Summer heatwaves promote harmful algal blooms in the Fuchunjiang Reservoir, an important drinking water source.

Extensive outbreaks of harmful algal blooms (HABs) occurred in the Fuchunjiang Reservoir in 2022, a crucial urban drinking water source, coinciding with extreme summer heatwaves. We hypothesize that these heatwaves contributed to HABs formation and expansion. Leveraging Landsat 8 and Sentinel-2 data, we employed clustering and machine learning methods to quantify the HABs distribution and area. Concurrent meteorological and water quality data aided in uncovering the effects of heatwave on HABs. When applying different methods to extract HABs from remote sensing images, random forest (RF) analyses indicated accuracies of 99.3% and 99.8% for Landsat 8 and Sentinel-2 data, respectively, while classification and regression tree (CART) analyses indicated 99.1% and 99.7% accuracies, respectively. Support vector machine (SVM) exhibited lower accuracies (83.5% and 97.4%). Thus RF, given its smaller differences between satellites and high accuracy, was selected for further analysis. Both satellites detected extensive HABs in 2022, with Sentinel-2 recording a peak area of 24.13 km2 (44.6% of cloud-free water area) on August 11, 2022. Increasing trends with amplified durations were observed for summer heatwaves in Jiande and Tonglu around the Fuchunjiang Reservoir. Notably, these areas experienced extreme heatwaves for 63 and 58 days in 2022, respectively, more than double the 1980-2022 average. From June 1 to October 8, 2022, water temperature peaks significantly coincided with expansive HABs and elevated chlorophyll a (Chl-a) concentration from 4.8 µg/L to 119.2 µg/L during the summer heatwaves. Our findings indicated that the reservoir became more HAB-prone during heatwave events, escalating the drinking water safety risk. These results emphasize the challenges faced by reservoir managers in dealing with climate-induced extreme heatwaves and underscore the urgency for heightened attention from water source management departments.

Decreasing denitrification rates poses a challenge to further decline of nitrogen concentration in Lake Taihu, China.

Nitrogen (N) concentrations in many lakes have decreased substantially in recent years due to external load reduction to mitigate harmful algal blooms. However, little attention has been paid to the linkage between the lakes' nitrogen removal efficiency and improved water quality in lakes, especially the variation of denitrification rate (DNR) under decreasing N concentrations. To understand the efficiency of N removal under improving water quality and its influence on the N control targets in Lake Taihu, a denitrification model based on in situ experimental results was developed and long-term (from 2007 to 2022) water quality and meteorological observations were used to estimate DNR and relate it to the amount of N removal (ANR) from the lake. The concentration of total nitrogen (TN) in Lake Taihu decreased from 3.28 mg L-1 to 1.41 mg L-1 from 2007 to 2022 but the reduction showed spatial heterogeneity. The annual mean DNR decreased from 45.6 µmol m-2 h-1 to 4.2 µmol m-2 h-1, and ANR decreased from 11.85×103 t yr-1 to 1.17×103 t yr-1 during the study years. N budget analysis suggested that the amount of N removed by denitrification accounted for 23.3 % of the external load in 2007, but decreased to only 4.0 % in 2022. Thus, the contribution of N removal by internal N cycling decreased significantly as water quality improved. Notably, the proportion of ANR in winter to total ANR increased from 14 % in 2007 to 23 % in 2022 due to warming. This could potentially lead to N deficiencies in spring and summer, thus limiting the availability of N to phytoplankton. A TN concentration of less than 1.0 mg L-1 in the lake and 1.5 mg L-1 in the inflowing lake zones in spring contribute to local N-limitation in Lake Taihu for cyanobacteria control. Our study revealed a general pattern that N removal efficiency decreases with improved water quality, which is instructive for eutrophic lakes in nitrogen management.

An indispensable role of overlying water in nitrogen removal in shallow lakes.

