In aquatic ecosystems, phytoplankton biomass profiles often exhibit nonuniform vertical distributions under certain environmental conditions. Their distribution patterns and structural characteristics serve as important indicators of the stability and ecological health of aquatic ecosystems. However, the patterns and structures of phytoplankton biomass profiles in deep-water reservoirs, as well as the influences of surface water quality, meteorological conditions, and hydrological factors on these profiles, remain insufficiently understood. To characterize the patterns of phytoplankton biomass profiles in deep-water reservoirs, six years of high-frequency profiling buoy data collected from the large, deep Xin’anjiang Reservoir in China were analyzed using nonlinear fitting. Furthermore, ten potential controlling factors—including surface water quality parameters, meteorological and hydrological variables—were selected and analyzed using the extreme gradient boosting (XGBoost) model to assess their relative contributions and impacts on phytoplankton biomass patterns and structures. The results indicated that nonuniform phytoplankton biomass profiles could be parameterized using a generalized Gaussian function, while uniform profiles were more appropriately described by sigmoid or linear functions. In addition, the structural metrics of the phytoplankton biomass profiles exhibited significant spatial and temporal variations. On the other hand, air temperature (AT), dissolved oxygen (DO), and rainfall (RF) were the primary factors influencing the patterns of phytoplankton biomass profiles. Chlorophyll a (Chla), DO, and air pressure (AP) were the primary factors affecting the structures of nonuniform-type phytoplankton biomass profiles, while Chla, AP, and AT mainly influenced the uniform-type phytoplankton biomass profiles. Our work has significant implications for effectively managing water quality and scientifically estimating phytoplankton biomass in the entire water column.

Elucidating the impacts of wetland use changes on soil carbon (C) storage will contribute to C management strategies and maintaining the global C balance. We quantified soil total carbon (TC) content across various wetland-use types including primitive wetland, degraded wetland, paddy field, dryland field, as well as restored wetland from paddy and dryland field in the Songnen Plain, China. The results indicated that primitive wetland and paddy field exhibited elevated soil TC, which was attributable to their higher soil water content. Primitive wetland soil showed the highest C fixing microbial abundance and RubisCO activity due to its highest water content and lowest bulk density. These findings underscores the importance of hydrological restoration in enhancing the soil C fixing capacity of degraded and reclaimed wetlands. Variations in soil water content, C fixing microbial abundance and RubisCO activity positively explained soil TC variation across different wetland use. Redundancy analysis (RDA) revealed that soil electrical conductivity and TC were the predominant factors in influencing microbial abundance, while soil microbial biomass nitrogen and carbon storage primarily influenced enzyme activity. These results not only illustrate the driving mechanism underlying soil C sink function following wetland use changes, but also provide a scientific basis for enhancing soil C sequestration and promoting sustainable wetland utilization through hydrological restoration.

Eutrophication management has long relied on an empirical cascade linking external nutrient loads to in-lake nutrient concentrations and, ultimately, algal biomass. Yet this cascade is often treated as structurally stable across lakes, despite strong differences in morphometry, as well as its associated mixing regime and internal nutrient cycling. Using a paired comparison of the shallow polymictic Lake Taihu and the deep stratified reservoir Lake Qiandaohu, we show that this eutrophication cascade can weaken at different links under contrasting morphometric and mixing settings, with important consequences for nutrient-control strategies and threshold setting. In Lake Taihu, external loading signals were substantially clearer for total nitrogen (TN) than for total phosphorus (TP), whereas the opposite pattern occurred in Lake Qiandaohu, consistent with contrasting nutrient-retention and internal-cycling pathways between the two systems. Nutrient-chlorophyll a (Chla) relationships also diverged: upper-bound Chla in Lake Taihu increased with both TN and TP, supporting dual nutrient control, whereas Chla in Lake Qiandaohu remained primarily responsive to TP, with TN sensitivity emerging only above approximately 0.89 mg/L and mainly in localized high-TN areas. Across both lakes, pronounced wedge-shaped nutrient-Chla relationships further showed that similar nutrient concentrations can produce markedly different algal outcomes under varying environmental conditions. We therefore reinterpret nutrient thresholds not as fixed deterministic cutoffs, but as risk-dependent probability boundaries, and use quantile regression to explicitly link Chla management targets with different levels of management assurance. For Lake Taihu, where load-concentration relationships were sufficiently robust, these probabilistic concentration thresholds were further translated into external nutrient-load targets. Together, these results establish a morphometry-informed diagnostic pathway that identifies where the load-concentration-response cascade remains reliable, determines whether nitrogen (N), phosphorus (P), or dual nutrient control is warranted, and converts ecological targets into probability-based nutrient thresholds and, where feasible, actionable load targets.

