Search Results (3,331)

Fish are an important criterion for evaluating the quality of river ecosystems, and water flow characteristics may be the main factor affecting the living environment of fish. As the main component of a river, the topography of the bank slope has a significant impact on the characteristics of nearshore water flow. At the same time, eco-revetment structure has the functions of smoothing water flow, maintaining stable bank slopes, and improving river ecology. It can reset the distribution of nearshore water flow and provide a stable living environment for fish. This study focuses on the middle and lower reaches of the Yangtze River as the research area, with the main research object being grass carp. We construct a generalized model based on river morphology and flow characteristics. A new eco-revetment structure is proposed with the main research area of nearshore waters, aiming to improve the flow state of nearshore water and enhance its ecology. A suitability evaluation model for grass carp habitat was constructed based on Large Eddy Simulation and fuzzy mathematics theory, with water flow as the main habitat influencing factor. We study the distribution pattern of suitability for grass carp habitats near nearshore waters. The results indicate that the nitrogen phosphorus ratio near the top of the revetment structure is close to the Redfield value and can be used as a stable foraging area for fish. The flow rate is the dominant factor for the habitat of juvenile grass carp. When there is no vegetation, the suitability of region A is 0–0.4, the suitability of region B is 0.2–0.6, and the area proportion of the high suitability area (0.4–0.6) is maintained at 10–30% with the increase in the flow rate. Region C is not suitable for the long-term survival of juvenile grass carp. When there is vegetation, the suitability of region A ranges from 0 to 0.6, and the proportion of low-suitability areas decreases. The suitability of region B ranges from 0.4 to 0.6, and the proportion of suitable areas is positively correlated with flow velocity. The suitability of region C is consistent with the absence of vegetation. The dominant factors for fish spawning habitat are flow velocity, vorticity, and kinetic energy gradient. The spawning suitability zone (HSI ≥ 0.6) is located between the spanwise structures, with a proportion positively correlated with flow velocity and higher suitability on the deep-water side. The existence of fish has little impact on the habitat. In the juvenile fish habitat area, the proportion of areas suitable for juvenile fish in region A has slightly decreased, and the suitability of region B has increased. In spawning grounds, an HSI ≥ 0.6 accounts for about 5% of the decrease compared to no-fish conditions, and overall can meet the needs of fish habitat, foraging, and spawning. This article provides ideas and foundations for the design of future new eco-revetment structures and a suitability analysis of living environments for fish. Full article

Scientific studies of mine closure and ecosystem management have become very important since the rate of coal mine closures in China has increased rapidly over the last decade. This study first analyzed spatiotemporal changes in land use and ecosystem services value (ESV) during the period 2000–2020 around the Kailuan Mining Area in Tangshan City. The area has a history of over 100 years of continuous mining activities in the region. The analyses used the PLUS model, multi-scenario simulation, and ESV equivalent factor method and multi-source data on land use, mining activities, socioeconomic factors, and climatic conditions. The study then projected land-use changes and spatiotemporal ESV characteristics for the year 2030 for two alternatives: (1) the Current Development Scenario (CDS), representing the current pace of development without mine closure; and (2) the Ecological Restoration Scenario (ERS), representing mine closure and ecological restoration. Key results include: (1) during 2000–2020, cultivated land and construction land were the primary land uses, with the overall trends showing decrease in cultivated, forest, pasture, and unused lands, varying water use areas, and continuously increasing construction land; (2) the revised ESV results show that total ESV declined from 31.27 million USD in 2000 to 25.30 million USD in 2020, a net decrease of 6.19 million USD, mainly because of cropland loss and degradation of forest and grassland; and (3) for 2030, the CDS projected a continued decline in total ESV to 24.30 million USD, whereas the ERS increased total ESV to 26.50 million USD, which is 2.19 million USD higher than the CDS and 1.20 million USD higher than the 2020 baseline. Compared with the CDS, the ERS increased cropland by 13.20 km² and reduced construction land by 10.06 km², indicating that reclaiming subsided water bodies and idle construction land into cropland and restored ecological land can enhance ecosystem services while mitigating subsidence-related risks. The framework can support data-driven post-mining land-use planning and ecological management in resource-based regions. Full article

