Quantitative impacts of meteorology and emissions on the long-term trend of O3 in the Yangtze River Delta (YRD), China from 2015 to 2022.

Extensive spatiotemporal analyses of long-trend surface ozone in the Yangtze River Delta (YRD) region and its meteorology-related and emission-related have not been systematically analyzed. In this study, by using 8-year-long (2015-2022) surface ozone observation data, we attempted to reveal the variation of multiple timescale components using the Kolmogorov-Zurbenko filter, and the effects of meteorology and emissions were quantitatively isolated using multiple linear regression with meteorological variables. The results showed that the short-term, seasonal, and long-term components accounted for daily maximum 8-hr average O3 (O3-8 hr) concentration, 46.4%, 45.9%, and 1.0%, respectively. The meteorological impacts account for an average of 71.8% of O3-8 hr, and the YRD's eastern and northern sections are meteorology-sensitive areas. Based on statistical analysis technology with empirical orthogonal function, the contribution of meteorology, local emission, and transport in the long-term component of O3-8 hr were 0.21%, 0.12%, and 0.6%, respectively. The spatiotemporal analysis indicated that a distinct decreasing spatial pattern could be observed from coastal cities towards the northwest, influenced by the monsoon and synoptic conditions. The central urban agglomeration north and south of the YRD was particularly susceptible to local pollution. Among the cities studied, Shanghai, Anqing, and Xuancheng, located at similar latitudes, were significantly impacted by atmospheric transmission-the contribution of Shanghai, the maximum accounting for 3.6%.

Phosphorus prediction in the middle reaches of the Yangtze river based on GRA-CEEMDAN-CNLSTM-DBO.

Accurate and rapid prediction of water quality is crucial for the protection of aquatic ecosystems. This study aims to enhance the prediction of total phosphorus (TP) concentrations in the middle reaches of the Yangtze River by integrating advanced modeling techniques. Using operational and discharge data from the Three Gorges Reservoir (TGR), along with water quality parameters from downstream sections, we used Grey Relational Analysis (GRA) to rank the factors contributing to TP concentrations. The analysis identified turbidity, permanganate index (CODMn), total nitrogen (TN), water temperature, chlorophyll a, upstream water level variation, and discharge from the Three Gorges Dam (TGD) as the top contributors. Subsequently, a coupled neural network model was established, incorporating these key contributors, to predict TP concentrations under the dynamic water level control during flood periods in the TGR. The proposed GRA-CEEMDAN-CN1D-LSTM-DBO model was compared with conventional models, including BP, LSTM, and GRU. The results indicated that the GRA-CEEMDAN-CN1D-LSTM-DBO model significantly outperformed the others, achieving a correlation coefficient (R) of 0.784 and a root mean square error (RMSE) of 0.004, compared to 0.58 (R) and 0.007 (RMSE) for the LSTM model, 0.576 (R) and 0.007 (RMSE) for the BP model, and 0.623 (R) and 0.006 (RMSE) for the GRU model. The model's accuracy and applicability further validated in two sections: YC (Yunchi) in Yichang City and LK (Liukou) in Jingzhou City, where it performed satisfactorily in predicting TP in YC (R = 0.776, RMSE = 0.007) and LK (R = 0.718, RMSE = 0.007). Additionally, deep learning analysis revealed that as the distance away from dam increased, prediction accuracy gradually decreased, indicating a reduced impact of TGR operations on downstream TP concentrations. In conclusion, the GRA-CEEMDAN-CN1D-LSTM-DBO model demonstrates superior performance in predicting TP concentration in the middle reaches of the Yangtze River, offering valuable insights for dynamic water level control during flood seasons and contributing of smart to the advancement of water management in the Yangtze River.

Pollution loads in the middle-lower Yangtze river by coupling water quality models with machine learning.