The nitrogen (N) removal characteristics in water columns and sediments of shallow lakes, influenced by various factors, may exhibit spatial variations in lakes with algal-macrophyte dominance. The N removal rates in water columns and sediments of Lake Taihu were investigated. Our findings indicated that the total N removal rates in Lake Taihu followed the order of algae-dominance > macrophyte-dominance > pelagic lake (without the presence of algae and macrophytes). Correlation analysis revealed that the key environmental factors affecting denitrification and anammox in sediments of algae/macrophyte-type lakes were nitrate nitrogen (NO3--N), nitrite nitrogen (NO2--N), ammonia nitrogen (NH4+-N), and chlorophyll a (Chl-a). The linear regression demonstrated that a significant correlation between the denitrification and the anammox in sediments, with a correlation coefficient of 0.81 (p < 0.01). The contributions to N removal from the water columns and sediments in Lake Taihu were 53 % and 47 %, respectively. Denitrification predominantly drove N removal from sediments, whereas anammox dominated the N removal in water columns. Thus, N removal from the water columns is nonnegligible in shallow eutrophic lakes. This study enhances our understanding of N biogeochemical cycling dynamics in sediment-water and algae/macrophyte ecosystems across various shallow eutrophic lake regions.

Climate change intensifies algal biomass resurgence in eutrophic Lake Taihu, China.

Climate change can significantly alter phytoplankton growth and proliferation, which would counteract restoration efforts to control algal blooms. However, the knowledge is limited about the quantitative evaluation of the causal effect of algal biomass resurgence in large shallow lakes where there is no significant improvement after long term lake restoration. Here, a bucket process-based phytoplankton dynamic model is developed to quantify the contributions of climate change and nutrients concentration changes to phytoplankton biomass resurgence after 2014 in hypereutrophic Lake Taihu, China. Compared to 2008-2014, the mean water temperature (WT) and the mean phosphate are higher, the mean photosynthetically active radiation (PAR), the mean total suspended solids (TSS), and the mean dissolved inorganic nitrogen (DIN) are lower, during 2015-2020. Their contribution to algal biomass resurgence during 2015-2020 is WT (+58.7 %), PAR (-2.6 %), TSS (+23.2 %), DIN (-22.1 %) and phosphate (+42.7 %), respectively. Climate change (WT, PAR, and TSS), which contributed +64.9 % to the phytoplankton biomass resurgence, underscores the urgent need to continuously take more effective measures to reduce nutrient emissions to offset the effects of climate change in Lake Taihu and in other eutrophic lakes.

An optical mechanism-based deep learning approach for deriving water trophic state of China's lakes from Landsat images.

Widespread eutrophication has been considered as the most serious environment problems in the world. Given the critical roles of lakes in human society and serious negative effects of water eutrophication on lake ecosystems, it is thus fundamentally important to monitor and assess water trophic status of lakes. However, a reliable model for accurately estimating the trophic state index (TSI) of lakes across a large-scale region is still lacking due to their high complexity. Here, we proposed an optical mechanism-based deep learning approach to remotely estimate TSI of lakes based on Landsat images. The approach consists of two steps: (1) determining the optical indicators of TSI and modeling the relationship between them, and (2) developing an approach for remotely deriving the determined optical indicator from Landsat images. With a large number of in situ datasets measured from lakes (2804 samples from 88 lakes) across China with various optical properties, we trained and validated three machine learning methods including deep neural network (DNN), k-nearest neighbors (KNN) and random forest (RF) to model TSI with the optical indicators and TSI and derive the determined optical indicator from Landsat images. The results showed that (1) the total absorption coefficients of optically active constituents at 440 nm (at-w(440)) performs best in characterizing TSI, and (2) DNN outperforms other models in the inversion of both TSI and at-w(440). Overall, our proposed optical mechanism-based deep learning approach demonstrated a robust and satisfactory performance in assessing TSI using Landsat images (root mean squared error (RMSE) = 5.95, mean absolute error (MAE) = 4.81). This highlights its merit as a nationally-adopted method in lake water TSI estimation, enabling the convenience of the acquisition of water eutrophic information in large scale, thereby assisting us in managing lake ecology. Therefore, we assessed water TSI of 961 lakes (>10 km2) across China using the proposed approach. The resulting at-w(440) and TSI ranged from 0.01 m-1 to 31.42 m-1 and from 6 to 96, respectively. Of all these studied lakes, 96 lakes (11.40 %) were oligotrophic, 338 lakes were mesotrophic (40.14 %), 360 lakes were eutrophic (42.76 %), and 48 were hypertrophic (5.70 %) in 2020.

