Search Results (2,468)

High-altitude animals rely on vertical spatial adaptation to cope with harsh environments, yet the underlying drivers of their seasonal altitudinal distribution remain poorly understood. This study investigated how solar radiation, seasonal high-quality food resources and stable foods shape the altitudinal distribution of the highest-altitude primate Rhinopithecus bieti, to uncover its survival strategies. Through systematic environmental data collection and three-year field tracking of a wild group in the Lasha Mountains, northwest Yunnan, China, we identified consistent seasonal patterns: spring in low-altitude habitats, summer at highest elevations, and intermediate ranges during autumn/winter. Statistical modeling revealed seasonally shifting environmental dependencies. Summer showed no resource limitations, while autumn introduced solar exposure and mature leaves as positive synergistic factors (50% model explanatory power). Winter exhibited peak environmental pressure (80%), with solar and buds becoming critical, though revealing a trade-off between foraging and thermoregulation. Spring demonstrated the strongest environmental coupling (86%), where solar and high-quality food showed significant positive synergy, enabling physical recovery. The species displays remarkable ecological plasticity, with solar being the core cold-season driver. The winter-to-spring transition from resource trade-off to synergy reflects dynamic behavioral adaptations to seasonal climate and nutritional bottlenecks, offering new insights into primate survival strategies in extreme environments. Full article

Hainan Tropical Rainforest National Park is a prime example of a “continental island” tropical rainforest and holds significant value for biodiversity conservation. However, human activities have led to frequent changes in land use and increased habitat fragmentation within the park; a precise analysis of the underlying mechanisms is necessary for ecological restoration. Consequently, drawing upon land-use data from 2000 to 2020, this study coupled multi-dimensional fragmentation metrics (CFI, AFI, and SFI) with the XGBoost-SHAP framework to systematically unravel the spatiotemporal dynamics and underlying driving mechanisms of landscape fragmentation in Hainan Tropical Rainforest National Park. Our findings revealed that the spatial configuration of fragmentation predominantly propagated along river networks and transport corridors, accompanied by a fluctuating ‘decline–rise–decline’ temporal trajectory. Notably, the XGBoost-SHAP attribution highlighted a distinct temporal shift in the dominant drivers: fragmentation was primarily mitigated (negatively driven) by NDVI between 2000 and 2010 but was subsequently exacerbated (positively driven) by GDP growth from 2010 to 2020. The findings of this study provide data support and a scientific basis for ecosystem restoration and land use planning in Hainan Tropical Rainforest National Park. Full article

Resource-based cities in Northwest China face increasing ecological, geotechnical, and socio-economic challenges caused by long-term mining, including subsidence, slope instability, waste rock accumulation, soil erosion, industrial decline, and settlement deterioration. Post-mining land reuse is constrained by geological safety, foundation stability, slope safety, drainage capacity, erosion risk, and waste rock dump stability, yet existing restoration studies often separate engineering remediation from landscape reuse, industrial pathway selection, and long-term governance. Taking a mining area in City A, Gansu Province, as a case study, this paper develops a geotechnical constraint-based ecology–landscape–economy framework for post-mining land reuse and sustainable human settlement improvement. Unlike conventional reclamation approaches that mainly emphasize engineering remediation, vegetation recovery, or single-function land reuse, this study integrates geotechnical constraints, land-unit classification, pathway-specific compatibility assessment, and capital–space coupling into a planning-scale decision-support framework. Post-mining land was classified into five units, and their compatibility with three restoration plus industrial pathways was assessed using five indicators: geological safety, ecological sensitivity, land-use availability, landscape and cultural value, and industrial operation potential. The results indicate that backfilled mining voids and reclaimed platforms are most suitable for modern agriculture, tailings ponds and subsidence waterbodies for cultural tourism and wellness, and waste rock dump platforms and other stable, low-sensitivity open land for new energy development. A capital–space coupling mechanism is further proposed to link restoration, support, and development zones with government funds, corporate capital, social capital, green finance, and industrial income. This framework provides a planning-scale engineering-suitability screening tool for sustainable post-mining land transformation. Full article

