically quantified the critical thresholds of driving factors and their interactive effects. To address these research gaps, this study quantified the supply, demand, and supply–demand ratios of four key ESs (food production [FP], carbon sequestration [CS], water yield [WY], and soil retention [SR]) in the Yellow River Basin of Henan Province (2000–2020) using the InVEST model and multi-source data. An analytical framework integrating the Extreme Gradient Boosting (XGBoost) model and Shapley Additive Explanations (SHAP) was established to identify dominant drivers, reveal nonlinear response patterns, and quantify critical thresholds. The results showed that FP and CS supply increased continuously, while WY and SR supply slightly declined; CS and WY demand grew faster than supply, leading to expanding deficits, whereas FP and SR maintained relative balance. Spatially, FP/CS surpluses concentrated in eastern plains and southwestern forests, WY deficits occurred in the northwest, and SR balance prevailed in most regions. Dominant drivers differed by ES type—arable land proportion (FP), population density (CS), precipitation (WY), and slope (SR)—all exhibiting distinct threshold effects (e.g., arable land proportion >0.6, slope >3°). These findings provide novel insights into ESSDR spatial heterogeneity and threshold-based regulation, offering a scientific basis for differentiated ecological management and sustainable spatial planning in the Yellow River Basin and similar ecologically vulnerable regions. Full article

Identifying the specific sources of heavy metal accumulation in intensive agricultural landscapes is essential for ensuring soil sustainability and food security. In this study, we independently carried out a high-density regional geochemical survey and high-resolution field sampling in the Yangtze–Huaihe Watershed, Eastern China, and used the original sample dataset to distinguish between geogenic backgrounds and anthropogenic enrichments. By employing the APCS-MLR model, four distinct pollution sources were quantitatively identified: natural pedogenesis, agricultural activities, traffic emissions, and industrial inputs. Results demonstrated that while most heavy metal concentrations remained below national safety thresholds, Cd and Hg exhibited significant topsoil enrichment, signaling potential ecological risks. Source apportionment revealed that natural sources primarily controlled As, Cr, Ni, and Pb, with the contribution ranging from 41% to 70%. In contrast, traffic emissions (e.g., tire wear and fuel combustion) emerged as the dominant source for Cd (68%), Zn (55%), and Cu (34%), while industrial activities accounted for a substantial 89% of Hg accumulation via atmospheric deposition. Notably, despite the region’s intensive cultivation, agricultural practices played a surprisingly minor role in heavy metal accumulation. These findings highlight that the accumulations from traffic and industry now account for approximately 50% of the total heavy metal load in the region. Our results underscore the critical importance of high-resolution spatial data for precise source identification and suggest that implementing vegetative buffer zones and stricter industrial emission controls are imperative to mitigate further soil degradation in similar agricultural watersheds. Full article

Wildfires at the wildland–urban interface (WUI) have increased in frequency and severity under global warming and intensified human activities. As a representative high-altitude mountainous region in southwestern China, Yunnan features complex topography, steep climatic gradients, and dispersed settlements interwoven with wildlands, making it a fire-prone area where wildfire management is particularly challenging. However, a fine-scale WUI dataset is currently lacking for this region. To address this gap, we refined WUI classification thresholds using a one-factor-at-a-time (OFAT) method and generated the first fine-resolution WUI map of Yunnan. Seasonal wildfire driving factors from 2004 to 2023 were quantified, and machine learning models were applied to produce seasonal susceptibility maps. SHapley Additive exPlanations (SHAP) were employed to interpret the dominant contributing factors. The resulting WUI covers 25,730.67 km², accounting for 6.5% of Yunnan’s land area. Random forest models effectively captured seasonal wildfire susceptibility patterns, with AUC values exceeding 0.83 across all seasons. High susceptibility zones (>0.5) comprised 30.09% of the WUI in spring, 25.74% in winter, 22.61% in autumn, and 13.74% in summer. SHAP analysis revealed that anthropogenic factors consistently drive wildfire occurrence, while climatic conditions in the preceding season influence vegetation status and subsequently affect wildfire likelihood in the current season. By integrating static “where” mapping with dynamic “when” susceptibility analysis, this study establishes a comprehensive “When–Where” framework that supports both long-term WUI planning and short-term seasonal early warning. The integration of fine scale WUI mapping with seasonal susceptibility modeling enhances wildfire risk management in complex high-altitude regions. These findings provide a scientific basis for location-specific, time-sensitive, and full-chain wildfire management in mountainous landscapes and contribute to cross-border ecological security governance in the Indo-China Peninsula. Full article

