The influence of changes in wind patterns on the areal extension of surface cyanobacterial blooms in a large shallow lake in China

Spatiotemporal changes in chlorophyll-a concentration in China's lakes and its driving factors

This study provides a comprehensive analysis of the temporal and spatial variations in chlorophyll-a (Chl-a) concentrations across 524 lakes in China from 2007 to 2016, leveraging extensive water quality monitoring data to identify the key drivers of these changes. Our results indicate a general decline in Chl-a concentrations, suggesting a mitigation of eutrophication. However, significant regional and seasonal disparities persist, reflecting varying ecological conditions and anthropogenic influences. Elevated Chl-a concentrations were predominantly observed in regions with intensive agricultural and urban areas, such as the middle and lower reaches of the Yangtze River, the Pearl River Delta, and the North China Plain. In contrast, lower concentrations were recorded in areas with extensive forest and grassland cover, such as the northeast and southwest. Multiple linear regression analysis revealed that ammonia nitrogen (NH3-N) and chemical oxygen demand (CODMn) were the primary factors influencing Chl-a levels during the growing season, while water temperature (W-T), CODMn, and pH had greater impacts in the non-growing season. Categorized according to the key factors influencing Chl-a concentration, 52 lakes were divided into 7 categories, and future Chl-a concentrations were projected using data from the China National Environmental Monitoring Centre and the China Environmental Status Bulletin. Specifically, we estimate a 3.060% annual decrease in CODMn and a 2.748% annual decrease in NH3-N, total nitrogen (TN), and total phosphorus (TP), alongside a 0.350% annual increase in water temperature. These projections suggest that while most lakes are expected to see reductions in Chl-a concentrations, some CODMn-sensitive and water temperature-sensitive lakes may still experience increases, underscoring the complexity of interactions between multiple environmental factors. To address these dynamics, we recommend targeted management strategies, including reducing nutrient and organic matter inputs, enhancing ecological protection measures, and closely monitoring temperature fluctuations to mitigate the risk of algal blooms and maintain lake health.

How temperature and meteorological conditions trigger algal blooms on tropical reefs

Agglomerations of macroalgae have increased globally due to changing oceanic conditions, leading to a rise in studies of blooms driven by socio-economic and ecological impacts. Rhizoclonium-like macroalgae blooms have been reported in estuaries, but their occurrence on tropical reefs remains unexplored. This study, conducted between 2005 and 2018, documents the seasonal occurrence of Rhizoclonium-like blooms on reefs and identifies key environmental drivers. These blooms, first recorded in 2006 and becoming more frequent by 2010, occur annually between May and August. The algae form carpets near the substrate, interacting with organisms like reef-building corals, octocorals, ascidians, and sponges. Statistical analysis links the blooms to increased atmospheric pressure and a wider temperature range. The blooms are not influenced by upwelling or land-based nutrients, suggesting meteorological and temperature factors as key drivers. This is the first documented occurrence of large Rhizoclonium-like blooms on tropical reefs, highlighting the need for further study amid global environmental change.

Spatiotemporal dynamics of cyanobacterial blooms: Integrating machine learning and feature selection techniques with uncrewed aircraft systems and autonomous surface vessel data

Cyanobacterial blooms pose significant threats to aquatic ecosystems and public health due to their ability to release harmful toxins, degrade water quality, disrupt aquatic habitats, and endanger human and animal health through contact or consumption of contaminated water. Monitoring phycocyanin (PC), a pigment unique to cyanobacteria, offers a reliable method for detecting and quantifying these blooms, enabling timely interventions to mitigate their impacts. This study aimed to evaluate ten machine learning algorithms (MLAs) for assessing the spatiotemporal variations of cyanobacterial concentrations over an oyster reef in the Western Mississippi Sound (WMS) using remotely sensed imagery from uncrewed aircraft systems (UAS) and in-situ PC concentrations measured by an autonomous surface vessel (ASV). The study further investigated the influence of river discharge and climatic variables on cyanobacterial concentrations using a time-series of cyanobacteria maps. To derive the most accurate PC retrieval model, a comprehensive set of 85 features was initially generated, including individual spectral bands, band ratios, multiple vegetation indices, and three-band indices. Feature selection was performed using a two-step approach that combined Sequential Backward Floating Selection (SBFS) and Exhaustive Feature Selection (EFS). SBFS was first used to iteratively remove features and optimize model performance, while EFS evaluated all possible combinations of the features identified by SBFS to select the best subset. Among the ten MLAs tested, Extreme Gradient Boosting emerged as the top-performing model, achieving an R2 of 0.835, a root mean square deviation of 0.419 μg/l, an unbiased mean absolute relative difference of 0.176 μg/l, and an average percentage difference of 18.072 % in retrieving PC concentration. The novelty of this study lies in its data-driven approach to identifying the most suitable machine learning algorithm and feature subsets for PC retrieval, thereby enhancing the accuracy and robustness of the developed algorithm. The time-series analysis revealed substantial variations in cyanobacterial concentration in the WMS from 2018 to 2022. The highest average concentration occurred in 2019, coinciding with the introduction of diverted Mississippi River water through the Bonnet Carré Spillway, which triggered an unprecedented cyanobacterial bloom. Furthermore, the average PC concentration was consistently higher during the summer months, likely due to elevated air temperatures and increased sunlight promoting cyanobacterial growth. The methodology developed in this study improves the quantitative monitoring of cyanobacterial blooms using UAS imagery and provides valuable insights for future water quality monitoring initiatives in other regions.