Ensuring the sustainability of deep coal mining requires a comprehensive understanding of hydrogeological risks, particularly fault-induced water inrush, which threatens human safety, depletes freshwater resources, and causes irreversible ecological damage. This study addresses the sustainability gap in managing heterogeneous fault fracture zones by conducting coupled loading–seepage experiments on representative limestone, sandstone, coal, and coal–rock mixtures from the Zhaogu No. 2 Mine. Results demonstrate that seepage behavior follows the Forchheimer non-linear regime (E = 0.2–0.95), deviating significantly from Darcy’s law. We quantified that effective stress induces particle crushing and rearrangement, leading to a drastic porosity reduction (up to 97.52% in coal). Crucially, lithology dictates permeability evolution: coal and mixtures exhibit exponential decay, whereas sandstone and limestone follow quadratic functions. The fractal dimension of particles correlates negatively with permeability (R² > 0.95). These findings provide a quantitative framework for predicting water inrush channels, enabling proactive strategies to prevent catastrophic groundwater loss and ensure the long-term viability of mining operations. This research supports SDG 6 (Clean Water) and SDG 12 (Responsible Consumption and Production) by offering scientific guidance for balancing resource extraction with hydrogeological integrity. Full article

Intensified paddy production plays a crucial role in sustaining rice productivity and food security; however, long-term high-frequency puddling, heavy machinery operations under wet soil conditions, simplified cropping systems, and insufficient organic matter inputs have progressively degraded the physical structure of paddy soils. Such structural degradation not only weakens soil water movement, nutrient supply, and aeration but also restricts rice root penetration, alters rhizosphere processes, and disrupts plant–soil feedbacks. Previous studies have largely focused on individual aspects such as soil compaction, amendment-based improvement, water management, or root responses, whereas an integrated understanding of the multi-source drivers, functional consequences, and restoration pathways of soil structural degradation in intensified paddy fields remains limited. Following the overarching theme of soil degradation and regeneration, this review systematically synthesizes the indicator framework, formation mechanisms, degradation typology, ecological consequences, and regulation strategies of paddy soil structural degradation. We further clarify the transition of degraded paddy soils from single physical constraints to the coupled decline of physical, chemical, and biological functions, and compare the agronomic performance, environmental implications, implementation feasibility, and trade-offs of different restoration pathways. Existing evidence indicates that soil structural degradation in paddy fields can impair root-zone pore connectivity, rhizosphere oxygen supply, nutrient acquisition, microbial-mediated carbon and nitrogen cycling, and greenhouse gas regulation, thereby affecting rice growth, yield stability, and the ecological sustainability of paddy systems. Accordingly, the restoration of degraded paddy soils should move beyond short-term loosening or single-factor amendment toward integrated regeneration strategies that maintain soil structural health, reconstruct plough-layer functions, enhance root–soil interactions, and promote the synergistic recovery of pore networks, aggregates, organic carbon, and microbial processes. This review provides a theoretical basis and research reference for the precise restoration of soil structural constraints and the sustainable management of plant–soil systems in intensified paddy fields. Full article