As urbanization intensifies, improving street thermal comfort has become a critical issue in urban renewal. While existing studies generally assume that increasing the Green View Index (GVI) linearly improves pedestrian thermal comfort, this study identifies a significant “Decoupling Effect” in high-density commercial areas through field measurements and numerical simulations of three typical street types (commercial–service, ecological–recreational, and historical–cultural) in Shenyang. Integrating DeepLab V3 semantic segmentation with ENVI-met version 5.1.1 microclimate simulation, the results demonstrate a robust monotonic negative correlation between GVI and Physiological Equivalent Temperature (PET) in ecological streets (Spearman’s ρ = −0.692, p < 0.001), confirming the consistent cooling benefit of greenery in nature-dominated environments. However, a distinct “Threshold Effect” was identified in commercial streets using Piecewise Linear Regression (PLR). A critical breakpoint was detected at GVI = 22.08%. Below this threshold, visual greenery effectively contributes to cooling (slope = −0.454); yet, once GVI exceeds 22.08%, the cooling efficacy diminishes significantly (slope = −0.109), marking the onset of a “decoupling” phase. Specifically, despite Wenhua Road achieving a GVI of ~24.5% with a complex “three-board, four-belt” structure, its PET peak reaches 46.15 °C, approximately 5.5 °C higher than ecological streets. Mechanism analysis reveals that under peak thermal stress (Traffic Heat ≈ 75 W/m²), the high-intensity anthropogenic heat and hardscape radiation exceed the evaporative cooling threshold of vegetation. This study reveals the non-linear relationship between visual greenery and the physical thermal environment, suggesting that simply pursuing visual green quantity is ineffective in commercial canyon renewal; instead, a threshold-based synergistic optimization of canopy shading and pavement thermal performance is required. These findings provide a quantitative basis for sustainable street landscape planning and urban climate adaptation strategies in high-density cities. Full article

Wetlands are highly productive ecosystems that play a vital role in maintaining ecological balance. This study presents a geospatial assessment of the Harike Wetland, Punjab, using hyperspectral (PRISMA) and multispectral (Landsat series) satellite data to analyze its ecological structure and water dynamics. Six spectral indices—Normalized Difference Vegetation Index (NDVI), Normalized Dif-ference Aquatic Vegetation Index (NDAVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Floating Algal Index (FAI), and Algal Bloom Detection Index (ABDI)—were employed to map terrestrial agricultural cropland (paddy), aquatic vegetation and surface water. Threshold-based classification of index outputs was used to estimate the spatial extent of major land cover types. NDVI and NDAVI effectively captured vegetation patterns, while NDWI and MNDWI improved surface water delineation. Additionally, Z-spectral analysis was applied to extract and compare the reflectance profiles of agricultural cropland, open water, and algae, as well as built-up areas, enhancing spectral contrast and classification accuracy, particularly in spectrally mixed zones. The integration of index-based mapping with detailed spectral profiling demonstrates the advantage of combining multispectral and hyperspectral data for wetland monitoring and provides valuable insights to support wetland conservation and sustainable water management. Full article

Accurate and continuous monitoring of flood dynamics is fundamental to understanding wetland hydrological processes and their ecological implications, yet it remains challenging due to the inherent trade-off between spatial and temporal resolution in remote sensing observations. This study advances flood monitoring methodology by developing and validating a spatiotemporal fusion framework specifically designed for multi-source Synthetic Aperture Radar (SAR) data—an approach that has remained underdeveloped despite its critical importance for all-weather wetland observation. We propose the Fusion SAR Operational Monitoring (FSOM) framework, which integrates three established components—the Flexible Spatiotemporal Data Fusion (FSDAF) model, the Sentinel-1 Dual-Polarized Water Index (SDWI), and automated thresholding classification—into a coherent processing chain that generates consistent high-resolution flood extent time series from multi-sensor SAR data (Sentinel-1 and GF-3). The FSOM was applied to the Chen Lake Wetland from 2020 to 2024, producing a monthly flood map dataset at 5 m spatial resolution. Quantitative validation demonstrated the superiority of the FSOM-derived products. Compared to water classifications using original Sentinel-1 data, the FSOM results achieved a significantly higher overall accuracy (exceeding 90%) and Kappa coefficient (>0.90) than the Sentinel-1 results, which had overall accuracy (exceeding 86%) and Kappa coefficient (>0.75). Critically, the producer’s accuracy for water bodies consistently surpassed 91%, indicating a substantial reduction in omission errors and markedly improved detection of small water bodies. These results confirm the effectiveness of the proposed FSOM framework in mitigating the spatiotemporal resolution trade-off, thereby providing a reliable high-fidelity data foundation to support precise wetland conservation and flood disaster emergency response. The framework thus offers a practical tool for scientists and water resource managers seeking to enhance monitoring capabilities in the world’s most dynamic and ecologically significant wetland ecosystems. Full article

