Search Results (879)

Soil microbes play pivotal roles in nutrient cycling and ecosystem functioning across diverse farmland systems. Orchard grass coverage has been demonstrated to effectively alter microbial community structure and promote nutrient cycling. However, the effects of soybean intercropping on soil bacterial community characteristics and nutrient contents in citrus orchards remain poorly understood. In this study, a field experiment was conducted in a citrus orchard involving three planting patterns: clean tillage (CT), natural grass (NG), and soybean intercropping (SI). The physicochemical properties and bacterial community structure of the topsoil (0–40 cm depth) were determined. Results showed that compared with CT, NG and SI significantly increased cation exchange capacity (CEC), soil organic matter (SOM), alkali-hydrolyzable nitrogen (AN), and available potassium (AK). SI further elevated soil pH and available phosphorus (AP) relative to CT and NG. Bacterial diversity ranked SI > NG > CT, with PCoA showing lower community variation under SI. A total of 31 bacterial phyla were detected in the citrus orchard soil, with Cyanobacteria (17.20~40.81%), Proteobacteria (15.04~24.19%), Acidobacteriota (8.95~14.66%), and Chloroflexi (3.93~21.13%) identified as the dominant phyla. SI enriched Cyanobacteria and Proteobacteria but reduced Acidobacteriota, Chloroflexi, and Actinobacteriota. Mantel tests confirmed CEC and SOM as key drivers of bacterial community structure. Overall, soybean intercropping improves soil microecology and exhibits great potential for soil quality improvement in citrus orchards under local conditions. Full article

As the core pillar of international trade, the global shipping industry has seen its carbon and pollutant emissions become a key challenge in global environmental governance. Statistics indicate that ship carbon emissions account for 3% of the world’s total anthropogenic CO₂ emissions, while contributing 20% of global NO_x and 12% of SO₂ emissions, posing a serious threat to coastal ecosystems and public health. In response to the International Maritime Organization (IMO) “Net Zero Framework” and national green shipping policies, the transformation of ship power systems toward low-carbon and zero-carbon operation has become an inevitable trend. This paper systematically reviews the research progress and application status of green energy materials for ships, focusing on the working principles, technical characteristics, and engineering application cases of solar photovoltaic (PV) materials, wind energy utilization technologies, fuel cell materials, and alternative clean energy fuels (e.g., liquefied natural gas (LNG), methanol, and hydrogen energy). It also discusses the integration mode and optimization strategy of multi-energy hybrid power systems. The research findings show that solar photovoltaic technology has achieved large-scale application in coastal ships; hydrogen fuel cells are suitable for long-range ocean navigation scenarios due to their high energy density; LNG and methanol have become the current mainstream alternative fuels, relying on mature infrastructure; and hybrid energy systems can significantly improve power supply reliability and emission reduction efficiency through multi-energy complementarity. Finally, aiming at the existing bottlenecks (e.g., cost, energy storage, and safety) of various technologies, future development directions are proposed. This study provides a reference for the technological breakthrough and engineering practice of green energy power systems for ships and contributes to the realization of the “carbon neutrality” goal in the global shipping industry. Full article

In the digital economy era, digital inclusive finance represents a paradigmatic reconstruction of key economic information flows. This study integrates multi-source panel data of 27 cities in the Yangtze River Delta from 2011 to 2023. By constructing an economic geography composite spatial weight matrix and a nonlinear spatial panel model, this study analyzes the impact of the diffusion of digital inclusive financial information on industrial structure upgrading. The results show that: (1) digital financial inclusion exerts a significant direct effect and spatial spillover effect on industrial structure; (2) the local effect exhibits a “U-shaped” curve with an accelerating characteristic on the right side; the spatial spillover effect demonstrates an “inverted U-shaped” curve, revealing the transformation law and threshold effect of the diffusion and aggregation of digital financial information benefits; (3) digital payment and digital credit constitute the core information flows driving the coordinated upgrading of industries; and (4) entrepreneurial activity exerts a partial mediating effects, and exhibits a spatial mediating effect, while the technological innovation only demonstrates a significant local mediating effect. The findings provide quantitative evidence to support the optimization of the digital financial information ecosystem and the realization of coordinated industrial upgrading in the Yangtze River Delta. Full article