Colonial Microcystis' biomass affects its shift to diatom aggregates under aeration mixing.

The effect of hydrodynamic mixing on controlling Microcystis blooms or changing the algal community to diatom dominance has been widely studied; however, the effects of colonial Microcystis biomass on the development of the algal community are poorly known. Here, in order to study the changes in Microcystis blooms under continuous aeration mixing, an experiment was carried out in a greenhouse with factors of varying biomass of Microcystis and inorganic nitrogen and phosphorus enrichment in summer. There were three chlorophyll a (Chl-a) levels in six treatments: low Chl-a level of 68.4 µg L-1 (treatments L, L-E), medium Chl-a level of 468.7 µg L-1 (treatments M, M-E), and high Chl-a level of 924.1 µg L-1 (treatments H, H-E). Treatments L-E, M-E and H-E were enriched with the same inorganic nitrogen and phosphorus nutrients. During the experiment of 30 days, the concentration of Microcystis and Chl-a decreased, and diatom Nitzschia palea cells appeared in all the treatments, which became dominant in treatments M, M-E, H and H-E, with the highest biomass of 9.41 ± 1.96 mg L-1 Nitzschia in treatment H-E on day 30. The rank order of the biomass of Nitzschia from low to high was (L = L-E) < (M = M-E) < H < H-E (P < 0.05). In addition, Nitzschia cells were aggregates attached to Microcystis colonies in all the treatments. The results showed that the initial biomass of colonial Microcystis affected the algal shift from Microcystis dominance to Nitzschia dominance. However, the enriched inorganic nitrogen and phosphorus was beneficial for the Nitzschia increase in the high biomass treatment alone. The shift from Microcystis dominance to diatom dominance under continuous aeration mixing may be caused by low light conditions as well as the nutrients released from Microcystis decay. Moreover, the aerobic condition caused by aeration mixing maintained the colonial mucilaginous sheath to support the growth of Nitzschia cells in aggregation. This study found for the first time that Microcystis blooms could shift to diatom Nitzschia dominance in aggregates. It provided a method to control and manipulate Microcystis blooms to diatom dominance through continuous aeration mixing to proper biomass of Microcystis colonies. The shift to diatoms dominance would provide more high quality food organisms for aquaculture and be beneficial to the material cycling and energy flowing in food web dynamics.

Construction and assessment of an indicator system of stream conditions in a typical mountain landscape in Northeast China.

Stream ecosystem health assessments are crucial for the effective management of aquatic ecosystem service functions and the assessment of anthropogenic and climatic impacts on aquatic ecosystems. However, there is still a lack of comprehensive assessment methods based on complete ecosystem structures. This study improved an ecological health assessment system, which consists of 13 indicators based on ecosystem structure. The assessment system was applied to 30 streams on Changbai Mountain. The results showed that the comprehensive index of stream health (ISH) in Changbai Mountain was relatively high, and the ISH increased with the elevation gradient. The dominant factors controlling the ecosystem health level were water pH, water flow, vegetation coverage, total phosphorus (TP), and vegetation diversity index. All these results indicated that the damage caused by excessive deforestation and farmland occupation in recent years has not been fully reversed and that human disturbance from tourism may be the main reason for the low stream health at lower elevations. Our results suggest that the key to future work is to increase quantitative research on disturbance sensitivity and to develop economically viable restoration measures.

The impact of extreme heat on lake warming in China.

Global lake ecosystems are subjected to an increased occurrence of heat extremes, yet their impact on lake warming remains poorly understood. In this study, we employed a hybrid physically-based/statistical model to assess the contribution of heat extremes to variations in surface water temperature of 2260 lakes in China from 1985 to 2022. Our study indicates that heat extremes are increasing at a rate of about 2.08 days/decade and an intensity of about 0.03 °C/ day·decade in China. The warming rate of lake surface water temperature decreases from 0.16 °C/decade to 0.13 °C/decade after removing heat extremes. Heat extremes exert a considerable influence on long-term lake surface temperature changes, contributing 36.5% of the warming trends within the studied lakes. Given the important influence of heat extremes on the mean warming of lake surface waters, it is imperative that they are adequately accounted for in climate impact studies.

