Silver carp mediated biological control techniques are often advocated for controlling cyanobacteria blooms in eutrophic water, which are often enriched with arsenic (As). However, the transfer and fate of As during the biological control of cyanobacteria blooms by silver carp in As-rich eutrophic water remain unclear. Based on the simulated ecosystem experiment, the accumulation of As in silver carp and the transfer and fate of As in the water-algae-silver carp system during Microcystis aeruginosa blooms controlled by silver carp were investigated. Microcystis aeruginosa showed high tolerance to As(V). The accumulation of As in different tissues of silver carp was different, as follows: intestine > liver > gill > skin > muscle. After silver carp ingested As-rich Microcystis aeruginosa, As accumulation in the intestine, liver, gill, and skin of silver carp was enhanced under the action of digestion and skin contact. Compared with the system without algal, As accumulation in the intestine, liver, gill, and skin of silver carp increased by 1.1, 3.3, 3.3, and 9.6 times, respectively, after incubation for 30 days in the system with Microcystis aeruginosa, while the accumulation of As in the muscle was only slightly increased by 0.56 mg/kg. This work revealed the transfer and fate of As during algal control by silver carp, elucidated the accumulation mechanism of As in water-algae-silver carp system, enriched our understanding of As bioaccumulation and transformation in As-rich eutrophication water, and provided a scientific basis for assessing and predicting As migration and enrichment in water-algae-silver carp system.

Further treatment of secondary effluents before their discharge into the receiving water bodies could alleviate water eutrophication. In this study, the Chlorella proteinosa was cultured in a membrane photobioreactor to further remove nitrogen from the secondary effluents. The effect of hydraulic retention time (HRT) on microalgae biomass yields and nutrient removal was studied. The results showed that soluble algal products concentration reduced in the suspension at low HRT, thereby alleviating microalgal growth inhibition. In addition, the lower HRT reduced the nitrogen limitation for Chlorella proteinosa\'s growth through the phase-out of nitrogen-related functional bacteria. As a result, the productivity for Chlorella proteinosa increased from 6.12 mg/L/day at an HRT of 24 hr to 20.18 mg/L/day at an HRT of 8 hr. The highest removal rates of 19.7 mg/L/day, 23.8 mg/L/day, and 105.4 mg/L/day were achieved at an HRT of 8 hr for total nitrogen (TN), ammonia, and chemical oxygen demand (COD), respectively. However, in terms of removal rate, TN and COD were the largest when HRT is 24 hr, which were 74.5% and 82.6% respectively. The maximum removal rate of ammonia nitrogen was 99.2% when HRT was 8 hr.

The complex hydrological conditions caused by the backwater effect at the confluence inevitably modify the geochemical processes of elements. However, there is still a lack of comprehensive understanding regarding the precise transformation mechanisms of nutrients in large river systems. This study aimed to investigate the hydrodynamic characteristics and their impact on phosphorus transfer in the lower Han River, which is influenced by backwater from the Yangtze River (the largest river in China). By establishing a hydrodynamic-water quality model, we have determined that the discharge ratio (the ratio of flow between the Han River discharge and the Yangtze River discharge) can be utilized as a representative indicator of the backwater effect from the Yangtze River on the Han River. Three distinct patterns were identified in this study: mixing, backwater, and intrusion. The corresponding discharge ratio values were categorized as >0.08, 0.01∼0.08, and <0.01 respectively. Additionally, the extent of the backwater zone was determined, revealing that the length of the backwater zone increased from 50 km (XG) to 100 km (FS) as the discharge ratio decreased from 0.08 to 0.01. Furthermore, it was observed that the water level at the confluence rose from 2.52 m to 6.83 m in accordance with these changes in discharge ratio values. The migration pattern of phosphorus primarily involved the settling and retention of particulate phosphorus, particularly the labile particulate organic phosphorus (LOP) and dissolved organic phosphorus (DOP). When the confluent patterns became the intrusion pattern, the backwater zone expanded to 150 m (XT), causing a 10.40 m increase in water level at the confluence. An intrusion zone formed, and its phosphorus concentrations were same as Yangtze River\'s. Above the intrusion area, a backwater region formed and its concentrations of LOP and DOP decreased, while the concentration of PO43- increased due to the release from resuspended particles. This release was induced by higher velocity of bottom water brought about by the water exchange of two rivers. The discharge ratio of 0.01-0.08 resulted in the sedimentation of LOP and DOP, causing the lower Han River to act as a \"sink\" for phosphorus, potentially exacerbating phosphorus pollution. Higher discharge ratios in spring led to phosphorus release from sediment, increasing dissolved phosphorus concentrations and raising the risk of algal blooms in the lower Han River. These findings have significant implications for larger rivers worldwide and provide insights into strategies for ecological management and prevention of algal blooms.