Wetlands act as major sinks and sources of greenhouse gases (GHG) like carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O). These GHG emissions are affected by nitrogen (N) inputs and climate warming, yet their combined impacts on wetland GHG dynamics remain elusive. This study investigated the short-term response of soil CO 2 , CH 4 , and N 2 O emissions from the Sanjiang Plain wetlands in northeastern China to interactive N input (25, 50, and 100 mg N kg-1 soil) and warming (from 20 degrees C to 25 degrees C). Soil microbial abundances, enzyme activities, and soil carbon (C) and N fractions contents were also examined to identify the underlying mechanisms driving GHG emissions. Results showed that short-term N input and warming significantly boosted CO 2 and N 2 O emissions. Nevertheless, compared with low and medium N inputs, high N input suppressed CO 2 release by disrupting the competitive balance among microorganisms and causing soil nutrient imbalance. N input strongly inhibited CH 4 emissions, with greater suppression at higher levels. Two - way ANOVA indicated N input had a stronger effect on CH 4 and N 2 O, while warming influenced CO 2 more. The interaction between N input and warming minimally affected CO 2 and CH 4 emissions and had no significant impact on N 2 O emissions. Mantel and linear regression analyses revealed that CO 2 and N 2 O emissions were positively correlated with microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) contents. CO 2 and CH 4 emissions were also influenced by enzymes and bacterial activities, while CH 4 emissions were positively regulated by the mcrA: pmoA gene abundance ratio and negatively affected by nitrate nitrogen (NO 3--N) content. Ammonium nitrogen (NH 4+ N) and denitrification genes primarily drove N 2 O emissions. These findings shed light on the microbial mechanisms of wetland GHG emissions under N pollution and warming, facilitating predictions of global change impacts on wetland ecosystems.

Wetlands store large soil carbon (C) pools but remain understudied with respect to how labile C inputs regulate microbial community dynamics and C cycling under climate warming. Here, we conducted a labile C (glucose) addition experiment in soils from Zhalong, Momoge, and Xianghai wetlands (Songnen Plain, China) to test two hypotheses: (1) Labile C input alleviates C limitation and increases microbial respiration and Q10; (2) Labile C enrichment shifts microbial communities toward r-strategists (copiotrophs). The results showed that labile C significantly stimulated respiration rate and Q10, especially in topsoil (0–15 cm). It increased bacterial abundance and bacteria-to-fungi ratio, enhanced carbohydrate utilization, and reduced polymer C use, indicating a shift to r-strategists. Labile C addition significantly increased the activities of β-1,4-glucosidase and the contents of soil NH4+-N, NO3−-N. Structural equation modeling showed that soil microbial C metabolic activity positively regulated Q10 and microbial strategy shifts. These findings demonstrate that labile C availability governs microbial thermal responses and life-history strategies in C-limited wetland soils. This study improves mechanistic understanding of wetland C-limited feedbacks and supports evidence-based wetland management under global warming.