Pollution control and environmental protection of the Yangtze River have received major attention in China. However, modeling the river's pollution load remains challenging due to limited monitoring and unclear spatiotemporal distribution of pollution sources. Specifically, anthropogenic activities' contribution to the pollution have been underestimated in previous research. Here, we coupled a hydrodynamic-based water quality (HWQ) model with a machine learning (ML) model, namely attention-based Gated Recurrent Unit, to decipher the daily pollution loads (i.e., chemical oxygen demand, COD; total phosphorus, TP) and their sources in the Middle-Lower Yangtze River from 2014 to 2018. The coupled HWQ-ML model outperformed the standalone ML model with KGE values ranging 0.77-0.91 for COD and 0.47-0.64 for TP, while also reducing parameter uncertainty. When examining the relative contributions at the Middle Yangtze River Hankou cross-section, we observed that the main stream and tributaries, lateral anthropogenic discharges, and parameter uncertainty contributed 15, 66, and 19% to COD, and 58, 35, and 7% to TP, respectively. For the Lower Yangtze River Datong cross-section, the contributions were 6, 69, and 25% for COD and 41, 42, and 17% for TP. According to the attention weights of the coupled model, the primary drivers of lateral anthropogenic pollution sources, in descending order of importance, were temperature, date, and precipitation, reflecting seasonal pollution discharge, industrial effluent, and first flush effect and combined sewer overflows, respectively. This study emphasizes the synergy between physical modeling and machine learning, offering new insights into pollution load dynamics in the Yangtze River.

Influence of extreme 2022 heatwave on megacities' anthropogenic CO2 emissions in lower-middle reaches of the Yangtze River.

An unprecedented heatwave hit the Yangtze River Basin (YRB) in August 2022. We analyzed changes of anthropogenic CO2 emissions in 8 megacities over lower-middle reaches of the YRB, using a near-real-time gridded daily CO2 emissions dataset. We suggest that the predominant sources of CO2 emissions in these 8 megacities are from the power and industrial sectors. In comparison to the average emissions for August in 2020 and 2021, the heatwave event led to a total increase in power sector emissions of approximately 2.70 Mt CO2, potentially due to the increase in urban cooling demand. Suzhou experienced the largest increase, with a rise of 1.12 Mt CO2 (12.88 %). Importantly, we observed that changes in daily power emissions exhibited strong linear relationships with temperatures during the heatwave, albeit varying sensitivities across different megacities (with an average of 0.0076 ± 0.0075 Mt d-1 °C-1). Conversely, we find that industrial emissions decreased by a total of 8.45 Mt CO2, with Shanghai seeing the largest decrease of 4.71 Mt CO2, while Hangzhou experienced the largest relative decrease (-21.22 %). It is noteworthy that the majority of megacities rebounded in industrial emissions following the conclusion of the heatwave. We convincingly suggest a tight linkage between the reductions in industrial emissions and China's policy to ensure household power supply. Overall, the reduction in industrial emissions offset the increase in power sector emissions, resulting in weaker emissions for majority of megacities during the heatwave. Despite remaining uncertainties in the emissions data, our study may offer valuable insights into the complexities of anthropogenic CO2 emissions in megacities amidst frequent summer heatwaves intensified by greenhouse warming.

Analysis of dynamic evolution characteristics and driving factors of regional synergistic effect of reducing carbon and saving water: the case of Yangtze River Delta Urban Agglomerations, China.

Carbon emissions and water consumption are both important factors affecting sustainable development. Therefore, it is necessary to put them in the same research framework and investigate the synergy. In this study, the dynamic evolution characteristics of the synergistic effect of reducing carbon and saving water (RCSW) were analyzed. Then, taking the Yangtze River Delta Urban Agglomerations (YRDUA) as the research object, the influencing factors and specific paths of the synergistic effect were clarified. The results showed that the low-carbon emission efficiency (LCEE) had a stable synergy with the intensive utilization efficiency of water resources (IUEWR) in the YRDUA. Government financial expenditure, actual use of foreign capital, and population density were the most significant driving forces for the synergistic effect of RCSW, with q values of 0.561, 0.363, and 0.240, respectively. In addition, most of the interactions of the driving factors were nonlinear enhancement and double-factor enhancement.

Spatial and temporal changes of ecosystem service value and its influencing mechanism in the Yangtze River Delta urban agglomeration.

