Winter wheat is the main cereal crop in Northern China, and excessive nitrogen (N) fertilization and irrigation are employed in recent years to ensure a high grain yield. A high amount of N was lost via leaching, which exacerbated the risk of non-point source pollution and further increased the resource waste. It is highly necessary to clarify the characteristics and influencing factors of N leaching loss during the winter wheat season in the region. The literature on N leaching loss from the winter wheat production in Northern China, published from 2000 to 2023 was screened, and linear, multiple-factor regression models, as well as random forest and XGBoost models were established in the study. The research showed that the N leaching during the winter wheat season was mainly affected by the fertilizer rate and irrigation water, as well as soil properties (pH, clay and sand content), and was effectively inhibited by crop straw incorporation. Multiple variable combinations were constructed based on the results of importance analysis and stepwise regression. Grid search method, Bayesian and the combination of Bayesian and Early stopping were used to optimize the model parameters. The models constructed through Random Forest, based on all influential variables and based on the influential variables screened by stepwise, had the R² of 0.628 and 0.708, respectively, and the R² for the corresponding models constructed through XGBoost were 0.745 and 0.722, respectively. This indicates that the prediction effects of N leaching based on Random Forest and XGBoost were much better than the linear and multiple-factor regression models. The influence of multiple factors on N leaching was comprehensively considered in the machine learning models, and the effects of prediction were better when choosing the influential variables screened by empirical statistical methods as independent variables. The results of this study can provide technical support for reducing the N leaching in the winter wheat production in Northern China.

To investigate the impact of phosphorus input on phosphorus output in the Three Gorges Reservoir Area, this study utilized the Net Anthropogenic Phosphorus Input (NAPI) model and the improved Export Coefficient Model (ECM) to analyze the spatiotemporal characteristics of phosphorus input and output from 2006 to 2021, as well as their response relationship. The results showed that the annual NAPI value initially increased and then decreased, with a peak in 2015. The distribution of NAPI values exhibited spatial clustering among counties, with phosphorus fertilizers contributing the most to NAPI, averaging 64.42% annually. Total phosphorus (TP) output fluctuated around 2500 tons per year with a slowly increasing trend, and the areas with high TP values shifted from the northeastern to the southwestern parts of the reservoir area. Dryland contributed the most to TP, with an annual average of 41.25%. There was a positive correlation between TP and NAPI, with the phosphorus input from human food and animal feed (P_im) having the greatest overall impact on TP, followed by non-food phosphorus input (P_nf) and phosphorus fertilizer input (P_fer). P_im was found to generate more TP per unit than P_nf and P_fer. The phosphorus output rate ranged from 1.18% to 2.26%, with an annual average of 1.78%. The proportion of P_im had the greatest influence on the phosphorus output rate, followed by the proportion of P_nf, with the output rate increasing as the proportions of P_im and P_nf increased. In contrast, the proportion of P_fer was negatively correlated with the phosphorus output rate. P_im posed the greatest threat to potential regional phosphorus pollution risks. This study provides scientific references for water environment management in the Three Gorges Reservoir Area.

This research increases the accuracy of Net Primary Productivity (NPP) estimation in the CASA (Carnegie-Ames-Stanford Approach) model by refining the calculation methods for solar radiation parameters and water stress coefficients. Based on the improvement, correlation and trend analysis of NPP and meteorological variables were carried out.Following model optimization, the correlation between NPP and field observation data improved to 0.62. From 2001 to 2022, the annual average NPP in Jiangxi Province increased steadily, with the average value exceeding 1000gC/(m²⋅a). The monthly NPP values were in the following seasonal order: autumn > summer > winter > spring, with July having the highest value. The highest and lowest annual NPP values were observed in 2018 and 2010, respectively. Trend analysis and correlation facts show that, despite a decline in solar radiation from 2001 to 2022, NPP changes were not considerably impacted. A least-squares regression model revealed that NPP increased with rising temperature and decreased with decreasing sun radiation. Despite recent increases in extreme events (2019~2022), there has been no notable decrease in NPP levels.

This study used a meta-analysis approach to examine the distribution of three polycyclic aromatic hydrocarbons (Phe, Pyr and BbF) in the surface water of the world's seas as well as the factors that influence them. According to the findings, the Pacific Ocean had significantly greater concentrations of Phe, Pyr and BbF (16.885, 15.787, and 0.642ng/L) than the other oceans. These concentrations were also significantly linked with salinity, temperature, latitude, distance from coast, and chlorophyll. According to the findings, energy consumption and oceanic PAHs had a substantial and positive correlation (P<0.05). The distribution pattern of PAHs in the world's oceans is shown by this study, which offers a scientific foundation for the development of practical methods for the prevention and management of marine pollution.