Wetlands play a key role in the global carbon cycle, where soil microorganisms and enzymatic activities dominate carbon storage and decomposition. However, the mechanisms underlying seasonal regulation of microbe-mediated carbon cycling in these ecosystems are poorly understood. We thus performed year-round seasonal sampling across spring, summer, autumn and winter in a typical saline-alkaline wetland in the Songnen Plain, northeastern China. By systematically analyzing the seasonal dynamics of metabolic characteristics of soil microbial communities, the abundance of functional genes related to carbon and nitrogen cycling, as well as the hydrolytic enzyme, oxidase, and carbon sequestration enzyme activities, combined with soil physicochemical property measurements. The results showed that soil microbial metabolic activity and beta-1,4-glucosidase activity peaked in summer, whereas polyphenol oxidase activity was highest in winter. In contrast, cbbL gene abundance and soil potential RubisCO activity showed significantly weaker seasonal fluctuations compared with carbon decomposition-related indicators, revealing an asynchronous seasonal pattern of functional potentials between soil heterotrophic carbon decomposition and autotrophic carbon fixation processes: decomposition-related processes were highly sensitive to seasonal changes, while fixation-related functional potential remained stable. Using structural equation modeling (SEM), we analyzed the causal relationships between environmental factors and microbial carbon cycling functions. The results revealed that soil labile carbon (dissolved organic carbon and microbial biomass carbon) was the key driver of seasonal dynamics in microbial and enzymatic activity, with its availability primarily regulated by soil water content and temperature. The mechanistic analysis in this study further reveals that saline-alkali stress is likely to limit the carbon utilization efficiency of microorganism. These findings highlight the pivotal role of labile carbon in wetland carbon cycling and provide new insights for predicting the evolution of carbon sink functions in saline-alkaline wetlands under climate change.

Wetlands are critical terrestrial carbon sinks, playing a vital role in mitigating global warming by fixing substantial atmospheric carbon dioxide. To explore how wetland reclamation and restoration affect soil microbial carbon fixation, we sampled soils from five land-use types in western Jilin Province, China: undisturbed natural reed wetland, reclaimed rice paddy and upland field, restored agricultural drainage wetland and naturally restored wetland after farmland abandonment. We analyzed the effects of wetland reclamation and restoration on microbial communities, metabolic pathways, and carbon fixation potential. Results showed Proteobacteria (31.81 %), Actinobacteria (27.08 %), and Acidobacteria (15.12 %) dominated carbon-fixing microbes, with the reductive tricarboxylic acid cycle and dicarboxylate/4-hydroxybutyrate cycle as major carbon-fixing pathways. The natural wetland had the highest carbon fixation potential, with a mean value of 1.58 mg·kg-1 across the 0-15 cm topsoil layer and 15-30 cm subsoil layer, which was 1.30 to 4.02 times that of the reclaimed wetlands and restored wetlands. Among reclaimed sites, the rice paddy retained soil microbial community similarity to the natural wetland with complex, stable microbial networks. Compared to the naturally restored wetland, the agricultural drainage-restored wetland showed superior restoration outcomes, including microbial communities more similar to the natural wetland, higher network stability, and greater carbon fixation potential. Soil water and inorganic nitrogen contents were core drivers regulating carbon fixation via RubisCO activity and microbial metabolic pathways. This result highlights that the key to wetland restoration lies in prioritising hydrological regulation and nitrogen management, thereby enhancing microbial carbon fixation potential.

Extreme rainfall and flooding are intensifying globally, yet their interaction with reservoir operations on cyanobacterial dynamics remains unclear. This study compares two flood years (2020 and 2024) in Lake Qiandaohu, China, using 2021-2023 as a baseline, to disentangle how rainfall patterns and flood-control operations shape cyanobacteria succession. The 2020 event featured concentrated summer rainfall and rapid high-discharge releases (maxoutflow = 7228 m3/s). Under this regime, the turbid inflow plunged to 20-40 m near the dam, and post-flood cyanobacterial responses were brief and confined to the reservoir inflow region. In contrast, the anomalously wet spring in 2024 (46% rainfall more than in 2020), combined with moderate staged discharge operations during the summer flood (maxoutflow = 4430 m3/s), caused sustained water-level rise and allowed the turbidity plume to intrude into the euphotic zone (0-20 m) near the dam. This press disturbance shifted the dominant control from physical flushing to nutrient-hydrodynamic coupling. Persistent spring rainfall first promoted pre-flood dominance of the shade-tolerant Pseudoanabaena. The coupling between lagged total phosphorus accumulation and cyanobacterial responses, together with prolonged phosphorus retention in the euphotic zone, further promoted five months of post-flood dominance by nitrogen-fixing and vertically migrating Aphanizomenon. These findings extend pulse-press disturbance theory to reservoir ecosystems. Under climate change, intensified extreme rainfall may increase press-type disturbances and associated cyanobacterial blooms in deep oligotrophic-mesotrophic reservoirs. Adaptive reservoir management should therefore dynamically optimize outflow/inflow ratios and avoid sustained water-level rise that traps nutrients within the euphotic zone, thereby reducing the risk of long-tail post-flood cyanobacterial blooms.