This paper systematically reviews losartan, a hypertension pharmaceutical compound that is one of many newly identified emerging contaminants in water. Worldwide use of pharmaceuticals continues to grow, and losartan has been identified as a contaminant that frequently accumulates in aquatic systems as a result of this global increase in use. The paper presents systematic reviews on the environmental occurrence, physicochemical characteristics, analytical methods of detection, and remediation techniques associated with losartan contamination. Losartan is often detected at levels of ng L⁻¹–µg L⁻¹ in wastewater systems, surface water and marine ecosystems, very effectively demonstrating the inadequacies of existing conventional wastewater treatment facilities, which are typically capable of removing only 20–70% of the contamination, with this variability largely attributed to differences in hydraulic/solids retention times, operational conditions, influent organic load, and the limited microbial acclimatization to recalcitrant pharmaceutical compounds. Emerging remediation technologies demonstrate the potential for removal efficiencies of >90% include hybrid systems, advanced electrochemical processes, new improved adsorption systems, and novel material for adsorption. However, there are still considerable barriers to progress, including excessive energy use, high operating costs, and perhaps most concerning, potentially toxic transition products generated by partial degradation. Furthermore, the literature review identified key literature gaps: lack of specific regulations, absence of full-scale studies, and inconsistencies in by-product toxicity assessments. The conclusion of this review is that to achieve worldwide water security and sustainability of aquatic resources, effective mitigation of the environmental risks associated with losartan requires combined approaches comprising innovative technologies, comprehensive ecotoxicological investigations, and improved collaboration between scientists, policymakers, and industry. Full article

Against the backdrop of intensifying global climate change and water eutrophication, the increasing occurrence of Harmful Algal Blooms (HABs) poses a significant threat to aquatic ecosystems, human health, and socio-economic activities. The occurrence and development of HABs are complex processes governed by the interaction of physical, chemical, and biological factors. Therefore, timely and accurate monitoring is essential for early warning and scientific research. This paper comprehensively reviews recent advances in HAB monitoring technologies, with a focus on two core components: sensors and monitoring platforms. First, organized around key environmental parameters, it summarizes the principles, applications, and limitations of in situ sensors, such as multi-parameter water quality sondes, Imaging Flow Cyto-bots (IFCB), and Environmental Sample Processors (ESP), as well as laboratory-based analytical techniques such as HPLC-MS for measuring physical, chemical, and biological indicators. Second, it compares the technical characteristics of three major monitoring platforms (including field surveys, remote sensing, and autonomous systems) and discusses their potential for synergistic application. Finally, this review proposes a future framework for an integrated “Space–Air–Ground–Sea” intelligent monitoring network and explores possible pathways to address current challenges through cross-platform data fusion, sensor miniaturization, intelligentization, and artificial intelligence-driven decision support. This review aims to provide a comprehensive reference for the optimization and innovation of HAB monitoring technologies and to promote the development of the field toward greater integration, intelligence, and real-time monitoring capability. Full article

Urban trees constitute a key component of sustainable urban green infrastructure, providing ecosystem services related to climate regulation, biodiversity conservation, and human well-being. At the same time, mature and veteran trees in public spaces are frequently perceived as a safety risk due to visible structural defects, often resulting in precautionary removal decisions based solely on visual assessment. This study evaluates the applicability of acoustic tomography as a non-invasive diagnostic tool supporting sustainable urban tree management using the city of Jarocin (western Poland) as a case study. Following preliminary Visual Tree Assessment (VTA), 20 mature urban trees were identified, of which six representative specimens were subjected to detailed analysis using the PiCUS Sonic Tomograph 3. The internal condition of tree trunks, sound wave propagation velocity, residual wall thickness (t/R ratio), and structural stability were analysed in relation to species characteristics and site conditions. The results demonstrated considerable variation in the internal condition of the analysed trees and revealed that visible external defects did not necessarily correspond to a critical reduction in mechanical stability. Five out of six examined trees met or approached the accepted safety threshold (t/R ≥ 0.30), supporting their retention rather than removal. In several cases, acoustic tomography identified substantially larger zones of structurally sound wood than suggested by visual inspection alone. The findings confirm that integrating acoustic tomography into urban tree risk assessment can improve decision-making accuracy, reduce unnecessary tree removal, and support biodiversity-oriented and climate-adaptive urban green space management. The proposed approach may serve as a transferable framework for sustainable management of mature urban trees in medium-sized cities. Full article