As the mainstream and trend of urban development in China, deeply exploring the spatiotemporal patterns and influencing mechanisms of ecosystem service value in the Yangtze River Delta urban agglomeration is of great significance for achieving sustainable development goals in urban agglomerations. This paper uses the normalized difference vegetation index and net primary productivity as dynamic adjustment factors to measure the ecosystem service value of the Yangtze River Delta urban agglomeration and analyze its spatiotemporal evolution characteristics. Furthermore, a panel quantile regression model is constructed to explore the response differences of ecosystem service value at different levels to various influencing factors. The results show that: (1) From 2006 to 2020, the ecosystem service value of the Yangtze River Delta urban agglomeration decreased by 37.086 billion yuan, with high-value areas mainly concentrated in the southern part of the urban agglomeration. (2) The value structure of various land type ecosystems and primary ecosystem sub-services in the Yangtze River Delta urban agglomeration is stable. (3) The number of grid units with reduced ecosystem service value is continuously increasing, mainly distributed in the eastern coastal areas. (4) The degree of interference of various types of land on ecosystem service value varies, and the response of ecosystem service value at different levels to the same influencing factor also shows heterogeneity. In summary, exploring the spatiotemporal patterns of ecosystem service value in the Yangtze River Delta urban agglomeration and analyzing its influencing mechanisms is conducive to adjusting the intensity of human utilization and protection methods of ecosystems, which is of great significance for enhancing the value of ecosystem products in urban agglomerations.

Components of dissolved organic carbon in relation to environmental factors in lakes along an altitudinal gradient in central China.

Dissolved organic carbon (DOC) is an important organic substance that affects biogeochemical processes and underwater light conditions in aquatic ecosystems. To explore altitudinal variations in DOC components and water quality, 66 surface water samples were collected along an altitudinal gradient (10-1857 m) in three regions of central China, including a montane region (Enshi Prefecture) and two floodplain regions (Dongting Lake Basin and Wuhan City). DOC components were measured using a three-dimensional excitation-emission matrix (3D-EEM) fluorescence spectroscopy, in conjunction with fluorescence regional integration (FRI) and fluorescence indices. Generally, lakes at high elevations (Enshi Prefecture) had higher DOC concentrations (a mean value of 6.43 mg L-1) than floodplain lakes in Dongting Basin (4.51 mg L-1) and Wuhan City (3.89 mg L-1). Fluorescence index (FI, a range of 1.37-1.92) and biological index (BIX, a range of 0.47-0.74) indicated that DOC mainly originated from allochthonous sources in the three regions. Enshi Prefecture had relatively lower FI and BIX values, suggestive of a larger contribution of allochthonous carbon in this montane region in comparison with the floodplain regions. Humic-like substances were more abundant than other four fluorescent components, including tyrosine-like, tryptophan-like, fulvic acid-like, microbial-like substances. Spearman rank correlation analyses showed that tryptophane-like substances were positively correlated with K+, Mg2+, and Na+, while humic-like substances were negatively correlated with these cations. Taken together, the results can improve our understanding on altitudinal variations in DOC components and potential driving forces.

Multi-machine learning methods to predict spatial variation characteristics of total nitrogen at watershed scale: Evidences from the largest watershed (Yangtze River Watershed), Asian.

Nitrogen pollution has emerged as a significant threat to the health of global river systems, garnering considerable attention. However, numerous challenges persist in understanding the characteristics and predicting the spatial changes of total nitrogen (TN) at the catchment scale. We leveraged data from 530 monitoring sections to calculate a land-use composite index and perform statistical analyses to explore the primary factors influencing nitrogen enrichment in the Yangtze River Watershed. We developed three machine learning models to forecast future TN concentrations at monitoring points. Our results showed that agricultural activities and rainfall were the primary drivers of monthly variations in TN concentrations. The upstream region of the watershed exhibited larger variations in TN concentrations (0.097 to 11.099 mg/L), significantly higher than the middle and downstream areas (0.348 to 6.844 mg/L). Microbial-mediated organic matter decomposition in sediment and changes in land-use were identified as key contributors to regional differences in nitrogen enrichment. Potential nitrogen sources include sediment release, urban sewage, and agricultural fertilization. Random Forest model achieved a prediction accuracy of 77.6 %, surpassing the BP and LSTM models. We identified 37 high-risk areas of nitrogen enrichment, concentrated in the Chengdu-Chongqing, Yunnan-Central urban cluster, and the Chaohu Lake sub-watershed. Increased urban land-use and industrial inputs primarily influenced nitrogen enrichment in the upstream area, while agricultural inputs were the main drivers in the middle and downstream regions. Our multi-machine learning models identified the relationship between TN and influencing factors, providing a reliable method for assessing nitrogen enrichment risk in the watershed.