The high-value utilization market for crop straw renders the development of stubble management technology crucial. This study aims to reduce the energy consumption of L-shaped rotary blades during stubble-breaking. Based on a theory analysis of the rotary-cutting operation process, this study involved the burial of the in situ maize root–soil composite in an indoor soil bin, and investigated the effects of rotary speed (275, 330, 385, 440 rpm) and working depth (50, 85, 120 mm) on torque, power, and energy. Field verification yields an overall average relative error of 2.76% across six replicates, verifying that the indoor test method can reliably reproduce field cutting conditions. As the high-speed video images show, a reduction in rotary speed coupled with an augmentation in working depth has the potential to result in residue entanglement and secondary cutting, thereby leading to an escalation in consumption. As the working depth increased, peak torque appeared at a deeper penetration position. The analysis of the computer-aided geometric model section of the root–soil composite indicated that the diameter of the branching root was the primary factor influencing peak torque. At a working depth of 85 mm, the average power savings ranged from 2.26% to 24.8% compared to 50 mm and 120 mm. Despite the increase in average power, peak power, and specific energy requirements at all operational depths with increasing rotary speed, torque reached its minimum at 385 rpm. At 385 rpm, average torque hits its minimum to mitigate component wear, though power and specific energy rise monotonically with rotational speed. The multi-index evaluation balancing mechanical load, energy loss, and residue delivery identifies 385 rpm paired with 85 mm depth as the optimal parameter set. The optimized parameter combination delivers a quantifiable sustainable residue management scheme that balances ecological residue treatment and economic machinery operation costs, supporting low-carbon, sustainable production. Full article

Accelerated urbanisation and associated land-use conversion are reshaping the composition and functions of terrestrial ecosystems globally. In Southeast Asia, ecological change is increasingly mediated not only by demographic urbanisation but also by urban expansion, peri-urban development, and the conversion of agricultural, coastal, and forest land into built-up surfaces. This study integrates multi-source geographical information from 2014 to 2024 to examine 351 provincial-level units in 11 Southeast Asian nations. To describe the spatial-material dimension of urbanisation and ecological conditions, two indices were created: the Composite Nighttime Light Index (CNLI), used as a proxy for urban expansion and built-up development intensity, and the Improved Remote Sensing Ecological Index (IRSEI), which is tailored to tropical coastal locations. The development of human-environment interactions was measured using the Coupling Coordination Degree (CCD) model. Pathways of synergy and trade-off were found using an incremental four-quadrant framework, and nonlinear causes of spatial differentiation were investigated using Spearman correlation and the Optimal Parameter-based Geographical Detector (OPGD). Uncertainty was addressed through data-quality masking, annual compositing, consistent index-construction rules, and cautious interpretation of CCD and driver results as relative provincial-scale patterns. The regional mean CCD rose from 0.250 to 0.314 during the decade, showing a slow improvement; nevertheless, most places still have low to moderate levels of coordination. There is clear pathway divergence, with 38.7% of locations enduring trade-offs where built-up development happens at the price of ecological quality and 58.4% of regions seeing synergistic improvement. The coupling pattern is primarily driven by built-up area expansion, with multiple factors jointly producing strong nonlinear enhancement effects. Climate conditions and forest disturbance further strengthen these effects. This study extends beyond single-country analyses by situating remote-sensing coupling results within land-use transition, peri-urbanisation, urban–rural linkage, and regional-governance perspectives. It provides quantitative evidence to support differentiated policy strategies in rapidly urbanising places. Full article

Cyanobacterial harmful algal blooms (cHABs) pose increasing ecological and public health risks in shallow lakes subject to nutrient enrichment and climate change. This research describes and evaluates a three-dimensional hydrodynamic ecological modeling framework for Fairy Lake, Ontario, using MIKE 3 FM coupled with ECO Lab to simulate lake circulation, thermal structure, nutrient dynamics, and cyanobacteria (PC3) concentrations, with model calibration using 2022 data observations and validation using 2023 data. Hydrodynamic performance showed moderate agreement for lake levels (NSE 0.47–0.52) and strong predictive capability for water temperature (NSE up to 0.96 across depths). Nutrient simulations reproduced seasonal nitrate and phosphate trends, with sediment parameter adjustments to stabilize internal loading dynamics. Cyanobacteria simulations captured seasonal bloom timing and spatial variability between inflow and central basin zones during the calibration and validation periods. The results demonstrate that integrated 3D hydrodynamic ecological modeling reproduces seasonal bloom dynamics in shallow polymictic lakes employing calibrated models and subsequent data, to predict sediment nutrient processes and periodic reassessments. As a result, this framework provides a quantitative basis for evaluating bloom behavior and the ability to predict management scenarios able to test changing climatic and nutrient conditions. Full article