Dioxins are highly persistent organic pollutants that exist in soil. Their hydrophobic and lipophilic characteristics facilitate long-term stability, posing high risks to the ecosystem and human health. They can be released by different sources, such as the incineration of waste materials, industrial activities, the production of pesticides, and natural or accidental events like forest fires. Dioxins accumulate in food chains and persist in the environment because dioxins are less volatile as well as chemically stable and can strongly bind to organic matter. The accumulation and persistence of dioxins in aquatic and terrestrial systems make them a significant threat to the environment, even at very low concentrations. This review explains the key sources of dioxin-contaminated soil, including industrial emissions and atmospheric deposition, and assesses the associated risks. The transport, places of contamination, and overall status of dioxins are also highlighted in this study. The review also examines the mechanisms of dioxin toxicity, focusing on their interference with hormonal functions and gene expression, as mediated through the aryl hydrocarbon receptor (AhR). This AhR activation leads to gene responses and causes immunotoxicity, endocrine disruption, and oxidative stress. Furthermore, various remediation strategies like biological, physical, and chemical remediation are discussed here as effective approaches for reducing ecological and health risks and promoting soil sustainability. Full article

As an important component of forest ecosystem processes, leaf litterfall plays a key role in nutrient cycling and ecosystem functioning. However, monitoring litterfall dynamics in subtropical forests remains challenging due to complex community structures and asynchronous leaf phenology, which limit the applicability of remote sensing approaches developed for temperate forests. As a critical linkage between vegetation and soil carbon pools, leaf litterfall directly influences forest carbon sequestration by providing carbon inputs in the form of litter. Unlike the concentrated autumn leaf fall in temperate forests, subtropical forests exhibit complex community structures with concurrent leaf abscission and new leaf growth, limiting the applicability of temperate-focused remote sensing techniques. To address this, we collected annual leaf litterfall data from 18 plots in eastern China’s subtropical forests and integrated these with high-resolution Sentinel-2 imagery using supervised machine learning models to develop a novel monitoring method. Our results indicated that subtropical forests exhibited clear seasonal leaf litterfall peaks during spring, summer, and autumn. Sentinel-2 satellite imagery combined with supervised machine learning algorithms can effectively monitor forest leaf litterfall dynamics. Temporal models, which use multi-date monthly spectral differences (R²_adj = 0.70, RMSE = 0.46, RPD = 1.86), significantly outperformed instantaneous models based on single-date canopy states (R²_adj = 0.33, RMSE = 0.85, RPD = 1.24). Following variable selection, model performance improved, with R² increasing by more than 2% in most models and the number of variables reduced by over 44%. Robustness analysis indicated that the model was spatially robust (no significant bias among sites), and despite seasonal intercept differences, the slopes were consistent, enabling reliable tracking of litterfall dynamics. Among the examined spectral indices and canopy characteristics, those reflecting canopy greenness, pigments, and structure contributed over 65%, with WV-VI, MCARI2, and LAI being most influential. Incorporating drought-sensitive water indices and soil exposure-related mineral indices further enhanced model performance. These indices may partially reflect drought stress or seasonal canopy opening. Our findings provide a new method for monitoring leaf litterfall dynamics in structurally complex subtropical forests and offer a critical theoretical basis for accurately assessing leaf fall dynamics. Our findings provide a novel and effective method for monitoring leaf litterfall dynamics in structurally complex subtropical forests, improving seasonal litterfall assessment and supporting vegetation monitoring, with potential implications for ecosystem- and carbon-related studies. Full article

This study comprehensively analyzed the compounded effects of climatic factors and non-climatic factors on vegetation dynamics in the northern Shaanxi Loess Plateau region in China. The objective was to provide robust scientific insights and a solid theoretical framework to support the long-term stability and sustainable development of the local ecosystem. The temperature vegetation dryness index was used to improve the water stress factor of the CASA model, so as to estimate the NPP of vegetation on the Loess Plateau of northern Shaanxi from 2000 to 2020. The temporal and spatial change characteristics of vegetation NPP and its relationship with climatic factors were analyzed using the coefficient of variation, the Mann–Kendall test of significance, and second-order partial correlation analysis. The partial derivative residual trend method was used to isolate the specific impacts of climatic factors and non-climatic factors on vegetation NPP. The results indicate the following: (1) The vegetation NPP shows a notable upward trend, with an annual growth rate of 9.4195 gC·m⁻²·a⁻¹ and a long-term average of 269.71 gC·m⁻², with the spatial distribution showing markedly high south, low north, and latitudinal zonation characteristics. (2) Vegetation NPP exhibits positive correlations with temperature, precipitation, and solar radiation. Among these factors, precipitation shows the strongest correlation with variations in vegetation NPP. (3) Non-climatic factors are the main factor affecting vegetation NPP across most parts of the study area, which is greater than the effect of selected climatic factors, and human activities may be the key component within non-climatic factors. Full article