As the largest inter-basin water diversion project in eastern China, the Eastern Route of China’s South-to-North Water Diversion Project (ER-SNWDP) plays a crucial role in alleviating water shortages and ensuring regional ecological security. However, large-scale water diversion that uses natural lakes as impounded lakes across different basins has impacted on the structure and function of the original ecosystems. To explore the changes in the food web and ecosystem structure of the impounded lakes during different operation periods of the ER-SNWDP, we constructed Ecopath models for Hongze Lake in 2010–2011 (pre-operation), 2017–2018 (initial operation), and 2023–2024 (operational period). Our results showed that the trophic energy flow in Hongze Lake was dominated by the detrital food chain, with the highest trophic level ranging from 3.06 to 3.50. Energy flows at trophic levels I and II accounted for a high proportion of the total throughput, and the interactions between trophic levels were relatively simple, indicating that Hongze Lake is approaching a mature ecosystem. Compared with the pre-operation period, the average trophic level, food chain length, and energy conversion efficiency of Hongze Lake declined during the initial operation period, but rebounded during the operational period, though still remaining lower than the pre-operation period. Ecosystem stability followed a similar trajectory: the total primary production/total respiration (TPP/TR) and the system omnivory index (SOI) indicated that ecosystem maturity decreased during the initial operation and increased during the operational period. Fishing activities had negative effects on most functional groups during the pre-operation and initial operation periods, whereas the negative effects from zooplankton and non-native species groups increased during the operational period. Based on changes in the food web structure and ecosystem of Hongze Lake across different water diversion periods, we suggest that the management of Hongze Lake should establish precautionary fishing management measures targeting the effects of filter-feeding functional groups and non-native species, optimize the species and quantities of restocking initiatives, prioritize the protection of critical habitat integrity, and implement long-term ecological monitoring. Full article

Digital transformation among small and medium enterprises (SMEs) in developing countries is limited by a persistent gap between prevailing adoption frameworks and the sociocultural realities of target populations. Frameworks such as the Technology Acceptance Model (TAM), the Technology-Organization-Environment (TOE) framework, UTAUT, and IDT were originally developed for industrialized contexts and do not adequately account for the cultural factors influencing adoption behavior in structurally distinct environments. A systematic mapping of 256 articles revealed that only 14 consider cultural behavior as a variable, and none utilize a validated cultural measurement instrument. This study introduces the Culturally Contextualized Digital Transformation Model (CC-DTM), a four-layer theoretical architecture that integrates the TOE framework, TAM constructs, and Hofstede’s cultural dimensions, operationalized as individual-level espoused values rather than national aggregate scores. The model incorporates a novel meso-level construct, Ecosystem Density, which mediates the relationship between environmental context and organizational readiness. The CC-DTM specifies 22 constructs and 15 directional hypotheses, organized into an initial empirical agenda (H1–H12) and deferred extensions (H13–H15). Additionally, a three-configuration typology based on internal SME attributes is developed. A two-phase validation roadmap, consisting of expert-panel content assessment and configurational case illustration across ten Chilean SMEs, is proposed. Full article

With the advancement of systematic ecological protection and restoration, ecosystem coordination assessment and multi-scale differentiation analysis have become increasingly important for regional ecological governance. In this context, this study develops a multi-scale coupling coordination evaluation framework for the mountain–water–forest–farmland–lake (MWFFL) system in Dangtu County, Anhui Province. The framework integrates 14 indicators across five subsystems, uses a combined weighting method based on the Entropy Weight Method and Analytic Hierarchy Process, and applies the coupling coordination degree (CCD) model and trend analysis to characterize inter-system coordination and its spatiotemporal patterns at the regional and ecosystem scales. The results indicate that land use is dominated by arable land, with water bodies forming the structural backbone and construction land distributed in clusters. From 2020 to 2024, the mean CCD remained stable around 0.675, indicating that the overall coupling coordination level was relatively stable. Spatially, the CCD pattern remained higher in the southwest and lower in the northwest, with a new high-value clustering zone emerging in the south. At the ecosystem scale, the four ecological restoration units showed distinct spatiotemporal patterns of coupling coordination. This multi-scale MWFFL evaluation framework supports regional ecological monitoring and provides a reference for restoration effectiveness assessment in similar regions under the life community concept. Full article