Increased dominance of terrestrial component in dissolved organic matter in Chinese lakes.

The source composition of chromophoric dissolved organic matter (CDOM) in lakes is closely related to regional environmental changes, human activities, and the carbon cycle. The spectral slope ratio (SR) is an important parameter of CDOM optical components, and combined with remote sensing technology, the source composition of CDOM can be tracked comprehensively and efficiently in large regions. Here, we proposed a CDOM source tracking remote sensing model (CDOM-SR) based on the hue angle (α) to assess the spatial pattern and long-term trend of the CDOM source composition in Chinese lakes (surface area ≥ 1 km2) from 1986 to 2021. Validation results show that the CDOM-SR model has a good SR estimation performance with a median absolute percentage difference, root mean square deviation, median ratio, and median deviation of 17.91 %, 0.23, 1.02, and 0.03, respectively. We found that the average SR of Chinese lakes presents an obvious spatial pattern of high in the west and low in the east due to the difference in human activity intensity and the natural geographical environment. Additionally, we found that the average SR of Chinese lakes from 1986 to 2021 decreased at a rate of - 0.06/10 years, of which 64.37 % of lakes decreased significantly, 15.42 % of lakes had no significant change, and only 20.20 % of lakes increased. The widespread decrease in the average SR indicates that the increasing human activity discharge of terrestrial organic matter has had an important impact on the source composition of the CDOM in Chinese lakes. Our results provide a new resource for remote sensing monitoring of CDOM sources and important insights into lake carbon cycling under the influence of ongoing human activities.

Sediment Bacteria in the Alpine Lake Sayram: Vertical Patterns in Community Composition.

Bacterial communities inhabiting alpine lakes are essential to our understanding of ecosystem processes in a changing climate, but little has been reported about the vertical patterns of sediment bacterial communities in alpine lakes. To address this knowledge gap, we collected the 100 cm long sediment core from the center of Lake Sayram, the largest alpine lake in Xinjiang Uygur autonomous area, China, and used 16S rRNA gene-targeted amplicon sequencing to examine the bacterial populations. The results showed that bacterial diversity, as estimated by the Shannon index, was highest at the surface (6.9849 at 0-4 cm) and gradually decreased with depth up to 3.9983 at 68-72 cm, and then increased to 5.0927 at 96-100 cm. A total of 56 different phyla and 1204 distinct genera were observed in the sediment core of Lake Sayram. The bacterial community structure in the sediment samples from the various layers was dissimilar. The most abundant phyla in alpine Lake Sayram were Proteobacteria, Firmicutes, and Planctomycetes, accounting for 73%, 6%, and 4% of the total reads, respectively; the most abundant genera were Acinetobacter, Hydrogenophaga, and Pseudomonas, accounting for 18%, 12%, and 8% of the total reads, respectively. Furthermore, the relative abundance of Acinetobacter increased with sediment depth, while the relative abundance of Hydrogenophaga and Pseudomonas decreased with sediment depth. Our findings indicated that the nitrate-reducing bacteria (Acinetobacter, Hydrogenophaga, and Pseudomonas) may be prevalent in the sediment core of Lake Sayram. Canonical correspondence analysis showed that carbonate and total organic carbon (TOC) may be the main environmental factors affecting the vertical patterns of bacterial community composition (BCC) in the sediment of Lake Sayram. This work significantly contributes to our understanding of the BCC of sediments from alpine lakes in arid and semiarid regions.

Controls of thermal response of temperate lakes to atmospheric warming.

Atmospheric warming heats lakes, but the causes of variation among basins are poorly understood. Here, multi-decadal profiles of water temperatures, trophic state, and local climate from 345 temperate lakes are combined with data on lake geomorphology and watershed characteristics to identify controls of the relative rates of temperature change in water (WT) and air (AT) during summer. We show that differences in local climate (AT, wind speed, humidity, irradiance), land cover (forest, urban, agriculture), geomorphology (elevation, area/depth ratio), and water transparency explain >30% of the difference in rate of lake heating compared to that of the atmosphere. Importantly, the rate of lake heating slows as air warms (P < 0.001). Clear, cold, and deep lakes, especially at high elevation and in undisturbed catchments, are particularly responsive to changes in atmospheric temperature. We suggest that rates of surface water warming may decline relative to the atmosphere in a warmer future, particularly in sites already experiencing terrestrial development or eutrophication.