Heavy metals are persistent environmental contaminants that accumulate in soils and vegetation, posing significant risks to ecological systems and human health. Pinus nigra needles are widely recognized as effective biomonitors for reflecting spatial and temporal variations in atmospheric heavy metal deposition. However, the complex, nonlinear interactions among multiple pollutants, environmental factors, and site-specific conditions limit the effectiveness of conventional statistical approaches in accurately modeling and predicting contamination patterns. This study investigated the spatial and seasonal distribution of heavy metals in soils and Pinus nigra needles across different environmental settings in Adıyaman, Türkiye, including urban traffic zones, an organized industrial area, a cement factory vicinity, and a clean reference site. Metal concentrations were determined using inductively coupled plasma mass spectrometry (ICP–MS) following standardized acid digestion procedures. To address the limitations of traditional methods and capture complex nonlinear relationships, advanced machine learning (ML) algorithms—multilayer perceptron, Random Forest, XGBoost, LightGBM, CatBoost, and Gradient Boosting—were employed to model elevation based on heavy metal concentrations. The dataset was divided into training (80%) and testing (20%) subsets, and model performance was evaluated using R², RMSE, MAE, MAPE, and EVS. Among the models, XGBoost exhibited superior predictive performance. Excluding Cd, Cr, and Cu, it achieved R² = 0.9996 (RMSE = 0.068) in training and R² = 0.9526 (RMSE = 17.77) in testing. Including these metals further improved performance to R² = 0.9999 (RMSE = 0.054) for training and R² = 0.9890 (RMSE = 5.55) for testing. The results confirm that Pinus nigra needles are reliable bioindicators of heavy metal accumulation. More importantly, the integration of biomonitoring data with ML techniques provides a powerful framework for capturing complex environmental interactions and improving predictive accuracy, thereby supporting more effective environmental monitoring, risk assessment, and sustainable management strategies. Full article

Sustainable urbanization requires reconciling rapid land development with ecological security, a challenge particularly acute in mountainous megacities. While land-use/cover change (LUCC) substantially reshapes regional carbon storage, conventional whole-region assessments often mask critical spatiotemporal dynamics and subregional heterogeneity. Taking Chongqing, China, as a representative case, this study integrates the Future Land-Use Simulation (FLUS) and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models to decode historical carbon-storage dynamics (2000–2020) and simulate future spatial trajectories (2035) under four multi-scenario land-use pathways: Integrated Development Priority Scenario (IDPS), Ecological Conservation Priority Scenario (ECPS), Farmland Conservation Priority Scenario (FCPS), and Economic Priority Scenario (EPS). Results show a net decline of 8.49 × 10⁶ t in total carbon storage during 2000–2020, primarily driven by the often-overlooked degradation of high-carbon-density grasslands alongside construction-land expansion. Scenario simulations reveal that the ECPS is the only pathway achieving a net carbon-storage increase (+4.26 × 10⁶ t), although the resulting land-use pattern was jointly shaped by ecological protection constraints, land suitability, and scenario-specific land-demand allocation. Crucially, subregional analysis highlights distinct spatial roles: the Northeastern Urban Agglomeration (NUA) emerges as the core for ecological restoration, the Main Urban Area (MUA) remains highly sensitive to development-driven carbon loss, and the Southeastern Urban Agglomeration (SUA) acts as a buffer requiring a delicate development balance. By linking coupled spatial modeling with subregional constraints, this framework advocates for a shift from “one-size-fits-all” land management to precise spatial governance, providing a scalable scientific reference for carbon-oriented sustainable planning in mountainous megacities worldwide. Full article