A dataset of trophic state index for nation-scale lakes in China from 40-year Landsat observations

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.

Assessment of in-situ monitoring and tracking the vertical migration of cyanobacterial blooms using LISST-HAB

Cyanobacterial harmful algal blooms (cyanoHABs) are becoming increasingly common in aquatic ecosystems worldwide. However, their heterogeneous distributions make it difficult to accurately estimate the total algae biomass and forecast the occurrence of surface cyanoHABs by using traditional monitoring methods. Although various optical instruments and remote sensing methods have been employed to monitor the dynamics of cyanoHABs at the water surface (i.e., bloom area, chlorophyll a), there is no effective in-situ methodology to monitor the dynamic change of cell density and integrated biovolume of algae throughout the water column. In this study, we propose a quantitative protocol for simultaneously measurements of multiple indicators (i.e., biovolume concentration, size distribution, cell density, and column-integrated biovolume) of cyanoHABs in water bodies by using the laser in-situ scattering and transmissometry (LISST) instrument. The accuracy of measurements of the biovolume and colony size of algae was evaluated and exceeded 95% when the water bloom was dominated by cyanobacteria. Furthermore, the cell density of cyanobacteria was well estimated based on total biovolume and mean cell volume measured by the instrument. Therefore, this methodology has the potential to be used for broader applications, not only to monitor the spatial and temporal distribution of algal biovolume concentration but also monitor the vertical distribution of cell density, biomass and their relationship with size distribution patterns. This provides new technical means for the monitoring and analysis of algae migration and early warning of the formation of cyanoHABs in lakes and reservoirs.

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.

Daily process and key characteristics of phytoplankton bloom during a low-water level period in a large subtropical reservoir bay

Reservoirs, heavily influenced by artificial management, often harbor phytoplankton assemblages dominated by cyanobacteria or dinoflagellates, triggering significant changes in aquatic ecosystems. However, due to limited sampling frequency and insufficient attention to species composition, the bloom processes and key characteristics of phytoplankton community structure have not been systematically elucidated. During the low-water level period when blooms are most likely to occur (June to September) in a tributary bay of the Three Gorges Reservoir, daily sampling was conducted to investigate phytoplankton community composition, identify significant environmental factors, and evaluate important structure characteristics of phytoplankton community. The results showed that Microcystis aeruginosa maintained a clear dominance for almost a month in stage 1, with low Shannon and evenness but a high dominance index. Phytoplankton total density and biomass decreased drastically in stage 2, but Microcystis aeruginosa still accounted for some proportion. The highest Shannon and evenness but the lowest dominance index occurred in stage 3. Peridiniopsis niei occurred massively in stage 4, but its dominant advantages lasted only one to two days. NH4-N was responsible for the dominance of Microcystis aeruginosa, while TP and PO4-P was responsible for the dominance of Peridiniopsis niei; however, precipitation contributed to their drastic decrease or disappearance to some extent. The TN : TP ratio could be considered as an important indicator to determine whether Microcystis aeruginosa or Peridiniopsis niei dominated the phytoplankton community. Throughout the study period, physiochemical factors explained more variation in phytoplankton data than meteorological and hydrological factors. Pairwise comparisons revealed an increase in average β diversity with stage progression, with higher β diversities based on abundance data than those based on presence/absence data. Repl had a greater effect on β diversity differences based on presence/absence data, whereas RichDiff had a greater effect on β diversity differences based on species abundance data. Co-occurrence networks for stage 1 showed the most complex structure, followed by stage 4, while the network for stage 3 was relatively sparse, although the overall community division remained compact. This study provides a useful attempt to explore the status and changes in phytoplankton community structure during the bloom process through high-resolution investigation.