On one hand, the University of Kragujevac, Serbia, needs an ESP course in ecology; on the other hand, the available wordlists do not meet fully meet the needs of the target group of students, i.e., the undergraduate ecology students. This discrepancy served the a main incentive for creating an institution-specific word list of key content words found in a corpus compiled from English-medium textbooks intended for ecology students (here referred to as the Eco-Text corpus). The keyword list was generated in AntConc, with a keyness measure threshold automatically set at p < 0.055 (3.84 with Bonferroni correction). After the list was complete, the NGSL (New General Service List), NAWL (New Academic Word List), and the SWL (Science Word List) Highlighters were used to further systemize the words into four sublists. In addition to presenting some key findings, we also suggest areas for further refinement. Although preliminary, the findings can be useful to practitioners in planning an ESP course in ecology and developing materials. Full article

Amid the accelerating global pursuit of carbon neutrality, the regulatory role of forest ecological security in carbon sink function has emerged as a critical issue in achieving climate goals. This study developed a forest ecological security evaluation index system based on the Driving Force–Pressure–State–Impact–Response–Management (DPSIRM) framework. The forest ecological security comprehensive index for 31 Chinese provinces from 2007 to 2022 was calculated using the entropy weight method, and forest carbon sinks were estimated through the volume expansion method. Spatial econometric models and a mediation effect model were employed to empirically examine the impact of forest ecological security on forest carbon sinks and their underlying mechanisms. The results indicated the following: (1) Improvements in forest ecological security exerted significant positive direct and spatial spillover effects on forest carbon sinks. (2) The enhancing effect of forest ecological security on carbon sinks was significant in western regions, resource-based provinces, and economically underdeveloped areas. (3) Forest area transition and forest age structure transition served as key mediators in the relationship between forest ecological security and carbon sinks. In contrast, the mediating effects of forest species structure transition and forest origin structure transition were not significant, likely constrained by long-term ecological thresholds and socioeconomic inertia. Full article

Urban green spaces (UGS) are critical regulators of carbon sequestration in industrial cities; however, the configuration mechanisms underlying their carbon dynamics remain insufficiently understood. This study investigates how landscape configuration influences carbon sequestration capacity in Lanzhou and Baotou using multi-temporal datasets from 2000, 2011, and 2022. Net primary productivity (NPP) derived from the CASA model was employed to represent carbon sequestration capacity. An integrated XGBoost-SHAP framework was applied to identify dominant configuration metrics, nonlinear responses, and structural thresholds. The XGBoost model showed stable predictive performance across the three periods, with test-set R² values ranging from 0.470 to 0.510 in Lanzhou and from 0.325 to 0.379 in Baotou. The results reveal systematic and persistent differences in configuration-driven controls between the two cities. In Lanzhou, aggregation-related metrics, particularly COHESION, consistently exert the strongest influence across all three periods, indicating that spatial cohesion and connectivity function as primary stabilizing mechanisms in a mountainous, valley-constrained urban system. Carbon sequestration performance increases once sufficient structural integration is achieved, with aggregation thresholds remaining relatively stable, for example AI values of approximately 0.31–0.34 across 2000–2022, reflecting the importance of maintaining ecological continuity under semi-arid climatic stress. In contrast, Baotou is more strongly regulated by fragmentation-related metrics, especially edge density (ED) and division index (DIVISION), suggesting that its relatively open terrain and industrial spatial structure render carbon sequestration more sensitive to patch separation and edge proliferation. Here, fragmentation acts as a dominant structural constraint, limiting vegetation productivity once spatial disintegration intensifies; for example, ED thresholds shifted from approximately −0.23 in 2000 to −0.56 in 2022. Landscape–carbon relationships exhibit pronounced nonlinear and threshold-dependent behavior in both cities. Rather than responding gradually to structural modification, NPP shifts across identifiable transition points that remain broadly stable over time; for instance, Lanzhou’s AI threshold remains within 0.31–0.34, whereas Baotou’s ED threshold changes from −0.23 to −0.56 across 2000–2022, indicating that these thresholds represent intrinsic structural characteristics of the respective urban ecological systems. However, the magnitude and configuration logic of these thresholds differ between Lanzhou and Baotou, confirming the existence of city-specific nonlinear regimes. These findings demonstrate that urban carbon sequestration operates through context-dependent configuration pathways shaped by terrain, climatic constraints, and long-term spatial organization. The study advances understanding of how structural heterogeneity governs carbon dynamics in arid and semi-arid industrial cities and provides a quantitative basis for configuration-sensitive land planning. Full article