The expansion of algal blooms in reservoirs, driven by climate change and human activities, poses intensifying threats to water supply safety. Although altered rainfall runoff patterns act as critical climate multipliers, the response process of the algal community to different rainfall runoff intensities remains poorly understood, particularly in stratified reservoirs. To clarify the pathways and mechanisms by which altered hydrological processes drive algal community, we conducted high-frequency (every 3 d) monitoring program of hydrology, nutrients, and algae through manual sampling combined with data from autonomous buoys from 2018 to 2019 in Xin'anjiang Reservoir, a subtropical reservoir in the humid region of China. The results indicate that the impact of rainfall runoff on algal community is closely associated with its intensity. When the inflow exceeds 300-500 m3 /s, it significantly inhibits algal growth in the riverine zone, with suppression lasting up to 6 days. Compared to nutrient factors, photothermal environmental conditions, especially after rainfall during the flood season, play a more important role in driving algal community changes. Path analysis and correlation analysis further reveal that rainfall runoff not only directly influences algal community dynamics through dilution and pulse effects induced by high inflow, but also indirectly affects algal changes by altering photothermal conditions and nutrient concentrations. Our study quantifies the algal community dynamics and their relationship with environmental factors during variable rainfall runoff processes, improving our knowledge of the driving mechanisms of algal blooms for safeguarding drinking water safety in reservoirs under the context of future climate change.

Abnormal phytoplankton proliferation is increasingly observed in nutrient-poor lakes, yet studies focusing on severe blooms defined by absolute cell-density thresholds remain limited. Through 4 years of high-frequency monitoring in the deep and overall nutrient-poor Lake Qiandaohu, China, we documented recurrent blooms with cyanobacterial densities exceeding 2 & times; 10(7) cells/L (peaking >4 & times; 10(7) cells/L) in its river-lake transition zone. We propose a Liebig-Blackman sequential constraint-alleviation framework to mechanistically explain these events. Rainstorms first alleviate Liebig-type final yield limitation by supplying nitrogen and phosphorus, thereby increasing the attainable cyanobacterial density ceiling for similar to 30 days. Subsequent heatwaves, coupled with poststorm declines in turbidity and flow, alleviate Blackman-type growth rate limitation, thereby favoring rapid cyanobacterial accumulation. The temporal overlap of these two switches forms a critical "bloom window" that enables cyanobacterial densities to rapidly reach severe levels. A mechanism-informed forecasting model, integrating lagged rainfall, current hydrology and water quality, and future short-term meteorological data, achieved good predictive accuracy (R-2 = 0.60-0.95). This transferable mechanism is particularly important in the context of the rapid global expansion of deep drinking-water reservoirs and the increasing occurrence of storm-heatwave coupling under climate change, offering a general framework for understanding bloom risk in river-lake transition zones in oligotrophic lakes and reservoirs.

Wetlands play a critical role in soil carbon storage, a process significantly influenced by land use changes. However, a limited understanding of microbial and environmental mechanisms hampers the development of effective land management strategies for soil carbon sequestration. To elucidate soil carbon stability and microbial mechanisms, we investigated soil carbon content, microbial abundance and enzyme activity across five land types: natural wetlands, paddy fields, dry fields, and wetlands restored from former paddy and dry fields in western Jilin province, China. Our findings show that both topsoil (0-15 cm) and subsoil (15-30 cm) in paddy fields exhibited the highest total carbon (TC) content. In contrast, natural wetlands exhibited lower dissolved organic carbon (DOC) level but maintained relatively high TC content. Wetland reclamation significantly altered soil carbon content, microbial abundance and enzyme activity. Mean soil TC and microbial biomass carbon (MBC) content, along with the abundances of cbbM, nifH and nirS genes and ribulose-1, 5-bisphosphate carboxylase (RubisCO) activity, were all higher in paddy fields compared to dry fields. Bacterial abundance, nirS gene abundance, and the activities of RubisCO, N-acetyl-glucosaminidase (NAG) were higher in summer than in autumn and winter. Structural equation modeling revealed that soil TC content was positively correlated with soil moisture and cbbM gene abundance, but negatively associated with soil salinity and alkalinity. Land use indirectly influenced soil TC content by modulating soil moisture content, cbbM gene abundance, salinityalkalinity level, and RubisCO activity. These results suggest that converting wetlands to paddy fields than dry fields in western Jilin Province, China, may preserve soil carbon content, microbial abundance, and enzyme activity, offering valuable insights for wetland conservation and restoration.