Rapid urbanization and climate change are reshaping land-use systems, intensifying conflicts among urban growth, cultivated land conservation, and ecosystem protection. Understanding how land-use change affects carbon balance is important for designing sustainable land management and climate-resilient spatial planning. Taking Nanjing, China, as a case study, this study investigates how land-use change shaped carbon emissions, carbon sequestration, and net carbon emissions from 2000 to 2020 and further evaluates their future changes in 2030 under SSP–RCP scenarios. By integrating land-use simulation, carbon accounting, and contribution–sensitivity analysis, this study distinguishes land-use conversion effects from intra-type intensity change effects associated with changes in carbon emission or sequestration intensity within unchanged land categories. From 2000 to 2020, Nanjing experienced a substantial increase in net carbon emissions, with construction land expansion and higher emission intensity of construction land serving as the primary drivers. Although the carbon sink function was still mainly supported by cultivated land and forest land, land conversion and changes in sequestration intensity weakened the regional carbon balance. Under all SSP–RCP scenarios, simulated net carbon emissions for 2030 exceed the 2020 level, even though lower carbon intensity under SSP1–2.6 can partially mitigate emission growth. Conversion to construction land shows the highest carbon cost, especially when cultivated or ecological land is occupied. These findings highlight the need to coordinate urban expansion control, farmland protection, ecological restoration, and low-carbon industrial transformation. The study offers empirical support for improving sustainable land management and guiding spatial planning toward low-carbon development. Full article

Information disorders condition electoral processes, becoming a major institutional concern. In response, the European Union and various fact-checking organisations co-organised the Elections24Check project to curb disinformation in the 2024 European elections. This research analyses the activities, strategies, and editorial behaviour of the five Spanish fact-checking agencies that are integrated into the initiative. Through a content analysis applied to 3256 publications, the findings demonstrate the maturity of the Spanish ecosystem, which led the project by contributing 32.8% of the total content. Strategically, reactive action predominated, except for Newtral, which prioritised prebunking (62.6%). Political scrutiny was minor (6.6%), focusing on major coalitions and far-right leaders. Thematically, highlights included war conflicts, migration, and national/regional frameworks utilised for emotional polarisation, displacing the focus from the strictly European debate. In conclusion, Spain consolidates itself as a cornerstone of European fact-checking. However, the results reveal inefficiencies in the project’s extended timeframe, suggesting more constrained and effective frameworks for election campaigns. Furthermore, the persistence of narratives anchored to local agendas evidences a strategic fragmentation that hinders the construction of a fully pan-European public space. Full article

The rapid development of high-density cities has triggered severe ecological challenges, including habitat fragmentation, urban heat island (UHI) effects, and conflicting demands for public recreation. Traditional ecological networks (ENs) often focus only on “source” landscapes while neglecting degraded “sink” areas. This bias limits the ability of planners to resolve complex spatial conflicts. Therefore, the primary aim of this study is to develop a robust spatial planning framework that mitigates urban ecological conflicts and enhances regional resilience. To achieve this, we constructed a composite ecological network (CEN) for the high-density city of Guangzhou that harmonizes bird habitat conservation, thermal regulation, and cultural recreation. We combined the MaxEnt model, morphological spatial pattern analysis (MSPA), and circuit theory to identify functional “sources” and “sinks” across these three dimensions. Next, using complex network theory, we optimized the CEN and evaluated its structural robustness using low degree addition (LDA) and low betweenness addition (LBA) strategies. The results indicate the following: (1) The CEN effectively captured the complex mosaic landscape of the city. (2) Single-objective networks displayed distinct spatial differences—the recreational network formed a dispersed web of 242 corridors, while habitat and climate networks remained highly clustered. (3) The integrated CEN generated 1137 multi-layered corridors, creating a vital green skeleton to support species dispersal, mitigate UHI effects, and improve cultural access. (4) Optimization simulations verified that the LBA strategy provided the highest stability against targeted attacks by balancing network connectivity with local aggregation. Ultimately, this framework offers a highly adaptable planning tool for dense cities, providing precise spatial guidance to overcome ecological bottlenecks and harmonize urban growth with ecosystem resilience. Full article