Under global climate change, frequent droughts threaten ecosystem functions, but how drought characteristics affect ecosystem resilience remains unclear. Focusing on the Dongjiang River Basin, China, we identified drought events at an 8-day scale from 2000–2024 using multi-source remote sensing and reanalysis data. The water use efficiency-based resilience index (R_de) was calculated, and a random forest model quantified the contributions of 21 potential driving factors. The model explained 68% of R_de variance (R² = 0.68, RMSE = 0.12). Downward shortwave radiation was the primary factor, followed by antecedent water use efficiency and soil moisture anomaly, with drought intensity and air temperature ranking fourth and fifth. All dominant factors exhibited nonlinear threshold effects: R_de decreased significantly after radiation exceeded ~110 W·m⁻²·(8d)⁻¹; R_de declined when standardized soil moisture anomaly fell below −2.0; and R_de increased sharply when drought intensity exceeded 12%. Drought intensity far outweighed duration and severity, establishing it as the key drought attribute. This study reveals the dominant drivers and their thresholds governing ecosystem resilience in the Dongjiang River Basin, providing quantifiable indicators for ecological drought early warning. Full article

Trace metals are persistent stressors in coastal ecosystems, yet most marine algal toxicity assessments still rely on freshwater model species and growth-based endpoints that provide limited mechanistic resolution. Here, we quantified the sensitivity of two ecologically contrasting marine diatoms—the benthic Cylindrotheca closterium and the planktonic Thalassiosira weissflogii—to ten environmentally relevant metals using a dual-endpoint approach that integrates chlorophyll fluorescence (photosystem function) and Nile Red-based lipid-body fluorescence (metabolic reallocation). Fluorescence-based EC₁₀ values revealed distinct species- and metal-specific patterns, with C. closterium consistently responding at lower concentrations and Hg producing the strongest inhibition in both species (EC₁₀ ≈ 0.04–0.06 mg L⁻¹). Lipid-body accumulation detected earlier metabolic disturbance for several metals, particularly Hg, As, Cr(VI), and Cd, and frequently occurred at concentrations where fluorescence remained minimally affected. These sequential thresholds indicate that pigment impairment and metabolic reallocation represent mechanistically distinct stages of the cellular stress response that differ among metals and between diatom guilds. Comparison with published toxicity data shows that the dual-endpoint sensitivities observed here fall within, or slightly above, the upper range of reported microalgal responses, underscoring the pronounced susceptibility of benthic diatoms to redox-active and thiol-reactive metals. The strong agreement between fluorescence-based EC values and traditional growth-derived benchmarks for key metals further supports fluorescence as an operationally efficient endpoint suitable for integration into emerging ISO marine algal bioassays. Overall, this study demonstrates that pairing a rapid functional marker with a mechanistically informative metabolic biomarker enables metal-specific toxicity fingerprinting and provides an ecologically grounded basis for incorporating benthic diatoms into coastal metal risk assessment frameworks. Full article

Active Channel Width (ACW) provides a robust indicator for tracking river corridor dynamics, yet automated extraction from multisensory imagery remains limited by spatial and temporal variability in spectral conditions. We developed and validated a workflow in Google Earth Engine (GEE) to delineate the active channel using multispectral indices derived from annual composite Landsat and Sentinel-2 imagery. The indices include the Modified Normalized Difference Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI). The 34 km study segment of the Lircay River (Chile) served as a demonstration site undergoing substantial geomorphic change over a 20-year period (2003–2023) that spanned a decade-long mega drought (2010–2023) and two major floods (2006, 2023). Multispectral index thresholds were calibrated using manually digitized active channel polygons for a reference year and validated for five different years within the study period to assess their spatial transferability across reaches and temporal stability under varying hydrologic regimes. Sentinel-2 annual composites with the MNDWI-EVI pairing achieved the highest overall accuracy in estimating ACW (mean Kling-Gupta Efficiency = 0.72; Percent Bias = 12.69 across study reaches). Threshold values were tested at the cross-sectional and reach scales. Using cross-section-specific thresholds enhanced the accuracy of ACW estimation, indicating that threshold performance is strongly conditioned by the local characteristics present in the immediate surroundings of each cross section. These results suggest that spectral threshold selection is sensitive to small scale factors that vary across the river corridor, underscoring the need to explicitly consider local geomorphic and ecological conditions when defining thresholds. This reproducible, open-source workflow links automated channel delineation with cross-section-based morphology and explicitly quantifies uncertainty from spatiotemporal spectral variability. It enables high-resolution, repeatable measurements of river corridor change and underscores the need to consider evolving spectral and vegetation conditions when interpreting remotely sensed geomorphic indicators. Full article