Dynamics of Microcystis surface scum formation under different wind conditions: the role of hydrodynamic processes at the air-water interface

Due to climate change, Microcystis blooms occur at increasing frequencies in aquatic ecosystems worldwide. Wind-generated turbulence is a crucial environmental stressor that can vertically disperse the Microcystis surface scum, reducing its light availability. Yet, the interactions of Microcystis scum with the wind-generated hydrodynamic processes, particularly those at the air-water interface, remain poorly understood. Here, we explore the response of Microcystis (including colony size and migration dynamics) to varying magnitudes and durations of intermittent wind disturbances in a mesocosm system. The flow velocities, size of Microcystis colonies, and the areal coverage of the water surface by scum were measured through video observations. Our results demonstrate that low wind speeds increase colony size by providing a stable condition where Microcystis forms a scum layer and aggregates into large colonies at the air-water interface. In contrast, wind disturbances disperse scum and generate turbulence, resulting in smaller colonies with higher magnitudes of wind disturbance. We observed that surface scum can form rapidly following a long period (6 h) of high-magnitude (4.5 m s-1) wind disturbance. Furthermore, our results indicate reduced water surface tension caused by the presence of Microcystis, which can decrease surface flow velocity and counteract wind-driven mixing. The reduced surface tension may also drive lateral convection at the water surface. These findings suggest that Microcystis reduces surface tension, likely by releasing surface-active materials, as an adaptive response to various wind conditions. This could result in an increased rate of surface scum re-formation under wind conditions and potentially facilitate the lateral expansion of scum patches during weak wind periods. This study reveals new insights into how Microcystis copes with different wind conditions and highlights the importance of the air-water interface for Microcystis scum dynamics.

Temporal characteristics and trends of nitrogen loadings in lake Taihu, China and its influencing mechanism at multiple timescales

Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO3--N) and ammonium (NH4+-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. The validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH4+-N and NO3--N variations was 7.318 ± 3.876 (g/m2/day) and 0.0275 ± 0.222 (g/m2/day), respectively. The monthly analysis showed NH4+-N and NO3-N range from 2.04 to 12.04 (g/m2/day) and 0.0008 to 0.064 (g/m2/day), respectively. The magnitude NH4+-N and NO3--N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH4+-N and NO3--N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH4+-N and NO3-N were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation.

Urbanization shifts long-term phenology and severity of phytoplankton blooms in an urban lake through different pathways

Climate change can induce phytoplankton blooms (PBs) in eutrophic lakes worldwide, and these blooms severely threaten lake ecosystems and human health. However, it is unclear how urbanization and its interaction with climate impact PBs, which has implications for the management of lakes. Here, we used multi-source remote sensing data and integrated the Virtual-Baseline Floating macroAlgae Height (VB-FAH) index and OTSU threshold automatic segmentation algorithm to extract the area of PBs in Lake Dianchi, China, which has been subjected to frequent PBs and rapid urbanization in its vicinity. We further explored long-term (2000-2021) trends in the phenological and severity metrics of PBs and quantified the contributions from urbanization, climate change, and also nutrient levels to these trends. When comparing data from 2011-2021 to 2000-2010, we found significantly advanced initiation of PBs (28.6 days) and noticeably longer duration (51.9 days) but an insignificant trend in time of disappearance. The enhancement of algal nutrient use efficiency, likely induced by increased water temperature and reduced nutrient concentrations, presumably contributed to an earlier initiation and longer duration of PBs, while there was a negative correlation between spring wind speed and the initiation of PBs. Fortunately, we found that both the area of the PBs and the frequency of severe blooms (covering more than 19.8 km2 ) demonstrated downward trends, which could be attributed to increased wind speed and/or reduced nutrient levels. Moreover, the enhanced land surface temperature caused by urbanization altered the thermodynamic characteristics between the land and the lake, which, in turn, possibly caused an increase in local wind speed and water temperature, suggesting that urbanization can differently regulate the phenology and severity of PBs. Our findings have significant implications for the understanding of the impacts of urbanization on PB dynamics and for improving lake management practices to promote sustainable urban development under global change.