Macroinvertebrate Response to Internal Nutrient Loading Increases in Shallow Eutrophic Lakes.

In eutrophic lakes, even if external loading is controlled, internal nutrient loading delays the recovery of lake eutrophication. When the input of external pollutants is reduced, the dissolved oxygen environment at the sediment interface improves in a season without algal blooms. As an important part of lake ecosystems, macroinvertebrates are sensitive to hypoxia caused by eutrophication; however, how this change affects macroinvertebrates is still unknown. In this study, we analysed the monitoring data of northern Lake Taihu from 2007 to 2019. After 2007, the external loading of Lake Taihu was relatively stable, but eutrophication began to intensify after 2013, and the nutrients in the sediments also began to decline, which was related to the efficient use of nutrients by algal blooms. The community structure and population density of macroinvertebrates showed different responses in different stages. In particular, the density of oligochaetes and the Shannon-Wiener index showed significant differences in their response to different stages, and their sensitivity to eutrophication was significantly reduced. Under eutrophication conditions dominated by internal loading, frequent hypoxia occurs at the sediment interface only when an algal bloom erupts. When there is no bloom, the probability of sediment hypoxia is significantly reduced under the disturbance of wind. Our results indicate that the current method for evaluating lake eutrophication based on oligochaetes and the Shannon-Wiener diversity index may lose its sensitivity.

Toxins from harmful algal blooms: How copper and iron render chalkophore a predictor of microcystin production.

Research on harmful algal blooms has focused on macronutrients, yet recent research increasingly indicates that understanding micronutrient roles is also important in the development of effective environmental management interventions. Here, we report results on metallophore production from mesocosms amended with copper and iron (enzymatic co-factors in photosynthetic electron transport) to probe questions of how cyanobacteria navigate the divide between copper nutrition, copper toxicity, and issues with iron bioavailability. These experiments utilized Microcystis, Chlorella and Desmodesmus spp., in mono- and mixed-cultures in lake water from a large, hypereutrophic lake (Taihu, China). To initiate experiments, copper and iron amendments were added to mesocosms containing algae that had been acclimated to achieve a state of copper and iron limitation. Mesocosms were analyzed over time for a range of analytes including algal growth parameters, algal assemblage progression, copper/iron concentrations and biomolecule production of chalkophore, siderophore and total microcystins. Community Trajectory Analysis and other multivariate methods were used for analysis resulting in our findings: 1) Microcystis spp. manage copper/iron requirements though a dynamically phased behavior of chalkophore/siderophore production according to their copper and iron limitation status (chalkophore correlates with Cu concentration, R2 = 0.99, and siderophore correlates with the sum of Cu and Fe concentrations, R2 = 0.98). 2) A strong correlation was observed between the production of chalkophore and the cyanobacterial toxin microcystin (R2 = 0.76)-Chalkophore is a predictor of microcystin production. 3) Based on our results and literature, we posit that Microcystis spp. produces microcystin in response to copper/iron availability to manage photosystem productivity and effect an energy-saving status. Results from this work underscore the importance of micronutrients in influencing harmful algal bloom progression and represents a major advance in understanding the ecological function for the cyanobacterial toxin microcystin as a hallmark of micronutrient limitation stress.

The unprecedented 2022 extreme summer heatwaves increased harmful cyanobacteria blooms.