Molecular composition limits the reaction kinetics of riverine dissolved organic matter decomposition.

The bioavailability and degradation of riverine dissolved organic matter (DOM) play crucial roles in greenhouse gas emissions; however, studies on the kinetic decomposition of fluvial DOM remain scarce. In this study, the decomposition kinetics of dissolved organic carbon (DOC) were characterized using the reactivity continuum model through 28-day bio-incubation experiments with water samples from the Yangtze River. The relationship between DOM composition and decomposition kinetics was analyzed using optical and molecular characterization combined with apparent decay coefficients. Our results revealed that DOM compounds rich in nitrogen and sulfur were predominantly removed, exhibiting a transition from an unsaturated to a saturated state following microbial degradation. These heteroatomic compounds, which constituted 75.61 % of the DOM compounds positively correlated with the decay coefficient k0, underwent preferential degradation in the early stages of bio-incubation due to their higher bioavailability. Additionally, we observed that S-containing fractions with high molecular weight values (MW > 400 Da) may be associated with larger reactivity grades. This study underscored the complex interplay between DOM composition and its kinetic decomposition in river ecosystems, providing further support for the significance of molecular composition in large river DOM as crucial factors affecting decomposition.

[Regional Difference and Spatial Convergence of Land Use Carbon Emissions in Three Urban Agglomerations of Yangtze River Economic Belt].

It is of great significance to explore the regional differences of land use carbon emission （LUCE） in the Yangtze River Economic Belt and the path of coordinated emission reduction for regional sustainable development. Based on the LUCE estimation method, this study scientifically calculated the LUCE of the three major urban agglomerations of the Yangtze River Economic Belt （Yangtze River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing urban agglomeration） from 2010 to 2020. Kernel density estimation and the spatial convergence model were used to study the dynamic evolution, regional differences, and convergence characteristics of LUCE. The results showed that： ① The carbon absorption of forest land, water areas, grassland, and unused land were relatively small in terms of carbon emissions from cultivated land and construction land. The carbon emission of construction land increased gradually, whereas the carbon absorption of four carbon sinks fluctuated little during the study period. ② The core density curves of different urban agglomerations showed different distribution patterns, extensibility, and polarization characteristics but generally tended to be balanced. ③ From 2010 to 2020, the LUCE of the Yangtze River Economic Belt as a whole showed the spatio-temporal characteristics of increasing first and then decreasing and high in the east and low in the west. The LUCE of the central cities of the three urban agglomerations were at the highest level steadily, and stable coupling mechanisms had not been established between the economic development level and the ecological environment. ④ The LUCE of the three urban agglomerations in the Yangtze River Economic Belt all had absolute ß convergence and also had conditional ß convergence under the model control variables such as economic development level, urbanization level, industrial structure, population density, and environmental regulation, etc., and the conditional convergence speed was greater than the absolute convergence speed in each region. The convergence speed of the Yangtze River Delta urban agglomeration was the slowest. The above conclusions provide support for the coordinated emission reduction path of the three urban agglomerations in the Yangtze River Economic Belt and are also conducive to actively and steadily promoting the realization of the goals of carbon peak and carbon neutralization.

[Spatiotemporal Evolution Characteristics of Carbon Sources and Carbon Sinks and Carbon Balance Zoning in the Yangtze River Delta Region].