Eutrophication control of large shallow lakes in China

Large shallow lake refers to a polymictic system that is often well mixed without stratification during summer. Similar to a small and deep lake, a large and shallow lake has a high nutrient retention rate. Differing from a small and deep lake, it has an extensive sediment-water interface and internal loading from sediment, which has led to high susceptibility to eutrophication. There are many large and shallow freshwater lakes in the middle and lower Yangtze River (MLYR), China, experienced eutrophication and cyanobacteria blooms. To address this issue, a variety of methods focused on in-lake physical and biogeochemical processes was explored. The main gains of these studies included: (1) shallow lakes in the floodplain of the Yangtze River are prone to eutrophication because of their high trophic conditions; (2) wind-induced waves determine sediment resuspension, downward dissolved oxygen penetration, and upward soluble reactive nutrient mobilization, while wind-driven currents regulate the spatial distribution of water quality metrics and algal blooms; (3) the low P loss of shallow lakes via sedimentation and high N loss via denitrification lead to a low N:P ratio and N and P colimitation, which demonstrated the significance of dual N and P reduction for eutrophication control in shallow lakes; (4) extensive submerged macrophyte could suppress internal loading in large, shallow waters, but nutrient loading must be reduced and water clarity must be increased; and (5) climate warming promotes cyanobacterial blooms through positive feedback to exacerbate eutrophication in shallow lakes. The lack of action to address the challenges of non-point source pollution and internal loading from the sediment has led to limited effectiveness of eutrophication control in large shallow lakes under climate warming. In the future, the management of large shallow eutrophic lakes in China must combine social sciences (economic development) with natural technology (pollution reduction) to achieve sustainability.

Nutrient reduction mitigated the expansion of cyanobacterial blooms caused by climate change in Lake Taihu according to Bayesian network models

Although nutrient reduction has been used for lake eutrophication mitigation worldwide, the use of this practice alone has been shown to be less effective in combatting cyanobacterial blooms, primarily because of climate change. In addition, quantifying the climate change contribution to cyanobacterial blooms is difficult, further complicating efforts to set nutrient reduction goals for mitigating blooms in freshwater lakes. This study employed a continuous variable Bayesian modeling framework to develop a model to predict spring cyanobacterial bloom areas and frequencies (the responses) using nutrient levels and climatic factors as predictors. Our results suggested that both spring climatic factors (e.g., increasing temperature and decreasing wind speed) and nutrients (e.g., total phosphorus) played vital roles in spring blooms in Lake Taihu, with climatic factors being the primary drivers for both bloom areas and frequencies. Climate change in spring had a 90% probability of increasing the bloom area from 35 km² to 180 km² during our study period, while nutrient reduction limited the bloom area to 170 km², which helped mitigate expansion of cyanobacterial blooms. For lake management, to ensure a 90% probability of the mean spring bloom areas remaining under 154 km² (the 75th percentile of the bloom areas in spring), the total phosphorus should be maintained below 0.073 mg·L^-1 under current climatic conditions, which is a 46.3% reduction from the current level. Our modeling approach is an effective method for deriving dynamic nutrient thresholds for lake management under different climatic scenarios and management goals.

A critical review of operational strategies for the management of harmful algal blooms (HABs) in inland reservoirs

Occurrences of freshwater harmful algal blooms (HABs) are increasing on a global scale, largely in part due to increased nutrient input and changing climate patterns. While reservoir management strategies that can influence phytoplankton are known, there is no published guideline or protocol for the management of harmful algal blooms. There is a need to establish what factors are the predominant drivers of blooms, and how common reservoir management strategies specifically influence each factor. The following literature review seeks to establish the benefits and drawbacks of operational management strategies that currently exist. The main focus is altering hydrodynamic conditions (hypolimnetic withdrawals, surface flushing, pulsed inflow, artificial mixing), in order to induce environmental changes within the reservoir itself. Since excess nutrients are one of the biggest contributors to worsening bloom conditions, internal nutrient dynamics and reduction are also discussed. Additionally, we review the predominant seasonal factors (stratification, light, temperature, and wind) that affect likelihood of bloom occurrence and duration. The ultimate objective of this review is to increase understanding of the relationships between HAB drivers and reservoir operations in order to inform the development of data, modeling, and management strategies for the prevention and mitigation of blooms.