The tolerance to cyanobacterial blooms and the need for ecological safety vary spatially across different areas of lake and reservoir water sources (e.g., intake areas, lake/reservoir zones, bay areas), which requires more precise selection and application of emergency response technologies. Currently, there is a wide range of emergency response technologies available for cyanobacterial blooms, but selecting efficient and safe technologies that are tailored to the specific scenarios of lake and reservoir water sources presents a technical challenge for emergency responders. This study first details the theoretical foundations of current emergency response technologies for cyanobacterial blooms, focusing on three main aspects: rapid algae-water separation, environmental factor regulation, and physiological growth inhibition, providing a theoretical basis for technology application. Secondly, based on spatial heterogeneity, the study categorizes different treatment areas within lake and reservoir water sources: interception, skimming, filtration, and clear water dispatching for highly sensitive intake areas; aeration, pressurized algae control, ultrasonic, flotation, and magnetic separation technologies for lake/reservoir zones; and flocculation, modified clay, chemical oxidation, photocatalytic oxidation, allelopathic plants, and microbial algae control for bay areas. Finally, the study comprehensively compares the technical requirements, advantages, duration of effectiveness, and application costs of these technologies in different water areas, providing a reference for the selection and development of emergency response technologies for cyanobacterial blooms in lake and reservoir water sources.

We conducted a seasonal survey on phytoplankton and environmental factors in Yilong Lake from summer, 2020 to spring,2021 to uncover the seasonal pattern of phytoplankton community structure and biomass, and further identify the driving forces of bottom-up and zooplankton’s top-down effect in mediating phytoplankton variations through multivariate analysis. The results showed that the phytoplankton’s biomass in Yilong Lake ranged from 7.12mg/L to 66.07mg/L, with the highest value in September and the lowest value in December. The phytoplankton community was dominated by Cyanophyta, which contributed to 42.91% to 95.67% of total phytoplankton biomass. Raphidiopsis raciborskii, absolutely predominated during the investigation period(23.43%~84.30%), reflecting its strong competitive advantages. The ANOSIM and Kruskal-Wallis analyses indicated that there existed significant temporal fluctuation in phytoplankton community structure and biomass(P<0.05). The Spearman’s correlation analysis revealed that the biomass of phytoplankton, Cyanophyta and R. raciborskii were all positively related to total phosphorus(P<0.05), total nitrogen and water temperature and negatively related to transparency and ammonia nitrogen(P<0.05), but had no significant correlation with zooplankton biomass(P>0.05). The RDA results showed that total phosphorus, total nitrogen, silicate, water temperature and water depth were among the significant factors in driving phytoplankton community in Yilong Lake. The results of variation partitioning further revealed that the bottom-up effect (water temperature, nutrients and water depth) and top-down effect (zooplankton community) accounted for 20.30% and 0.20% of the total variance independently with a shared portion of 5.80%. Therefore, the bottom-up effect had a greater impact on variations in phytoplankton community than the top-down effect by zooplankton in Yilong Lake. This may be because zooplankton in Yilong Lake had small mean body length (ZB/ZA:0.0019±0.0018) and relatively low biomass (0.56±0.39mg/L), and thus resulting in the weak grazing pressure on algae (ZB/PB:0.0303±0.0271). Our results will provide scientific data for the ecological assessment and integrated watershed management of Yilong Lake.

We established an assessment framework for coastal ecological resilience and conducted a regional evaluation in the area of Shenzhen as a case study. The STIRPAT model was employed to quantify the socioeconomic factors affecting coastal ecological resilience and identify key influencing factors and the extent of their impact. Strategies for coastal zone protection and restoration were also proposed. The results showed that, in 2021, the Shenzhen's coastal ecological resilience score ranged from 8.97 to 92.12, indicating a distinct spatial difference between the eastern and western parts, with a higher ecological resilience in the former. The spatial pattern of coastal ecological resilience was closely associated with the underlying geographical characteristics and urban developmental features of the area. The level of regional affluence was identified as a major negative factor impacting the resilience, followed by other factors such as reclaimed land area, environmental pollution, and population density. Conversely, a reduction in water consumption per unit of GDP showed a positive effect on coastal ecological resilience, suggesting that technological innovation and high-quality economic development can significantly enhance coastal ecological resilience. The results of this study provide a new method for studying ecological resilience in high-density urban coastal zones and a scientific basis for coastal zone management.

To efficiently remove nutrient salts in high salinity lakes, this study implemented a plant+microbial ditch at Daihai Lake. The nutrient removal efficiency, plant growth, and microbial community dynamics of this ecological ditch was investigated across different salinity gradients. Immobilizing Bacillus amyloliquefaciens on polyurethane sponge within the ditch could significantly promote the growth of plant, enhance the activity of antioxidant stress-related enzymes, and strengthen the ability of plants to absorb and assimilate nutrients. Addiing Bacillus amyloliquefaciens in the ditch could not make it become the absolute dominant genus. but it could improve the microbial community structure, increase the abundance of functional microorganisms involved in nitrogen and phosphorus removal, and enhance the water purification capacity of the ditch. Compared to ecological ditches with plant-only or microorganism-only, the integrated ecological ditch could achieve higher nutrient removal rates across different salinity concentrations. Specifically, over 70% TN, NH₄⁺-N, TP, and CODCr could be removed in the integrated ditch at 15g/L salinity. Compared plant-only ditch, the activities of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) in plants were increased 33.7%, 43.6%, and 38.7%, respectively, in planted+microbial ditch at 15.0g/L salinity.