Mastering the spatiotemporal evolution laws of carbon sources and sinks is of great significance to promote the coordinated development of regional low-carbon, improve the science of carbon reduction and sink increase policies, and realize the goal of "double carbon." Taking 41 cities in the Yangtze River Delta Region as the research object, this study analyzed the spatiotemporal evolution characteristics of carbon sources and sinks in the Yangtze River Delta Region from 2000 to 2020 and conducted the carbon balance zoning. The results were as follows： ① The carbon emissions increased rapidly in the Yangtze River Delta Region from 2000 to 2011 but with some fluctuations after 2011. Carbon sinks increased slowly in the Yangtze River Delta Region from 2000 to 2020. The regional differences in carbon emissions and carbon sinks were significant, and the spatial pattern was relatively stable. ② The carbon compensation rate in the Yangtze River Delta Region showed a downward trend, and the carbon productivity, energy utilization efficiency, and carbon ecological support capacity were constantly enhanced. Interregional differences were the main source of carbon compensation rate in the Yangtze River Delta Region. Both the carbon compensation rate and carbon ecological support coefficient showed a spatial pattern of "high in the west and low in the east, high in the south and low in the north." The areas with high carbon economy contributive coefficient were concentrated in the central and southern areas of the Yangtze River Delta regions, and the areas with low carbon economy contributive coefficient were concentrated in Anhui Province. ③ Based on the carbon economy contributive coefficient and the carbon ecological support coefficient, cities in the Yangtze River Delta Region were classified into low-carbon maintenance areas, economic development areas, carbon sink development areas, and comprehensive optimization areas. Recommendations were proposed for each category of cities in order to promote the coordinated development of regional low-carbon and realize the goal of "double carbon".

Assessment of the influence of levees along Yangtze River on Oncomelania hupensis, the intermediate host of Schistosoma japonicum.

BACKGROUND: Oncomelania hupensis is the exclusive intermediate host of Schistosoma japonicum in China. Snail control is an essential component of schistosomiasis elimination programme. With 70 years of continuous efforts, the range of O. hupensis had reduced significantly, but slowed down in last decades. A large number of levees against flooding were constructed along Yangtze River and its affiliated lakes in the middle and lower reaches, which influenced the hydrology and ecology in the alluvial plains. The purpose of this study was to assess the impact of levees on the distribution of O. hupensis in the middle and lower reaches of the Yangtze River. METHODS: The snail habitats were digitalised by hand-held GPS system. The years for discovery and elimination of snail habitats were extracted from historical records. The accumulated snail-infested range for each habitat was calculated on the basis of annual reports. The current distribution of O. hupensis was determined by systematic and environmental sampling. The geographical distribution of levees was obtained from satellite imagery. To assess the impact of levees, the data pertaining to O. hupensis were divided into two parts: inside and outside the Yangtze River. Joinpoint regression was utilised to divide the study time span and further characterise the regression in each period. The 5-year-period moving averages of eliminated area infested by snails were calculated for the habitats inside and outside Yangtze River. The moving routes of corresponding geographical median centres were simulated in ArcGIS. Hotspot analysis was used to determine the areas with statistical significance clustering of O. hupensis density. RESULTS: Three periods were identified according to Joinpoint regression both inside and outside Yangtze River. The area infested by O. hupensis increased in the first two periods. It decreased rapidly outside Yangtze River year over year after 1970, while that inside the Yangtze River did not change significantly. Furthermore, the latter was significantly higher than the former. It was observed that the present density of O. hupensis inside Yangtze River was lower than outside the Yangtze River. The median centre for eliminated ranges inside Yangtze River wavered between the east (lower reach) and the west (middle reach). In contrast, the median centre for eliminated ranges continuously moved from the east to the west. CONCLUSIONS: Our findings indicated that the levees had a considerable negative impact on the distribution of O. hupensis outside Yangtze River. Some hotspots observed in the irrigation areas need a sluice system at the inlet of branch for snail control. The major distribution of O. hupensis located in Hubei might be caused by severe waterlogging. The intensive surveillance should be implemented there. The biggest two freshwater lakes, the major endemic regions historically, were identified as cold spots. The long-term impact of Three Gorges Dam on the distribution of O. hupensis in the lakes should be monitored and evaluated.