The anthropogenic transformation of the steppe zone in the southern East European Plain has led to the destruction and catastrophic fragmentation of natural ecosystems. Due to the presence of highly fertile lands and the deposits of the Donetsk coal basin, up to 90% of the territory is occupied by agricultural and industrial activities, urban agglomerations, other settlements, and extensive transportation networks. The predominant use of introduced species in artificial plantings (within the city limits, the ratio of species to quantity is 7:3) leads to the widespread spread of alien species, further isolation of natural habitats, and their subsequent degradation. The problem of preserving natural ecosystems and restoring a stable balance in their functioning can be solved through the widespread introduction of native species into all types of plantings capable of serving as ecological corridors. In this regard, we analyzed the key characteristics of native tree and shrub species that determine their functional value. The results indicate that of the 85 native plant species, only two cannot be used because they carry pests and diseases dangerous to agricultural crops. The remaining 83 species are suitable for various planting types, based on a set of individual characteristics, and 29 of these are universal for all planting types. Outside urban ecosystems, these 83 native species can completely replace introduced species. Within urban ecosystems, the need for their combination remains. Despite a number of advantages identified in native species in conditions of anthropogenic pollution (relatively high viability, long lifespan, good resistance to mechanical stress), native species lack a number of categories of traits necessary for the more effective functioning of urban green infrastructure. Among them, there is an insufficient number of tall species (>25 m) and conifers, which are more effective in purifying and improving the health of the atmosphere, as well as beautifully flowering and generally highly decorative species necessary for recreational areas and other territories that, among other things, perform esthetic functions. Full article

Global climate change and rapid socio-economic development have increasingly exacerbated the imbalance between ecosystem service (ES) supply and demand. Taking the Pinglu Canal Economic Zone as a case study and employing a water–energy–food (WEF) nexus perspective, this study selected three key ESs—water yield, carbon sequestration, and food supply. The InVEST model, supply–demand index (SDI), Pearson correlation analysis, and four-quadrant model were integrated to systematically reveal the spatiotemporal patterns, correlation characteristics, and spatial matching of ES supply and demand from 2005 to 2020. Scale effects and appropriate management scales were clarified through municipal, county, and grid scale comparisons, and a comprehensive management zoning scheme was constructed using a “zoning–classification–grading” framework. The results show that water yield and food supply exhibited an overall increasing trend, while carbon sequestration supply remained stable. Demand for all three services showed continuous growth, with a spatial pattern of “high in the central area and low in the surrounding areas”, consistent with population and economic agglomerations. The county scale was the most effective at capturing local supply–demand characteristics. A “zoning–classification–grading” spatial governance system was constructed based on dominant functions, supply–demand status, and control priority. This study can provide a scientific basis for territorial spatial planning and integrated ecosystem management in the Pinglu Canal Economic Zone and similar regions. Full article

Dissolved organic matter (DOM) plays a central role in estuarine carbon cycling and exhibits dynamically coupled interactions with chlorophyll-a (Chl-a). Under increasing nutrient loads, elevated Chl-a concentrations and shifts in DOM composition serve as key indicators of eutrophication in estuarine aquatic ecosystems. Previous studies have mainly focused on the composition and fluorescence properties of DOM in rivers and lakes. Here, 84 water samples were collected from the Ganjiang River Estuary of Lake Poyang during wet, normal, and dry seasons across the mainstream, middle, and south branches. The average Chl-a concentration showed wet season (6.61 μg·L⁻¹) > normal season (4.54 μg·L⁻¹) > dry season (2.01 μg·L⁻¹). By employing EEM-PARAFAC, five fluorescent components were identified, including C1, C2, C3, C4, and C5. Notably, microbial humic-like substances remained consistently high during the wet season. Two-dimensional correlation spectroscopy was further employed to evaluate sequential changes in DOM components, while a moving window was used to identify temporal variation characteristics. Based on Noda’s rules, the DOM response sequence was identified as C3→C2→C1→C4→C5. Kernel PCA showed that the variable cluster represented by PC1, which consisted of organic pollutants and nutrients, co-varied negatively with Chl-a, whereas the PC2 cluster, representing biogenic organic matter, co-varied positively with Chl-a. Moreover, partial least squares path modeling showed that humic-like and tryptophan-like substances were positively correlated with Chl-a, with the path coefficients of 0.47 and 0.19, respectively. These findings revealed the interaction patterns between DOM components and Chl-a at the river-lake confluence zone, thereby enhancing our understanding of the factors influencing the spatio-temporal variations in Chl-a concentration, and further providing a guide for the control of algal blooms. Full article