Land-use change in arid urban agglomerations reshapes landscape ecological risk (LER) and ecosystem service value (ESV), yet few studies jointly diagnose their current coupling state, temporal trajectory, and future scenario response. Focusing on the urban agglomeration on the northern slope of the Tianshan Mountains, we integrated land-use data for 2000, 2010, and 2020 with LER assessment, ESV estimation, static–dynamic coupling zoning, and intPLUS-based 2030 scenario simulation. From 2000 to 2020, cropland and construction land expanded by 46.43% and 107.84%, whereas forest and water bodies declined by 49.76% and 47.64%. LER was dominated by low- and medium-low-risk classes, although medium-high-risk areas expanded locally. Total ESV declined from 512.16 to 429.97 billion CNY, with continued contraction of medium-high- and high-ESV zones. In 2020, potential enhancement zones (PEZs) dominated the integrated management pattern, accounting for 43.64% of the study area. By 2030, static zoning changed only slightly, whereas dynamic and integrated zoning showed clear scenario sensitivity: PEZs accounted for 40.55% under the natural development scenario, while priority governance zones reached 49.06% and 49.26% under economic development and ecological protection scenarios. By treating LER as risk pressure and ESV as service-supply capacity, this framework links static risk–service matching, dynamic trajectory diagnosis, and future scenario response, thereby supporting ecological zoning in arid urban agglomerations. Full article

Litter-inhabiting fungi drive organic matter mineralization, regulate nutrient cycling, and support ecosystem stability. Understanding their dynamics in unique geological habitats is essential for predicting ecological recovery on volcanic landforms. Using high-throughput ITS sequencing and physicochemical analyses, we investigated litter-inhabiting fungal communities across four stand types on the Jingpo Lake lava plateau—shrub forest (SF), deciduous broad-leaved forest (DB), coniferous and broad-leaved mixed forest (CB), and coniferous forest (CF)—at the early (t₁) and late (t₂) stages of decomposition. The results showed significant differences in litter physical and chemical properties among forest stand types (p < 0.05). Regarding community composition, Ascomycota and Basidiomycota dominated throughout, and the core genera were primarily unclassified_o__Helotiales, Mortierella, and unclassified_k__Fungi. Alpha diversity analysis showed that DB had the highest Shannon and Pielou-e indices at stage t₁, while CB exhibited higher OTUs and Chao1 indices at stage t₂. Beta diversity showed that SF communities were significantly separated between the two stages. Co-occurrence networks showed the highest connectivity in CF with pronounced modularity. Notably, LEfSe analysis revealed that DB had the fewest biomarkers, suggesting matrix heterogeneity suppresses single-taxon dominance. Functionally, saprotrophs dominated initially but transitioned toward complex soil saprotroph and endophyte assemblages over time. Redundancy analysis (RDA) identified litter moisture content (LMC) and carbon (C) content as primary drivers, orchestrating a systematic shift in community assembly from “moisture-driven colonization” at t₁ to “carbon quality screening” at t₂. These findings provide a microecological basis for understanding plant-litter-microorganism coupling mechanisms and guiding ecological restoration in lava plateau ecosystems. Full article

Long-term assessment of vegetation recovery in mining-disturbed landscapes is essential for ecological restoration and sustainable land management. This study assessed fractional vegetation cover (FVC) dynamics from 2000 to 2024 in a hilly coal-mining region of the middle Yellow River Basin using Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data. Annual FVC was retrieved from maximum-value NDVI composites using a pixel dichotomy model. Theil–Sen trend analysis, the Mann–Kendall test, lag-1 autocorrelation assessment, coefficient of variation (CV), partial correlation analysis, and the geographical detector model were combined to quantify vegetation recovery, interannual variability, and hydroclimatic–topographic associations. To avoid ambiguity in spatial interpretation, statistics were calculated for the full study region, coalfield polygons, and the surrounding non-mining area. FVC increased across 67.78% of the full study region, 65.42% of the coalfield polygons, and 68.66% of the surrounding non-mining area. High-FVC zones expanded from 33.50% in 2000–2004 to 71.56% in 2020–2024. Because significant positive lag-1 autocorrelation occurred in 33.36% of valid pixels, nominal Mann–Kendall significance was interpreted cautiously. Low- and very-low-CV classes dominated the coalfields, while high-variability pixels were localized monitoring priorities. Precipitation was broadly positively associated with FVC, whereas the independent temperature effect was weak and mostly non-significant. Actual evapotranspiration (AET) had the highest explanatory power in the full geographical-detector model, but an AET-excluded sensitivity analysis showed that temperature, elevation, and precipitation remained important explanatory variables. Thus, AET should be interpreted as an integrated vegetation–water–energy coupling indicator rather than a fully independent causal driver. These findings support restoration-priority identification and sustainable land management in hilly mining regions. Full article