Following the drinking water crisis induced by harmful algal blooms in Lake Taihu in 2007, industrial restructuring and systematic pollution treatment projects were synchronously conducted to control pollutions in Lake Taihu basin. This paper conducts a systematic review of integrated pollution governance in the Lake Taihu Basin to conduct an exploration of sustainability in developing areas. Critical assessment of the conceptual frameworks and implementation strategies from the aspects of governance concept, technology application and environmental benefits have been made through multi-year water quality monitoring. The results showed that the total nitrogen (TN) and total phosphorous (TP) loads entering the lake decreased by 45.6% and 36.6% in 2008–2023, and the water quality of Lake Tiahu and all 15 major inflow rivers met or exceeded Grade III standards in 2024, according to the National Standard for Surface Water Quality. The lake ecosystem has showed signs of restoration via a decline in the extent and intensity of toxic cyanobacterial bloom. At same time, the local economics have been developed without halting due to the pollution governance, which demonstrates a feasible pathway for both pollution management and economic development. This synergistic governance with both soft and hard measures implemented in Lake Taihu basin has reference significance for other developing countries toward sustainability around the world.

1. Compound heatwave and drought (CHWD) events are becoming increasingly frequent, posing significant challenges to aquatic ecosystems. This study assesses the impact of the 2022 CHWD on chlorophyll-a (Chla) concentrations in 40 large shallow lakes (> 50 km(2)) in the Chinese Eastern Plains ecoregion. 2. The findings reveal that the impact of CHWD on algal biomass varies depending on hydrological and nutrient conditions in a lake. In rapidly flushing lakes, CHWD did not change Chla concentration from 32.9 +/- 3.8 mu g/L in the reference year to 34.1 +/- 4.3 mu g/L in the CHWD year (Z = -1.098, p = 0.272), but in long retention lakes Chla concentration decreased from 35.9 +/- 4.1 mu g/L to 33.7 +/- 4.8 mu g/L (Z = -3.552, p < 0.001). 3. Field-monitoring data suggest that the Chla decline in long retention lakes is primarily due to reduced external nutrient inputs from decreased rainfall. In rapid flushing lakes, Chla shows minimal sensitivity to variations in TN or TP. Consequently, the direct effect of climate warming on algal biomass in these lakes may be limited. 4. The effect of CHWD on long retention lakes is nutrient-dependent. For example, Lake Gehu, a long retention lake, experienced an overall increase in Chla, likely because its surplus nitrogen and phosphorus made it less susceptible to drought-induced reductions in external nutrient loads. 5. This study highlights the complex responses of lake ecosystems to climate extremes and provides insights for managing eutrophication in a changing climate.

Wetland soil microbial communities play pivotal roles in biogeochemical cycling; however, how their network complexity mediates carbon (C), nitrogen (N), and phosphorus (P) metabolism in response to soil water content (SWC) changes remains unclear. In this study, soil samples from the Zhalong, Momoge and Xianghai wetlands in Songnen Plain of China were incubated under natural (CK), drought (10 % SWC), and high SWC (50 % SWC) conditions, followed by metagenomic sequencing to evaluate the impact of SWC changes on bacterial community structure and function. The results showed that soil bacterial diversity and network complexity decreased under drought but recovered under high SWC, with Proteobacteria and Actinobacteria displaying divergent responses. C fixation pathways (rTCA and DC-HB cycles) were significantly enriched under 50 % SWC, which correlated strongly with enhanced bacterial interactions. The abundance of denitrification genes (norBC, nosZ) decreased under drought but increased under high SWC. P metabolism (purine metabolism and two-component systems) showed strong SWC dependence, with key genes (PstS, phnDC) increased in abundance under 50 % SWC. Notably, bacterial network complexity tightly coupled with metabolic pathways, indicating SWC driven community restructuring regulates wetland soil C, N and P cycling. These findings underscore the critical importance of hydrological management in maintaining bacterial-mediated nutrient cycling functions of wetland ecosystem under climate change.