Heatwaves are increasing and expected to intensify in coming decades with global warming. However, direct evidence and knowledge of the mechanisms of the effects of heatwaves on harmful cyanobacteria blooms are limited and unclear. In 2022, we measured chlorophyll-a (Chla) at 20-s intervals based on a novel ground-based proximal sensing system (GBPSs) in the shallow eutrophic Lake Taihu and combined in situ Chla measurements with meteorological data to explore the impacts of heatwaves on cyanobacterial blooms and the potential relevant mechanisms. We found that three unprecedented summer heatwaves (July 4-15, July 22-August 16, and August 18-23) lasting a total of 44 days were observed with average maximum air temperatures (MATs) of 38.1 ± 1.9 °C, 38.7 ± 1.9 °C, and 40.2 ± 2.1 °C, respectively, and that these heatwaves were characterized by high air temperature, strong PAR, low wind speed and rainfall. The daily Chla significantly increased with increasing MAT and photosynthetically active radiation (PAR) and decreasing wind speed, revealing a clear promotion effect on harmful cyanobacteria blooms from the heatwaves. Moreover, the combined effects of high temperature, strong PAR and low wind, enhanced the stability of the water column, the light availability and the phosphorus release from the sediment which ultimately boosted cyanobacteria blooms. The projected increase in heatwave occurrence under future climate change underscores the urgency of reducing nutrient input to eutrophic lakes to combat cyanobacteria growth and of improving early warning systems to ensure secure water management.

Relationship between anthropogenic factors and freshwater quality in Hainan Province, south China.

Water resource security directly or indirectly affects the development of society, economy, and the environment, and is of massive significance for regional sustainable development. This study addresses whether anthropogenic activities, especially from tourism, significantly affect the freshwater quality in Hainan Province, China. The freshwater quality in Hainan Province was generally good in 2012 to 2015 (at level II, GB3838-2002). Agriculture, fishery, animal husbandry, and chemical oxygen demand discharge mainly affect freshwater quality in the Nandu and Changhua rivers. Water quality in Wanquan River is more susceptible to tourism in comparison with the Nandu and Changhua rivers. DO content in the Wanquan River fluctuated greatly. It remains necessary to closely monitor negative changes in water quality due to increasing tourism, especially in Wanquan River and eastern Hainan Province. The developed radial basis function neural network shows that the changes in water quality are predicted accurately in comparison with experimental values in the present study. Our results suggested that current anthropogenic factors had a modest effect on water quality on Hainan Island, while tourism had a perceptible effect in eastern Hainan. Our findings provide a reference for the interplay of water quality, people's livelihood, and economic development (tourism and port construction) in Hainan Province.

Climate change drives rapid warming and increasing heatwaves of lakes.

Climate change could seriously threaten global lake ecosystems by warming lake surface water and increasing the occurrence of lake heatwaves. Yet, there are great uncertainties in quantifying lake temperature changes globally due to a lack of accurate large-scale model simulations. Here, we integrated satellite observations and a numerical model to improve lake temperature modeling and explore the multifaceted characteristics of trends in surface temperatures and lake heatwave occurrence in Chinese lakes from 1980 to 2100. Our model-data integration approach revealed that the lake surface waters have warmed at a rate of 0.11 °C 10a-1 during the period 1980-2021, being only half of the pure model-based estimate. Moreover, our analysis suggested that an asymmetric seasonal warming rate has led to a reduced temperature seasonality in eastern plain lakes but an amplified one in alpine lakes. The durations of lake heatwaves have also increased at a rate of 7.7 d 10a-1. Under the high-greenhouse-gas-emission scenario, lake surface temperature and lake heatwave duration were projected to increase by 2.2 °C and 197 d at the end of the 21st century, respectively. Such drastic changes would worsen the environmental conditions of lakes subjected to high and increasing anthropogenic pressures, posing great threats to aquatic biodiversity and human health.

Climate Change Causes Salinity To Become Determinant in Shaping the Microeukaryotic Spatial Distribution among the Lakes of the Inner Mongolia-Xinjiang Plateau.