As the environmental sustainability of blockchain technology becomes a focal point of public and academic debate, understanding how technically engaged communities frame this issue is increasingly important. This study examines 3000 long-form comments from a highly active sustainability-focused Bitcointalk thread to analyze sentiment patterns, recurring arguments, and the linguistic cues associated with community responses to environmental criticism. Using Natural Language Processing (NLP) methods, we apply Valence Aware Dictionary and sEntiment Reasoner (VADER) sentiment analysis to classify the discourse, n-gram extraction to identify dominant thematic expressions, and a Random Forest model combined with SHapley Additive exPlanations (SHAP) to interpret the lexical features most strongly associated with sentiment polarity. The results show a strongly positive and internally consistent discourse structure: 87.63% of comments are classified as positive, while negative and neutral comments are comparatively rare. The dominant themes emphasize energy consumption as a necessary trade-off for network security, while external criticism is frequently reframed or rejected. Explanatory modeling further indicates that negative sentiment is primarily driven by terms associated with climate risk, damage, and reputational concerns when users respond to criticism. Rather than claiming to capture the cryptocurrency ecosystem as a whole, this study presents a localized case study of one Bitcointalk mega-thread and describes it as a highly homogeneous narrative space shaped by recurrent rebuttal and rhetorical reinforcement. The findings offer a focused contribution to understanding how insider communities construct sustainability narratives around blockchain energy use, while also highlighting the need for broader comparative and network-structural research in future work. Full article

In the context of an increasingly complex and dynamic digital ecosystem, accurately assessing the value of Specialized, Refined, Differentiated, and Innovative (SRDI) enterprises is crucial for making effective decisions. Traditional valuation methods struggle to effectively address issues such as the high R&D expenditures and significant operational risks associated with these enterprises. This study proposes an interpretable intelligent decision-support framework for valuing SRDI enterprises listed on the Beijing Stock Exchange (BSE), constructing a multidimensional indicator system that encompasses solvency, profitability, and R&D capabilities. Feature importance screening using the XGBoost algorithm was conducted to identify key indicators as input variables for a backpropagation (BP) neural network. Concurrently, the Particle Swarm Optimization (PSO) algorithm was applied to the neural network to optimize initial weights and thresholds, thereby modeling nonlinear valuation relationships. Empirical analysis of 770 SRDI firms listed on the Beijing Stock Exchange from 2020 to 2024 indicates that the XGBoost-PSO-BPNN model achieved a coefficient of determination of 0.8083 on the test set, outperforming traditional linear models and benchmark models such as single-tree models. SHAP explainability analysis further reveals that current asset turnover, return on assets, and equity concentration are the primary value drivers. This study employs various clustering methods to further classify enterprises into three categories and proposes recommendations for differentiated regulatory policies, providing intelligent decision support for enterprises operating within complex digital ecosystems. Full article

Vegetation is an important component of ecosystems and plays an important role in carbon balance, water balance, and energy conversion. The spatial and temporal changes in the normalized difference vegetation index (NDVI), water resources, and hydrometeorological factors in southwest China between 2003 and 2020 were investigated using multisource remote sensing data. Correlation analyses were performed to assess the correlation among NDVI, water resource changes, and hydrometeorological factors with different time lags. A stepwise regression model with different lag times was constructed to clarify the effects of four topographic factors and eight climatic factors on NDVI, and the following conclusions were obtained: (1) NDVI increased from 2003 to 2020, and the increase became obvious after 2012. (2) NDVI was considerably affected by alterations in the soil water content caused by natural changes. The correlation of NDVI with evapotranspiration and precipitation was high, followed by NDVI’s correlation with surface temperature. The spatial distribution of the positive correlation between NDVI and evapotranspiration and NDVI and precipitation was relatively consistent, and a positive correlation was observed in most parts of Southwest China. (3) The hydrometeorological factors mainly affected NDVI with a lag of 0–1 month, and the correlation was high in western Sichuan and most of Yunnan. In Yunnan, Available Water Capacity (AWC) affected NDVI with a lag of 0–2 months; the lag was 0–1 month in western Yunnan and 1–2 months in eastern Yunnan. (4) In terms of different vertical heights, the NDVI in the regions with altitudes higher than 3000 m was affected by climate change, especially evapotranspiration and precipitation. (5) Digital Elevation Model (DEM), Latitude (Lat), Evapotranspiration (ET), Precipitation (PRCP), Land Surface Temperature (LST), and NDVI were closely related in the construction of stepwise regression models with different lag times. Full article