The food security risks in the Yangtze River Delta of China associated with water scarcity, grain production, and grain trade.

Grain production consumes a large amount of water and is affected by the degree of water scarcity and participation in the grain trade in various regions. The grain trade has changed the food security risks in regions where grain exports and imports. Therefore, it is crucial to consider regional water scarcity to understand food security risks from the grain trade network. Here, we construct a new framework for measuring regional food security risks associated with water scarcity, grain production, and grain trade based on a cross-city grain trade network combined with virtual water flows to evaluate the regional food security risks in the Yangtze River Delta region (YRD) of China in 2017. The results show that under the current domestic grain trade pattern in China, the YRD and its four provincial-level administrative regions are in a net grain import state. The grain trade within the YRD is concentrated in exports from the two major grain-producing areas of Anhui and Jiangsu to Zhejiang and Shanghai, especially from northern Jiangsu to southeastern Zhejiang. The net import results of virtual blue water in most cities indicate that the YRD has shifted its water resource pressure to other grain exporting regions in China, with Shanghai and Zhejiang being the greatest beneficiaries. Extreme risk only exists in Shanghai, and severe and moderate risks are concentrated in Jiangsu. The current grain trade has reduced the overall food security risk in the YRD by 1.3 % but increased the risks in Shanghai and Zhejiang by 2.1 % and 0.8 % respectively. This study highlights the potential risks that excessive production of food in water-scarce areas in the grain trade system may bring to a stable food supply, providing useful information for a comprehensive understanding of the food and water security situation and for future trade-offs.

Thirty years of 3-D urbanization in the Yangtze River Delta, China.

Accurately capturing the urbanization process is essential for planning sustainable cities and realizing the United Nations Sustainable Development Goal 11. However, until recently, most of the studies on urban expansion in the world have focused on area growth but have little knowledge of height dynamics. This study mapped the spatial distribution of urban built-up areas (UBA) in the Yangtze River Delta (YRD), one of the most urbanized regions in China, to investigate the spatio-temporal evolution in both the horizontal and vertical directions from 1990 to 2020. We coupled and analyzed the horizontal and vertical urban expansion from the 3-D perspective and identified the dominant types. The results showed that 30 cities (73.17 % of the total number of cities) were increasing in the 3-D combined expansion intensity. The decreasing cities were mainly located in Anhui Province. Despite the increasing number of skyscrapers, horizontal growth has dominated urban expansion over the past three decades. The UBA area of the YRD has grown from 4,855.30 km2 to 44,447.15 km2, while the average building height has slowly decreased by 1.26 m. Significant unevenness and differences existed in horizontal and vertical expansions of varying provinces and cities. Our study can accurately grasp the 3-D urban expansion process in the YRD and could promote the efficient development and sustainable utilization of urban land resources in China and beyond.

Seasonal dynamics of intestinal microbiota in juvenile Chinese mitten crab (Eriocheir sinensis) in the Yangtze Estuary.

Introduction: In this study, the seasonal differences in the intestinal microbiota of Chinese mitten crab (Eriocheir sinensis) larvae were investigated at different sites in the intertidal zone of the Yangtze River Estuary. Methods: 16S rRNA high-throughput sequencing technology was used to compare and analyze the microbial community structure in the intestines of juvenile crab from different seasons. Results: The results showed that the main microbial phyla in all seasons and sites were Proteobacteria, Bacteroidetes, Firmicutes, and Actinobacteria, which accounted for 97.1% of the total microbiota. Composition analysis revealed that the relative abundance of Proteobacteria decreased from summer to winter at each station, whereas Bacteroidetes showed the opposite trend. Alpha diversity analysis showed that species richness increased from summer to winter at the upstream site (P < 0.05), but decreased at the downstream site (P < 0.05), with no significant differences observed in other comparisons. Biomarker species analysis showed that juvenile crab exhibited a more specialized microbial community in summer compared with autumn and winter. Co-occurrence network analysis revealed that microbial interaction network complexity was lower in autumn compared with summer and autumn. Functional prediction analysis showed that the microbial community only exhibited seasonal differences in amino acid biosynthesis, cofactor, prosthetic group, electron carrier, and vitamin biosynthesis, aromatic compound degradation, nucleotide and nucleoside degradation, and tricarboxylic acid cycle pathways. Discussion: The results indicated that the microbiota did not significantly differ among sites, and seasonal variation was a main factor influencing the differences in intestinal microbiota of Chinese mitten juvenile crab. Moreover, the microbial community was more complex in summer compared with autumn and winter.