Changes in temperature and water level affect the wetland CO2 emissions, while the response mechanism of marsh wetland CO2 emissions to temperature and water synergistic change is still rare. We monitored the CO2 emissions and analyzed their relationships with plant and soil properties in a typical marsh wetland of Sanjiang Plain, Northeast China. We utilized the open-top chamber (OTC) passive warming combined with the automatic water level control platform. Four treatments including control (CK), warming (W), water level reduction (WR), combined warming and water level reduction (WRW) were established. The results showed that the CO2 flux in the growing season reached the maximum value of 425.26 mg center dot m- 2 center dot h- 1 in the WRW treatment. Warming under different water conditions promoted CO2 emissions. Water level reduction interacted with warming and intensified CO2 emissions. Combined warming and water level reduction significantly enhanced soil hydrolases activities, bacteria and nirK gene abundances, microbial biomass carbon and nitrogen (MBC and MBN) contents. Mantel test results revealed that soil beta-glucosidase (BG), acid phosphatase (AP) activities, MBC, MBN contents, plant TC and soil temperature had a significant positive effect on cumulative CO2 flux. The regression analysis demonstrated air and soil temperatures, plant height, chlorophyll content of Carex lasiocarpa were critical factors influencing the dynamic of CO2 emissions in the marsh wetland of the Sanjiang Plain. This finding underscores the essential influence mechanism of hydrolases and MBC, MBN contents on CO2 emissions from marsh wetland under warming and water level reduction conditions. Mitigating climate warming and enhancing wetland water levels to inhibit hydrolytic enzyme activity may reduce wetland CO2 emissions and increase carbon sink.

Early warning of algal biomass is important for the preservation and management of drinking water. However, accurate prediction of algal biomass in large and deep reservoirs remains a challenge. Here, we used six years of high-frequency observations (30 min/time) to train long short-term memory (LSTM) models for forecasting chlorophyll-a concentration (CChla) and column-integrated CChla (CIC) for a large and deep Chinese reservoir (Xin'anjiang Reservoir). Five LSTM-based algal biomass forecasting models were developed, including four CChla models for various forecasting scales (1-hour, 3-hour, 6-hour, and 24-hour) and a CIC model (forecasting scale: 1day). The results showed that the trained LSTM-based models can accurately predict CChla and CIC at reservoir scale and the root mean square error (RSME) values are less than 1.1 and 14.9 mu g/L, respectively. The proposed CChla LSTM model outperformed the MLP, CNN, CNN-LSTM, and RNN models, with the RMSE decreasing by 2.6%, 4.8%, 5.3%, and 9.3%, respectively. Similarly, the proposed CIC LSTM model surpassed the MLP, CNN, CNN-LSTM, and RNN models, resulting in a RMSE reduction of 36.1%, 46%, 50.3%, and 52.8%, respectively. With the time lag increase, the performance of the multistep-ahead forecasting model exhibits initial improvement followed by deterioration. The best performance of the multistep-ahead forecasting model was observed when the input time length is 6-8 times the forecasting time length. Spatially, the proposed models perform better at the sites with small variations in algal biomass. On the other hand, water temperature is the most important influential factor for predicting algal biomass. Our work provides an effective tool for managers to develop preemptive measures to control algal blooms.