A sediment diagenesis model on sediment oxygen demand in managing eutrophication on Taihu, China

Blue-green algae (CyanoHABs), photosynthetic bacteria that create a harmful aquatic environment, have been a trending issue on Taihu for over a decade. CyanoHABs adapt to varying climatic changes, which explains why the problem on Taihu still thrives. One major drive that keeps the algae is Sediment Oxygen Demand (SOD). In this paper, seasonal and spatial variations of SOD that contribute immensely to nutrient growth in Lake Taihu were done using the Environmental Fluid Dynamics Code (EFDC). The results were analyzed based on Nitrogenous SOD (NSOD) and Total SOD (TSOD). Summer results ranged from - 0.05754 to - 0.0826 (- 0.75658 to - 0.83902) (g/m²/day) and Winter values ranged from - 0.3022 to - 0.40171 (- 1.34486 to - 1.48856) (g/m²/day) indicate a gradual decrease in NSOD (TSOD) values respectively. Relatively higher values in summer are attributed to warmer surface water which sets up thermal stratification to increase the internal loading of nitrogen. Lower winter values are related to inverse stratification, where lower oxygen concentration decreases the SOD to trigger ammonium accumulation in the water column. NSOD (TSOD) values for Autumn results ranged from - 0.1039 to - 0.24786 (- 0.96251 to - 1.39454) (g/m²/day) and Spring values of - 0.43019 to - 0.35959 (- 1.48297 to - 0.54089) (g/m²/day). Transition seasons (i.e., Autumn and Spring) results are impacted by wind mixing that allows dissolved oxygen and nutrients in the whole water column. However, spring values depict a gradual increase in SOD value attributed to spring turnover and gradual stratification, which decrease nutrient concentration. In contrast, decreasing SOD values in autumn are related to mixing, but temperature decreases tend to increase nutrient concentrations. Carbonaceous sediment oxygen demand (CSOD), due to sulfide oxidation, presents high values from the difference between TSOD and NSOD. Based on the high values of CSOD, it is highly recommended that more research on eutrophic Taihu lakes would consider delving into CSOD.

The role of nutrients, wind speed, and rainfall in determining the composition of the algal community of shallow lakes in the Taoge water system, upstream from Lake Taihu, China

Gaining a deeper understanding of factors that influence changes in phytoplankton community has significant implications for shallow lake management. The present study examined changes in the algae community of three shallow eutrophic lakes of the Taoge water system between 2008 and 2018 and the related factors influencing these changes. The composition of the algal community varied significantly during this period with the relative diatom biomass in lakes Changdanghu and Gehu increasing between 2014 and 2016 and again decreasing after 2017. However, relative cyanobacteria biomass initially decreased and later increased; meanwhile, the proportion of biomass of other phyla decreased continuously in the study period. Lake Zhushanhu showed similar trends, although it eventually returned to its initial state with absolute Microcystis dominance. Furthermore, the analysis of driving factors revealed that the concentrations of total nitrogen (TN), nitrate (NO₃), and orthophosphate (PO₄) were significantly associated with a significant increase in Microcystis biomass. Meteorological conditions also influenced changes in total algal and diatom biomasses, which were inversely related to the daily mean and daily maximum wind speeds. Monthly cumulative precipitation was only significantly associated with diatom biomass. Meanwhile, rainfall primarily affected the algal community structure between 2013 and 2017; an increase in the relative biomass of diatoms coincided with increased precipitation. Coordinating nitrogen and phosphorous use within the Taoge water system should improve lake habitat management; a broader perspective in attempts to control global and regional climate change may be needed.

Multivariable integrated risk assessment for cyanobacterial blooms in eutrophic lakes and its spatiotemporal characteristics