To alleviate the harmful effects of salinization on soil micro-ecological environments, this study investigates the restorative effects of a dual microbial system on saline-alkaline soil. The experiment used the tomato variety 'Zhongshu No. 4'(Lycopersicon esculentum L.) as the test plant and tested arbuscular mycorrhizal fungi (AMF) and Bacillus subtilis as inoculants. Inoculations were carried out using pot culture and root drenching methods, with saline-alkaline solutions at concentrations of 15mmol/L (SA₁), 75mmol/L (SA₂), and 150mmol/L (SA₃), to assess the effects of exogenous AMF and B. subtilis on the soil micro-ecological environment under saline-alkaline stress. Results showed that both AMF+B. subtilis sterilisation solution (Gm) and AMF steriliser+B. subtilis (B) moderately improved the saline-alkaline soil conditions. However, the dual treatment (Gm+B)demonstrated the most pronounced remediation effect. Under the dual inoculation, plant height increased significantly, by 57.52%compared to the blank control (CK₁) and by 58.04% compared to the inactivated inoculant control (CK₂). In the Gm+B group, soil organic matter increased by a maximum of 47.15% compared to CK₁, exceeding the growth observed in the Gm and B treatments alone. Significant increases in soil total nitrogen (N), available phosphorus (P), and available potassium (K) were observed, with improvements of 38.85% (SA₂+Gm+B), 465.20% (SA₁+Gm+B), and 157.75% (SA₃+Gm+B), respectively. Soil enzyme activities, including urease, sucrase, and catalase, were markedly enhanced under dual treatment, with increases of 63.64% (SA₂+Gm+B),209.63% (SA₃+Gm+B), and 45.26% (SA₃+Gm+B), respectively. Soil bacterial, fungal, and actinomycete populations increased to 1.93, 1.25, and 4.37times those of CK₁under SA₂+Gm+B and SA₃+Gm+B, indicating a substantial improvement in the rhizosphere microbial community structure. The synergistic interaction of AMF and B. subtilis reduced soil pH and electrical conductivity while significantly increasing soil moisture content. N, P, and K levels showed an upward trend, and AMF colonization rates were enhanced, effectively mitigating the negative effects of saline-alkaline soil on enzyme activities and promoting root and stem development. Therefore, the AMF-B. subtilis dual microbial system demonstrates strong potential for effective ecological restoration of saline-alkaline soil microenvironments.

The practical needs of specific regions in coordinating various ecosystem services could be effectively addressed through ecological zoning, guided by the spatial and temporal distribution characteristics of these services, as well as their trade-offs/synergies. Sustainable development in the study area was promoted by formulating corresponding management strategies according to the specific ecological attributes of different ecosystem services. The identification of ecological functional zones based on the trade-offs/synergies of ecosystem services offers a precise and differentiated regulatory framework for ecological function restoration and management. Taking Anhui Province as an example, the InVEST model was employed to assess and analyze the spatial-temporal evolution and trade-offs/synergies of typical ecosystem services in the region from 2000 to 2020. Ecosystem service clusters were extracted through the SOM (Self-Organizing Map) model to define ecological functional zones. The PLUS model was then applied to simulate the evolution trend of integrated ecosystem services by 2050, leading to the proposal of regulatory strategies. Key findings include: ① From 2000 to 2020, water production services and soil conservation in Anhui Province showed continuous improvement, whereas carbon sequestration services, habitat quality, and food supply experienced a decline. The comprehensive ecosystem service index revealed a spatial pattern of "high in the south and low in the north". Approximately 50% of the study area was capable of providing two types of ecosystem services, while only about 11% of the area supported all ecological services. Areas unable to provide ecosystem services increased from 0.07% in 2000 to 4.85% in 2020. ② Strong synergistic effects were observed among water production, carbon sequestration, habitat quality, and soil conservation sevices. Conversely, a distinct trade-off was evident between the water production and food production services. ③ Based on this findings, four clusters of ecosystem services were identified: the food supply cluster, ecological conservation cluster, human living environment cluster, and forest protection cluster. Consequently, Anhui Province was divided into agricultural ecological zones, ecological conservation zones, urban development zones, and forest ecological protection zones, each with tailored regulatory strategies.④Multi-scenario simulation analyses revealed that under the ecological protection scenario, habitat quality and carbon sequestration services were optimized. Food production reached its peak under the arable land protection scenario. The ecological protection scenario showed significant improvements in overall ecosystem services. The research outcomes offer a scientific basis for promoting sustainable development and optimizing ecological environment in Anhui Province.