Spatiotemporal Variations in Co-Occurrence Patterns of Planktonic Prokaryotic Microorganisms along the Yangtze River.

Bacteria and archaea are foundational life forms on Earth and play crucial roles in the development of our planet's biological hierarchy. Their interactions influence various aspects of life, including eukaryotic cell biology, molecular biology, and ecological dynamics. However, the coexistence network patterns of these microorganisms within natural river ecosystems, vital for nutrient cycling and environmental health, are not well understood. To address this knowledge gap, we systematically explored the non-random coexistence patterns of planktonic bacteria and archaea in the 6000-km stretch of the Yangtze River by using high-throughput sequencing technology. By analyzing the O/R ratio, representing the divergence between observed (O%) and random (R%) co-existence incidences, and the module composition, we found a preference of both bacteria and archaea for intradomain associations over interdomain associations. Seasons notably influenced the co-existence of bacteria and archaea, and archaea played a more crucial role in spring as evidenced by their predominant presence of interphyla co-existence and more species as keystone ones. The autumn network was characterized by a higher node or edge number, greater graph density, node degree, degree centralization, and nearest neighbor degree, indicating a more complex and interconnected structure. Landforms markedly affected microbial associations, with more complex networks and more core species found in plain and non-source areas. Distance-decay analysis suggested the importance of geographical distance in shaping bacteria and archaea co-existence patterns (more pronounced in spring). Natural, nutrient, and metal factors, including water temperature, NH4+-N, Fe, Al, and Ni were identified as crucial determinants shaping the co-occurrence patterns. Overall, these findings revealed the dynamics of prokaryotic taxa coexistence patterns in response to varying environmental conditions and further contributed to a broader understanding of microbial ecology in freshwater biogeochemical cycling.

Exploring the ecological security evaluation of water resources in the Yangtze River Basin under the background of ecological sustainable development.

The Yangtze River (hereafter referred to as the YZR), the largest river in China, is of paramount importance for ensuring water resource security. The Yangtze River Basin (hereafter referred to as the YRB) is one of the most densely populated areas in China, and complex human activities have a significant impact on the ecological security of water resources. Therefore, this paper employs theories related to ecological population evolution and the Driving Force-Pressure-State-Impact-Response (DPSIR) model to construct an indicator system for the ecological security of water resources in the YRB. The report evaluates the ecological security status of water resources in each province of the YRB from 2010 to 2019, clarifies the development trend of its water resource ecological security, and proposes corresponding strategies for regional ecological security and coordinated economic development. According to the results of the ecological population evolution competition model, the overall indicator of the ecological security of water resources in the YRB continues to improve, with the safety level increasing annually. Maintaining sound management of water resources in the YRB is crucial for sustainable socioeconomic development. To further promote the ecological security of water resources in the YRB and the coordinated development of the regional economy, this paper proposes policy suggestions such as promoting the continuous advancement of sustainable development projects, actively adjusting industrial structure, continuously enhancing public environmental awareness, and actively participating in international ecological construction and seeking cooperation among multiple departments.

Wastewater Discharge Transports Riverine Microplastics over Long Distances.