Climate change has catalyzed the global expansion of cyanobacterial blooms in eutrophic , lakes and threatens water security. In most studies, the cyanobacterial bloom risk levels in lakes were evaluated using field-collected data from multiple indicators or spatially continuous data from one cyanobacteria-related indicator. Nevertheless, the occurrence of cyanobacterial blooms in lakes has clear spatial heterogeneity and is affected by numerous factors. Therefore, we developed a multivariable integrated risk assessment framework for cyanobacterial blooms in lakes using five spatially continuous datasets to estimate the risk level of cyanobacterial blooms at the pixel scale (250 m). The spatial and temporal variations in cyanobacterial bloom risk levels from May 1, 2002, to October 31, 2020, were investigated for three typical eutrophic lakes in China: Lakes Taihu, Chaohu, and Dianchi. Seasons and regions of high cyanobacterial bloom risk were identified for each lake. Environmental characteristics were discussed. A long-term investigation revealed that owing to its warm climate, the cyanobacterial risk levels in summer and autumn were much higher than those in the other two seasons. At the synoptic scale, Lake Taihu had a lower cyanobacterial bloom risk than Lakes Chaohu and Dianchi. A further comparison found that precipitation, wind speed, and temperature were responsible for the differences in cyanobacterial bloom risk levels among the three lakes. At the pixel scale, the risk map indicated that the cyanobacterial bloom risk levels of Lake Taihu were unevenly distributed, and the cyanobacterial bloom risk of the lakeshore was higher than that of the other subregions. Nutrient levels played the most critical role in the regional differences in cyanobacterial bloom risk levels in a lake. While the differences of cyanobacterial bloom risk levels in three lakes were resulted by the climates. Bloom events were defined and classified as "long-term bloom" or "flash bloom" according to their duration (over or below a year). Overall, this study can assist in advanced water management with a pixel-scale evaluation of cyanobacterial bloom risk levels.

A novel indicator for defining plain urban river network cyanobacterial blooms: resource use efficiency

Increasing eutrophication and climate change have led to heavy cyanobacterial blooms in water diversion sources (e.g., lakes, reservoirs), which can potentially cause algae-bearing water to spread to downstream to an urban river network via diversion channels. Defining the extent of cyanobacterial blooms in an urban river network has become a novel concern in urban river management. In this paper, we investigated the physicochemical and algae community characteristics of a small, closed, urban river network, JiangXinZhou (JXZ), in the Lake Taihu basin. We propose a novel indicator, resource use efficiency (RUE), for defining the extent of cyanobacterial blooms in JXZ, whose recreational drinking water comes entirely from outside diversion sources. The results show that the JXZ's aquatic habitat conditions (mean water temperature, total nitrogen concentration, total phosphorus concentration, and nitrogen to phosphorus ratio) are highly suitable for the proliferation of cyanobacterial biomass during the high-water period. The RUE was used for calculation and shows a strong relationship with algae density, which means that it can be used as an index to define the degree of urban river cyanobacterial blooms. The findings indicate that the risk of cyanobacterial bloom is absent when the RUE is less than 46.81; blooms appear in the water bodies when the RUE reaches up to 106.68. This work provides theoretical support for the sustainable use of regional water resources.

Amplified cyanobacterial bloom is derived by polyphosphate accumulation triggered by ultraviolet light

Cyanobacterial blooms appear more strongly, constantly and globally, yet the positive effect of surface solar ultraviolet radiation (UV) on cyanobacterial bloom in natural freshwater habitats is largely ignored. Here in-situ and laboratory studies were jointly designed to probe the mechanism of cyanobacterial bloom promoted by solar UV light. The results showed that solar UV light is a key trigger factor for the accumulation of total phosphorus, dissolved inorganic phosphorus and polyphosphate (polyP) in blooming cyanobacterial cells. The increase of UV dose induces polyP accumulation to result in the excessive phosphorus uptake of blooming cyanobacteria, which provides sufficient phosphorus for cyanobacterial growth in suitable environment. Solar UV light also can promote the contents of phycocyanin, allophycocyanin, and phycoerythrin, producing sufficient ATP by photosynthesis for polyP synthesis in cyanobacterial cells in lake enviroment. The frequent variations of UV irradiance exposure prompts cyanobacteria to absorb excessive phosphorus from suspended solid or sediment. Cyanobacterial intracellular phosphorus is accumulated for their growth. UV light promotes polyP accumulation in blooming cyanobacterial cells to avoid damage. The adsorption amount of phosphorus increases for exuberant growth and then more surface blooming cyanobacteria are exposed to UV light to absorb ample phosphorus. Thus, the positive feedback occurs in lake water bodies with abundant phosphorus. This amplified cycle of cyanobacterial density and phosphorus due to solar UV light in eutrophic water bodies is analogous to a triode to amplify visible photosynthesis by UV light as a base electric current in the energy flow process in lake environment, therefore, "Cyanobacterial Phosphorus Assimilation Ultraviolet Effect" is used to describe this phenomenon. A new explanation is provided for the continuing proliferating mechanism of cyanobacterial bloom. Besides, a new perspective appears on the outbreak of cyanobacterial blooms in natural eutrophic lake water bodies worldwide.