The decomposition of macrophytes plays a crucial role in the nutrient cycles of macrophyte-dominated eutrophication lakes. While research on plant decomposition mechanisms and microbial influences has rapid developed, it is curious that plant decomposition models have remained stagnant at the single-stage model from 50 years ago, without endeavor to consider any important factors. Our research conducted in-situ experiments and identified the optimal metrics for decomposition-related microbes, thereby establishing models for microbial impacts on decomposition rates (k_RDR). Using backward elimination in stepwise regression, we found that the optimal subset of independent variables-specifically Gammaproteobacteria-Q-L, Actinobacteriota-Q-L, and Ascomycota-Q-L-increased the adjusted R-squared (Ra2) to 0.93, providing the best modeling for decomposition rate (p = 0.002). Additionally, k_RDR can be modeled by synergic parameters of ACHB-Q-L, LDB-Q-L, and AB-Q-L for bacteria, and SFQ for fungi, albeit with a slightly lower Ra2 of 0.7-0.9 (p < 0.01). The primary contribution of our research lies in two key aspects. Firstly, we introduced optimal metrics for modeling microbes, opting for debris surface microbes over sediment microbes, and prioritizing absolute abundance over relative abundance. Secondly, our model represents a noteworthy advancement in debris modeling. Alongside elucidating the focus and innovative aspects of our work, we also addressed existing limitations and proposed directions for future research. SYNOPSIS: This study explores optimum metrics for decomposition-related microbes, offering precise microbial models for enhanced lake nutrient cycle simulation.

Although benthic microbial community offers crucial insights into ecosystem services, they are underestimated for coastal sediment monitoring. Sepetiba Bay (SB) in Rio de Janeiro, Brazil, holds long-term metal pollution. Currently, SB pollution is majorly driven by domestic effluents discharge. Here, functional prediction analysis inferred from 16S rRNA gene metabarcoding data reveals the energy metabolism profiles of benthic microbial assemblages along the metal pollution gradient. Methanogenesis, denitrification, and N2 fixation emerge as dominant pathways in the eutrophic/polluted internal sector (Spearman; p < 0.05). These metabolisms act in the natural attenuation of sedimentary pollutants. The methane (CH4) emission (mcr genes) potential was found more abundant in the internal sector, while the external sector exhibited higher CH4 consumption (pmo + mmo genes) potential. Methanofastidiosales and Exiguobacterium, possibly involved in CH4 emission and associated with CH4 consumers respectively, are the main taxa detected in SB. Furthermore, SB exhibits higher nitrous oxide (N2O) emission potential since the norB/C gene proportions surpass nosZ up to 4 times. Blastopirellula was identified as the main responsible for N2O emissions. This study reveals fundamental contributions of the prokaryotic community to functions involved in greenhouse gas emissions, unveiling their possible use as sentinels for ecosystem monitoring.

Metal materials undergo severe corrosion in eutrophic environments. The effect of DO decay stimulated by high concentrations of nitrogen and phosphorus pollutants on microorganisms leads to the coupling of electrochemical and microbial corrosion processes. However, there are few studies on microbial corrosion mechanisms in eutrophic environments. This article discusses the corrosive factors of marine eutrophication, summarizes the impact of marine eutrophication on microbial corrosion and the potential mechanisms, including aerobic biofilm corrosion, aerobic & anaerobic mixed biofilm corrosion, and anaerobic microbial electron transfer corrosion, and expounds on the research methods for microbial corrosion of materials serving in estuarine areas prone to pollution. Microbial prevention and control, such as nutrient restriction and microbial interspecies competition, are of research value in the field of green protection. Microbial corrosion mechanisms studies in marine eutrophication environments are significant for environment monitor development, water intake and algae control technologies, and corrosion protection in polluted environments.

Excessive anthropogenic phosphorus (P) emissions put constant pressure on aquatic ecosystems. This pressure can be quantified as the freshwater eutrophication potential (FEP) by linking P emissions, P fate in environmental compartments, and the potentially disappeared fraction of species due to increase of P concentrations in freshwater. However, previous fate modeling on global and regional scales is mainly based on the eight-direction algorithm without distinguishing pollution sources. The algorithm fails to characterize the fate paths of point-source emissions via subsurface pipelines and wastewater treatment infrastructure, and exhibits suboptimal performance in accounting for multidirectional paths caused by river bifurcations, especially in flat terrains. Here we aim to improve the fate modeling by incorporating various fate paths and addressing multidirectional scenarios. We also update the P estimates by complementing potential untreated point-source emissions (PSu). The improved method is examined in a rapidly urbanizing area in Taihu Lake Basin, China in 2017 at a spatial resolution of 100 m × 100 m. Results show that the contribution of PSu on FEP (62.6%) is greater than that on P emissions (58.5%). The FEP is more spatially widely distributed with the improved fate modeling, facilitating targeted regulatory strategies tailored to local conditions.