The Agro-Pastoral Transitional Zone in northern China is a typical ecologically fragile area highly sensitive to climate change. Understanding how future climate change will affect the suitability of agricultural and pastoral land use in this region is a critical scientific issue for both climate change research and regional sustainable development. This study integrates multi-scenario climate projections from the Coupled Model Intercomparison Project Phase 6 (CMIP6) with a land use suitability evaluation framework. Three Shared Socioeconomic Pathways (SSPs) are employed, driven by three Integrated Assessment Models (IAMs): IMAGE (SSP1-2.6, low emission), MESSAGE (SSP2-4.5, moderate emission), and REMIND-MAGPIE (SSP5-8.5, high emission). Future climate variables (annual precipitation and accumulated temperature ≥ 10 °C) are statistically downscaled to 1 km resolution for the years 2030, 2050, and 2100. Using a restrictive factor evaluation method that incorporates climatic, topographic, and edaphic indicators, we assess the evolution of land use suitability for both agriculture and livestock farming under each scenario. The results reveal that under moderate- and high-emission scenarios, thermal conditions gradually improve across the study area, particularly in the central and eastern parts, leading to enhanced natural suitability for agricultural and pastoral production. However, precipitation shows no consistent trend of increase or decrease. The moderate emission scenario (SSP2-4.5) yields the most balanced improvement in suitability, with the proportion of unsuitable agricultural land decreasing from 84.5% in 2030 to 37.4% in 2100, and unsuitable pastoral land decreasing from 53.1% to 13.6%. In contrast, the low-emission scenario (SSP1-2.6) results in a sharp contraction of suitable areas by 2100 due to concurrent warming and drying. These findings suggest that climate warming may benefit mid-to-high-latitude agro-pastoral transition zones under moderate emission pathways, but the benefits are spatially heterogeneous and contingent on precipitation stability. This study provides a scientific basis for regional land use planning and climate adaptation strategies. Full article

This study reviewed 187 articles based on systematic review guidelines to evaluate pollution controls through a novel analytical multimedia framework that bridges air, water, soil, and acoustic compartments, alongside emerging digital and circular economy paradigms. With 5–7% of worldwide CO₂ emissions originating in the cement industry, fugitive particulate matter constitutes more than 90% of a plant’s emissions. The results show that the cement sector has considerable potential for decarbonization, though highly context-dependent. Under optimal conditions, clinker substitution coupled with alternative fuels could reduce direct emissions by up to 50% and total energy usage by 44%, constrained by regional material availability. Fully integrated carbon capture systems (TRL 7–9) could reduce exhaust emissions by up to 90%, contingent upon overcoming significant energy penalties. Engineering controls in dry-process mills reduced daily occupational noise exposure from 102.9 to 88.3 dB(A). Regarding soil pollution, cement kiln dust increased the unconfined compressive strength of native soils up to 9.9 times for geotechnical stabilization. In water management, hybrid biological systems removed 94.5% of particulate matter and reduced oxygen demand by over 87%, while advanced biomonitoring decreased effluent toxicity by over 90%. The significance of this study lies in overcoming traditional siloed assessments by introducing a holistic multimedia framework that maps biogeochemical interconnectivity alongside Industry 4.0 paradigms. Ultimately, this review provides a vital sociotechnical road map for stakeholders to align localized ecological risk mitigation with stringent 2026 global market mechanisms, such as the carbon border adjustment mechanism and mandatory environmental, social and governance disclosures, ensuring both industrial competitiveness and environmental stewardship. Full article