Climate change greatly affects lake microorganisms in arid and semiarid zones, which alters ecosystem functions and the ecological security of lakes. However, the responses of lake microorganisms, especially microeukaryotes, to climate change are poorly understood. Here, using 18S ribosomal RNA (rRNA) high-throughput sequencing, we investigated the distribution patterns of microeukaryotic communities and whether and how climate change directly or indirectly affected the microeukaryotic communities on the Inner Mongolia-Xinjiang Plateau. Our results showed that climate change, as the main driving force of lake change, drives salinity to become a determinant of the microeukaryotic community among the lakes of the Inner Mongolia-Xinjiang Plateau. Salinity shapes the diversity and trophic level of the microeukaryotic community and further affects lake carbon cycling. Co-occurrence network analysis further revealed that increasing salinity reduced the complexity but improved the stability of microeukaryotic communities and changed ecological relationships. Meanwhile, increasing salinity enhanced the importance of deterministic processes in microeukaryotic community assembly, and the dominance of stochastic processes in freshwater lakes transformed into deterministic processes in salt lakes. Furthermore, we established lake biomonitoring and climate sentinel models by integrating microeukaryotic information, which would provide substantial improvements to our predictive ability of lake responses to climate change. IMPORTANCE Our findings have important implications for understanding the distribution patterns and the driving mechanisms of microeukaryotic communities among the lakes of the Inner Mongolia-Xinjiang Plateau and whether and how climate change directly or indirectly affects microeukaryotic communities. Our study also establishes the groundwork to use the lake microbiome for the assessment of aquatic ecological health and climate change, which is critical for ecosystem management and for projecting the ecological consequences of future climate warming.

Bloom-induced internal release controlling phosphorus dynamics in large shallow eutrophic Lake Taihu, China.

High phosphorus (P) concentrations are commonly observed in lakes during algal blooms despite massive efforts on external nutrient reduction. However, the knowledge about the relative contribution of internal P loading linked with algal blooms on lake phosphorus (P) dynamics remains limited. To quantify the effect of internal loading on P dynamics, we conducted extensive spatial and multi-frequency nutrient monitoring from 2016 to 2021 in Lake Taihu, a large shallow eutrophic lake in China, and its tributaries (2017-2021). The in-lake P stores (ILSP) and external loading were estimated and then internal P loading was quantified from the mass balance equation. The results showed that the in-lake total P stores (ILSTP) ranged from 398.5 to 1530.2 tons (t), and exhibited a dramatic intra- and inter-annual variability. The annual internal TP loading released from sediment ranged from 1054.3 to 1508.4 t, which was equivalent to 115.6% (TP loading) of the external inputs on average, and responsible for the fluctuations of ILSTP on a weekly scale. High-frequency observations exemplified that ILSTP increased by 136.4% during algal blooms in 2017, while by only 47.2% as a result of external loading after heavy precipitation in 2020. Our study demonstrated that both bloom-induced internal loading and storm-induced external loading are likely to run counter significantly to watershed nutrient reduction efforts in large shallow lakes. More importantly, bloom-induced internal loading is higher than storm-induced external loading over the short term. Given the positive feedback loop between internal P loadings and algal bloom in eutrophic lakes, which explains the significant fluctuation of P concentration while nitrogen concentration decreased. It is emphasized that internal loading and ecosystem restoration are unignorable in shallow lakes, particularly in the algal-dominated region.

Atmospheric Reactive Nitrogen Deposition from 2010 to 2021 in Lake Taihu and the Effects on Phytoplankton.

The effects of nitrogen deposition reduction on nutrient loading in freshwaters have been widely studied, especially in remote regions. However, understanding of the ecological effects is still rather limited. Herein, we re-estimated nitrogen deposition, both of wet and dry deposition, in Lake Taihu with monthly monitoring data from 2010 to 2021. Our results showed that the atmospheric deposition of reactive nitrogen (namely NH4+ and NO3-) in Lake Taihu was 4.94-11.49 kton/yr, which equaled 13.9%-27.3% of the riverine loading. Dry deposition of NH4+ and NO3- contributed 53.1% of the bulk deposition in Lake Taihu. Ammonium was the main component of both wet and dry deposition, which may have been due to the strong agriculture-related activities around Lake Taihu. Nitrogen deposition explained 24.9% of the variation in phytoplankton community succession from 2010 to 2021 and was the highest among all the environmental factors. Atmospheric deposition offset the effects of external nitrogen reduction during the early years and delayed the emergence of nitrogen-fixing cyanobacterial dominance in Lake Taihu. Our results implied that a decrease in nitrogen deposition due to a reduction in fertilizer use, especially a decrease in NH4+ deposition, could limit diatoms and promote non-nitrogen-fixing cyanobacterial dominance, followed by nitrogen-fixing taxa. This result was also applied to other shallow eutrophic lakes around the middle and lower reaches of the Yangtze River, where significant reduction of fertilizer use recorded during the last decades.