Predicting the parameters that influence colloidal phosphorus (CP) release from soils under different land uses is critical for managing the impact on water quality. Traditional modeling approaches, such as linear regression, may fail to represent the intricate relationships that exist between soil qualities and environmental influences. Therefore, in this study, we investigated the major determinants of CP release from different land use/types such as farmland, desert, forest soils, and rivers. The study utilizes the structural equation model (SEM), multiple linear regression (MLR), and three machine learning (ML) models (Random Forest (RF), Support Vector Regression (SVR), and eXtreme Gradient Boosting (XGBoost)) to predict the release of CP from different soils by using soil iron (Fe), aluminum (Al), calcium (Ca), pH, total organic carbon (TOC) and precipitation as independent variables. Results show that colloidal-cations (Fe, Al, Ca) and colloidal-TOC strongly influence CP release, while bioclimatic variables (precipitation) and pH have weaker effects. XGBoost outperforms the other models with an R2 of 0.94 and RMSE of 0.09. SHapley Additive Explanations described the outcomes since XGBoost is accurate. The relative relevance ranking indicated that colloidal TOC had the highest ranking in predicting CP. This was supported by the analysis of partial dependence plots, which showed that an increase in colloidal TOC increased soil CP release. According to our research, the SHAP XGBoost model provides significant information that can help determine the variables that considerably influence CP contents as compared to RF, SVM, and MLR.

Dinoflagellates and diatoms are highly prevalent and ecologically important phytoplankton in coastal waters, greatly contributing to primary productivity in marine ecosystems. Although their composition and diversity have been extensively elucidated in the open ocean, their interaction patterns and community assembly in long-term eutrophic coastal waters remain poorly understood. This investigation aimed to elucidate the seasonal successional patterns of dinoflagellates and diatoms by 18S rRNA gene amplicon sequencing in a semi-enclosed bay. The results revealed that dinoflagellate and diatom communities have pronounced seasonal succession patterns, which are primarily associated with temperature. Furthermore, the most prevalent species throughout the year were Heterocapsa rotundata and Skeletonema costatum. Moreover, the assembly of dinoflagellate and diatom communities was mainly dominated by stochastic processes, with drift being the major factor. The co-occurrence of dinoflagellates and diatoms showed seasonal patterns, with the highest interactions observed in autumn. In addition, interactions of Syndiniales with dinoflagellates and diatoms highlighted the roles of parasites in eutrophic conditions. Flavobacteriaceae and Rhodobacteraceae are the bacterial taxa that most frequently interacted with dinoflagellates and diatoms, with interactions between dinoflagellates and bacteria being more complex than those between diatoms and bacteria. Overall, this study provides results that deepen our understanding of the phytoplankton dynamics in coastal eutrophic waters.IMPORTANCEDinoflagellates and diatoms are major phytoplankton groups in coastal waters. The composition and diversity of dinoflagellates and diatoms in the open ocean have been well documented; however, it remains uncertain to what extent their adaptation to long-term eutrophic conditions influences their response to environmental disturbances. Here, we investigated the interactions and assembly processes of dinoflagellates and diatoms in a eutrophic bay throughout the whole year. Our findings revealed that interactions between dinoflagellates and diatoms are primarily shaped by seasonal transitions, while prolonged eutrophic conditions tend to amplify stochastic processes in community assembly. These findings provide novel perspectives on the influence of long-term eutrophication on phytoplankton dynamics within eutrophic waters.

Trophic state index (TSI) serves as a key indicator for quantifying and understanding the lake eutrophication, which has not been fully explored for long-term water quality monitoring, especially for small and medium inland waters. Landsat satellites offer an effective complement to facilitate the temporal and spatial monitoring of multi-scale lakes. Landsat surface reflectance products were utilized to retrieve the annual average TSI for 2693 lakes over 1 km2 in China from 1984 to 2023. Our method first distinguishes lake types by pixels with a decision tree and then derives relationships between trophic state and algal biomass index. Validation with public reports and existing datasets confirmed the good consistency and reliability. The dataset provides reliable annual TSI results and credible trends for lakes under different area scales, which can serve as a reference for further research and provide convenience for lake sustainable management.