Legume–grass mixtures are widely used to improve productivity and soil quality in alpine grasslands; however, their effects on soil fungal communities and the underlying mechanisms remain unclear. In this study, a two-factor field experiment (species richness (three, four, and five species) × legume–grass ratio (4:6, 3:7 and 2:8)) was conducted in an alpine artificial grassland on the Qinghai–Tibetan Plateau. Soil fungal communities were assessed using high-throughput sequencing combined with multivariate analyses. The results showed that Ascomycota, Mortierellomycota, and Basidiomycota were the dominant fungal phyla. Both species composition and seeding ratio significantly influenced fungal community structure and α-diversity primarily through indirect pathways mediated by plant community characteristics and soil properties. Plant height and soil total phosphorus (TP) were identified as key drivers of fungal α-diversity. Specifically, the four-species mixture (Z2) at a 3:7 legume–grass ratio resulted in relatively higher and more stable aboveground biomass and improved soil nutrient status, whereas increasing species richness to five species did not further enhance these benefits. Overall, our findings indicate that optimizing species composition and legume–grass ratio, rather than simply increasing species richness, is more effective for regulating soil fungal diversity and ecosystem function. Full article

Marine ecosystem integrity is paramount to global stability. With the advancement of industrialization, various types of waste are discharged into the ocean, accumulating through the food chain and ultimately threatening human health and the global climate environment. To achieve precise and efficient cleanup of marine debris, traceability is essential, with detection and classification serving as critical steps. To address the issues of missed detection and occlusion caused by the irregular shapes of marine debris due to water pressure or structural characteristics, as well as the coexistence of multi-scale objects resulting from aggregation and shooting angles, this study proposes the MD-YOLO model based on the YOLOv11L architecture. Firstly, a deformable attention mechanism is introduced in the neck network to achieve dynamic sampling and precise localization of targets with imbalanced aspect ratios. Secondly, a context-aware multi-scale feature fusion module is embedded in the backbone network to effectively mitigate the issue of missed detection of small targets when objects of different sizes coexist. Finally, a cooperative spatial-channel attention mechanism is designed in the detection head to enhance the feature representation capability in visible regions and infer occluded areas, thereby significantly suppressing occlusion interference. Experiments conducted on a self-constructed dataset containing 5095 images demonstrate that the proposed method achieves 86.7% in mAP@0.5, 67.6% in mAP@0.5:0.95, and an F1 score of 0.83, significantly outperforming comparative methods. This study provides key technical support for the effective traceability of marine debris. Full article

Driven by the rapid proliferation of generative artificial intelligence, the computing power industry is undergoing a paradigm shift from traditional linear supply chains toward complex, interdependent innovation ecosystems. This study investigates the evolutionary dynamics of the computing power ecosystem, specifically examining the strategic interplay between antitrust regulation and vertical integration. We construct a tripartite evolutionary game framework involving the government regulators, leading computing power incumbents, and downstream AI innovators. By deriving evolutionarily stable strategies, we analyze the underlying mechanisms of system transitions and employ numerical simulations to explore key parametric sensitivities. The theoretical analysis suggests that the evolution of the AI computing power innovation ecosystem manifests distinct stage-based progressions and threshold-driven bifurcation characteristics—potentially transitioning from an initial efficiency-based state of “natural monopoly and passive dependence” during the industry’s emergence, through transitionary states such as the “comfort zone trap” or “regulatory stalemate” during the expansion phase, and ultimately converging toward a mature configuration of “co-opetition and endogenous growth.” The model suggests that downstream AI firms may benefit from advancing vertical integration, achieving hardware–software co-optimization through self-developed domain-specific architectures, The analysis further implies that the leading computing power firm could strengthen its ecological niche by opening its underlying interfaces and software stacks to maintain its ecological niche as the industry cornerstone in integrated form. For the government, it is necessary to establish precise dynamic intervention and orderly exit mechanisms. Full article