Accurate assessment of carbon storage dynamics and their driving factors is important for ecological sustainability and land management on the Loess Plateau under China’s dual carbon goals. In this study, the InVEST and PLUS models were integrated to evaluate carbon storage changes from 2000 to 2020 and simulate future carbon storage patterns for 2030 under four development scenarios, including natural development (ND), rapid development (RD), cropland protection (CP), and ecological protection (EP). In addition, the XGBoost-SHAP framework was employed to identify the dominant drivers and nonlinear response relationships controlling spatial variation in carbon storage. During 2000–2020, ecosystem carbon storage across the Loess Plateau generally increased, rising from 5.780 Pg to 5.893 Pg. Spatially, carbon storage displayed a pronounced pattern characterized by higher levels in the southeast and lower levels in the northwest, aligning with forest–grassland restoration belts. Scenario simulations showed that EP produced the largest carbon storage gain, with total carbon storage projected to reach 5.962 Pg in 2030. In contrast, RD reduced carbon storage to 5.858 Pg because of intensive construction land expansion. XGBoost-SHAP results identified net primary productivity (NPP) as the most influential factor controlling spatial variation in carbon storage, accounting for 57.3% of the total explanatory importance, whereas soil erosion (SE) exhibited a strong negative effect on carbon storage. Population density (POPD) also exerted a negative effect, whereas gross domestic product (GDP) showed positive contributions in economically developed counties. These findings enhance understanding of the spatial response characteristics of carbon storage under environmental gradients and human disturbance across the Loess Plateau. They further provide scientific support for differentiated ecological management and regionally adapted carbon mitigation planning. Full article

Under the concurrent advancement of ecological civilization and resource-dependent region transformation, key state-owned forest areas in northeast China have shifted from timber supply to ecosystem protection. However, while the Natural Forest Protection Program has restored forest resources and increased coverage, it has also led to the contraction of traditional industries, reduced employment, population outflow, and a structural tension between weak economic growth and enhanced ecological functions. This study aims to investigate how labor mobility affects the coordinated development of economic and ecological welfare in these regions. To achieve this, we construct economic and ecological welfare indices using entropy weighting and calculate their coupling coordination degree based on panel data from the China Forestry Statistical Yearbook (2000–2017) and the China Forestry and Grassland Statistical Yearbook (2018–2025). Our key scientific contributions are as follows: (1) we reveal a nonlinear and significantly negative impact of labor mobility on coupling coordination; (2) we identify industrial structure as a partial mediating channel; and (3) we uncover significant regional and developmental stage heterogeneity. Methodologically, we employ fixed-effects, mediation, threshold, and spatial panel models to ensure robustness. The findings provide novel insights into labor–environment trade-offs in forest-dependent regions and offer policy implications for optimizing labor allocation, strengthening ecological compensation and industrial synergy, and improving regional governance to achieve coordinated economic–ecological development. Full article

The Suaeda heteroptera wetland in the Liaohe Estuary is a typical coastal wetland in northern China. This study presents a coupled PSR–entropy–PLSR model to assess ecosystem health and its driving factors, using long-term Landsat data from 1995 to 2024. The results show that the Ecosystem Health Index (EHI) dropped from 0.61 in 1995 to 0.20 in 2010, and then rebounded to 0.66 in 2024. The PLSR analysis identified four key drivers: Suaeda heteroptera carbon storage, mean patch area, aquaculture development intensity, and vegetation recovery rate. The simplified PLSR model constructed using these indicators achieved a cross-validation R² of 0.967. This coupled model provides a simple, efficient, and reliable method for the rapid assessment and long-term monitoring of coastal wetland ecosystem health. Full article

Per- and polyfluoroalkyl substances (PFASs) are persistent emerging contaminants characterized by high environmental stability and biotoxicity. Ubiquitous detection of these contaminants across aquatic environments poses severe threats to ecosystem stability and human health, while constructed wetlands (CWs) serve as a sustainable low-carbon alternative for the remediation of PFAS-laden wastewater. However, traditional mechanisms such as matrix adsorption, phytoaccumulation, and microbial transformation often suffer from low efficiency, rapid saturation, and incomplete degradation. To overcome the above drawbacks, the arbuscular mycorrhizal fungi (AMF)–plant–microbe synergistic consortium has become a promising remediation candidate, which facilitates PFAS immobilization and biodegradation via symbiotic crosstalk among three components. This paper reviews recent advancements in PFAS remediation within AMF-facilitated systems, examining fundamental synergistic mechanisms, treatment efficiencies, and key influencing factors. We propose several optimization strategies, including substrate modification, operational parameter refinement, and the integration of advanced technologies. Furthermore, we emphasize the necessity of elucidating the molecular pathways governing long-chain PFAS degradation and addressing current bottlenecks in engineering applications. Future research should prioritize molecular interaction level interaction mechanisms, the development of anti-interference systems, and field-scale validation. This review provides a theoretical foundation and technical framework for leveraging AMF–plant–microbe synergism to enhance PFAS removal in CWs. Full article