Wastewater discharge from wastewater treatment plants continuously pumps microplastics into rivers, yet their transport distances within these waterways remain unknown. Herein, we developed a conceptual framework by synthesizing the microplastic data from the Yangtze River Basin to evaluate its transport distances, quantifying a significant spatial dependence between large-scale wastewater discharge and riverine microplastics (p < 0.05). The presence of microplastics at a specific sampling site could be attributed to wastewater discharge within a large-scale range spanning >1000 km upstream, encompassing a substantial portion equivalent to one-third of the Yangtze River Basin. The dominance analysis indicated that the contribution of wastewater discharge in rivers with higher discharge (>100 m3/s) to riverine microplastic pollution exceeded 65% within the Yangtze River Basin. The spatial dependence framework of riverine microplastics on wastewater discharge advances our prior understanding of the prevention and control of riverine microplastics by demonstrating that such pollution is not limited to nearby environmental factors.

[Analysis of Regional Differences in Cadmium Ecological Risk in Surface Waters of the Yangtze River Basin].

This study primarily focused on the regional disparities in both water quality criteria and ecological risks attributed to cadmium presence within the surface waters of the Yangtze River Basin. In the initial phase, the long-term water quality criteria for cadmium were recalibrated in accordance with the guidelines outlined in China's "Water Quality Criteria for Freshwater Aquatic Organisms-Cadmium," accounting for the prevalent hardness distribution within the Yangtze River Basin's surface water. Subsequently, a more refined revision was undertaken considering the specific characteristics of the species residing within the Yangtze River Basin. This undertaking led to a comprehensive interpretation of the regional variations in both the distribution of long-term water quality criteria values and the risk quotient distribution of cadmium throughout the Yangtze River Basin. The incorporation of hardness and species-specific attributes resulted in a revised range of long-term water quality criteria for cadmium across different urban locales within the Yangtze River Basin. Notably, the recalibrated values ranged from 0.08 µg·L-1 as the lowest threshold to 0.75 µg·L-1 as the upper limit, signifying a tenfold differentiation. Correspondingly, the urban average annual risk quotient associated with cadmium exposure demonstrated a variation from 0.035 to 1.12, marking a significant 32-fold discrepancy between the lowest and highest values. It is essential to highlight that regions of paramount importance, such as the confluence area connecting the upper and middle stretches of the Yangtze River Basin and the intricate Dongting Lake system, exhibited noteworthy ecological risks attributed to cadmium presence. Consequently, further in-depth investigations into these critical regions are imperative for a comprehensive understanding of the associated risks.

[Trade-off and Synergy of Ecosystem Services in the Yangtze River Economic Belt and Its Driving Factors].

Ecosystem services (ESs) and their changes are complex processes driven by multiple factors. Understanding the trade-off and synergy between ESs and their driving factors is essential for achieving effective management of ESs and human well-being. Taking the Yangtze River Economic Belt as the research area, this study analyzed the temporal and spatial variation characteristics of four ESs including water yield, soil conservation, carbon sequestration, and food supply from 2000 to 2020. Correlation analysis and geographically weighted regression were used to identify and quantify the trade-off and synergy between ESs. On this basis, the partial least squares structural equation model was used to explore the impact of natural and human activities on ESs, and then the driving mechanism of ESs relationship change was analyzed via GeoDetector. The results showed that:① During the 20 years, the average annual carbon sequestration increased from 946.14 t·km-2 to 1 202.73 t·km-2, and the average food supply increased from 32.73×104 Yuan·km-2 to 127.22×104 Yuan·km-2. Water yield and soil conservation increased to a lesser degree. ② On the whole, carbon sequestration and soil conservation and food supply and water yield showed synergy, and other ESs were trade-offs. The relationship between ESs varied in different regions. ③ Terrain and climate were important driving factors for ESs and the trade-off and synergy of multiple ESs. Among them, structural equation model results showed that climate had a positive impact on water yield (S=0.73), and terrain had a negative impact on food supply (S=-0.57). GeoDetector results revealed that the main driving factors affecting the spatial relationship between carbon sequestration and water yield were elevation (q=0.38) and precipitation (q=0.19). The results of this study can provide a scientific reference for the sustainable management of ESs in the Yangtze River Economic Belt and the realization of the coordinated development of ecological environment protection and social economy in the region.