In recent years,algal blooms have occurred frequently in the backwater areas of tributaries of the Three Gorges Reservoir.The retention and release of sediment phosphorus might be a key factor,so it is necessary to conduct in-depth research on its impact.This study took the four important tributaries of the Three Gorges Reservoir,the Xiangxi River,Daning River,Caotang River,and Xiaojiang River,as the research object to evaluate the potential release of sediment phosphorus in these tributaries and its impact on water quality,using investigation and incubation experiments.The results showed that the total phosphorus content in sediments at the mouth of the Xiangxi River,Daning River,Caotang River,and Xiaojiang River were 634,434,629,and 689 mg·kg-1,respectively.The active phosphorus(NaOH-P)contents in sediment of those four rivers were 69,100,103,and 115 mg·kg-1,respectively,which were at medium and lower levels compared with those in major domestic reservoirs.The phosphorus contents in sediments in the river mouth area,where tributaries flowed into the main stream of the Three Gorges,were higher than that of the upstream reaches of the corresponding tributaries.The incubation experiments showed that the sediments in the river mouth area of each tributary had higher phosphorus release potential than sediments in the upstream reaches.Within the four tributaries,the sediments in the Xiaojiang River had the highest phosphorus release ability.The changes in water environmental conditions,such as increased temperature and reduced dissolved oxygen concentration,could significantly promote the phosphorus release rates from sediments.The phosphorus release rate of sediments in Xiaojiang River was the largest,at 0.861 mg·(m2·d)-1,which made the dissolved phosphorus concentration in bottom water much higher than in surface water during the algae bloom period.Overall,the sediment in the tributaries of the Three Gorges Reservoir,especially in the Xiaojiang and Xiangxi Rivers,currently played the role as phosphorus"source"during the algal bloom periods,in which phosphorus release from sediments could accelerate the phosphorus cycle in the water body.The results of this study offer a scientific basis for the control of internal phosphorus in river-type reservoirs and the prevention and control of algal blooms.

Monitoring total suspended solids (TSS) in lakes at a global scale is critical for understanding lake ecosystem responses to climate change and anthropogenic activities. However, reliable retrieval methods for TSS global mapping remain elusive due to the optical complexity of inland waters, leaving the spatiotemporal dynamics of global lake TSS poorly constrained. This study developed a global TSS retrieval model using a Random Forest (RF) algorithm based on Landsat OLI surface reflectance imagery. The model achieved satisfactory performance (R2 = 0.73) and demonstrated exceptional robustness in estimating lake TSS concentrations (0-1,500 mg L-1) across diverse water quality conditions, geographical locations, and temporal ranges. During summers of 2014 to 2023, lakes in mid-low latitude regions, particularly arid zones, exhibited significantly higher mean TSS concentrations compared to other areas. Our analysis revealed that 62.9% of clear lakes (TSS < 10 mg L-1) that underwent statistically significant changes (P < 0.05) showed significantly increasing trends of TSS, emphasizing the urgent need to enhance monitoring and protection measures for clear-water ecosystems. Furthermore, we classified lakes into three types based on the predominant regulatory mechanisms controlling TSS dynamics and systematically elucidated the distinct mechanisms through which lake topography, hydrological conditions, climate, and watershed vegetation cover influence TSS concentrations across different lake types. This study provides new insights into the spatiotemporal patterns of global lake TSS variations and the response mechanisms of different lake types to hydrological conditions and climatic forcing, contributing improved understanding of global freshwater ecosystem dynamics under environmental change.

The increased frequency and intensity of heavy rainfall events due to climate change could potentially influence the movement of nutrients from land-based regions into recipient rivers. However, little information is available on how the rainfall affect nutrient dynamics in subtropical montane rivers with complex land use. This study conducted high-frequency monitoring to study the effects of rainfall on nutrients dynamics in an agricultural river draining to Lake Qiandaohu, a montane reservoir of southeast China. The results showed that riverine total nitrogen (TN) and total phosphorus (TP) concentrations increased quickly with increasing rainfall intensity, while TN:TP decreased. The heavy rainfall and rainstorm drove more than 30% of the annual N and P loading in only 5.20% of the total rainfall period, indicating that increased storm runoff is likely to exacerbate eutrophication in montane reservoirs. NO3−-N is the primary nitrogen form lost, while particulate phosphorus (PP) dominated phosphorus loss. Spatially, forested watersheds have better drainage quality, while it is still a potential source of nonpoint pollution during rainfall events. TN and TP concentrations were significantly higher at sites dominated by cropland and residential area, indicating their substantial contributions to deteriorating river water quality. Temporally, TN and TP concentrations reached high values in May-August when rainfall was most intense, and TN and TP were higher in spring and summer under the same rainfall intensities. The results emphasize the influence of rainfall-runoff and land use on dynamics of riverine N and P loads, providing guidance for nutrient load reduction planning for Lake Qiandaohu.