The Effect of Algicidal and Denitrifying Bacteria on the Vertical Distribution of Cyanobacteria and Nutrients

Algicidal bacteria combined with the ability of aerobic denitrification is considered to be a promising way to control harmful cyanobacterial bloom and remove nitrogen. However, the effect of these bacteria on the vertical distribution of colonial cyanobacteria and nutrients remained unknown. In this study, two algicidal and denitrifying bacteria were respectively co-cultured with the colonial Microcystis aeruginosa to construct the microcosm systems, and then the cyanobacteria number, the ratio of bacterial to cyanobacterial abundance, the content of dissolved nitrogen, phosphorus and organic carbon in different water layers were investigated. The results showed that the distribution difference of Microcystis among the vertical water layers was further enlarged due to the short-term influence of algicidal bacteria Brevundimonas diminuta and Pseudomonas stutzeri. The number of Microcystis in the lower layer was further reduced by the inhibitory effect of the algicidal bacteria. However, there was a dramatic increase in the number of Microcystis in the upper layer, even when the ratio of algicidal bacteria to cyanobacteria increased significantly. B. diminuta and P. stutzeri both greatly promoted the removal of dissolved total nitrogen in the upper and middle layers of cyanobacteria blooming water, but they also boosted the release of dissolved phosphorus in all layers. These results enable us to better understand the possible limitations of algicidal bacteria in their application to control cyanobacteria blooms.

Spatiotemporal heterogeneities and driving factors of water quality and trophic state of a typical urban shallow lake (Taihu, China)

Water quality deterioration and eutrophication of urban shallow lakes are global ecological problems with increasing concern and greater environmental efforts. In this study, spatiotemporal changes of water quality and eutrophication were assessed by trophic level index (TLI), cluster analysis, and spatial interpolation methods in Lake Taihu and its sub-lakes from 2015 to 2019. Results showed that the Taihu had poor water quality and maintained a light-eutropher state overall, mainly astricted by the total nitrogen (TN) and the total phosphorus (TP). All nutrient parameters reached relatively higher concentrations in the northwestern and northern areas. Meiliang Bay was the most polluted and nutrient-rich area. In terms of trend, the Mann-Kendall test highlighted that the TP and chlorophyll-a (Chl-a) concentrations increased significantly while the TN and five-day biochemical oxygen demand (BOD5) decreased. The massive nutrient loads caused by human activity from the northwestern Taihu and the geomorphological characteristic of the north closed bays were the main contributors to the spatial heterogeneity in water quality. The main driving force of the alleviative nitrogen pollution was the declining river inflow nitrogen loading, and phosphorus pollution was affected more by accumulated endogenous pollution and decline in aquatic plants area, as well as closely linked with algae biomass. Further water pollution and eutrophication restoration of Taihu should focus on the nutrient reductions and those heavily polluted closed bays.

Utilization of GOCI data to evaluate the diurnal vertical migration of Microcystis aeruginosa and the underlying driving factors

Cyanobacterial blooms are one of the most severe ecological problems affecting lakes. The vertical migration of cyanobacteria in the water column increases the uncertainty in the formation and disappearance of blooms, which may be closely associated with light, temperature, and wind speed. However, it is difficult to quantitatively evaluate the influencing factors of cyanobacteria vertical movement in natural environment compared to the laboratory experimental environment. Besides, both field survey and laboratory experiment method have the difficulties in determining the diurnal vertical migration of cyanobacteria at the synoptic lake scale. In this study, based on the diurnal dynamics of cyanobacterial bloom intensity (CBI) observed by the Geostationary Ocean Color Imager (GOCI) from 2011 to 2019, the daily variations, floating rate, and sinking rate of Microcystis aeruginosa were calculated in the natural environment. Then, the effects of light, temperature, and wind speed on the vertical migration of M. aeruginosa were analysed from the perspectives of day, night, and season. The results are as follows: the records of three typical patterns of diurnal CBI exhibited strong seasonal variability from the 9-year statistics; at night, the buoyancy recovery rate of cyanobacterial colonies increased with temperature, so that at temperature >15 °C and wind speed <3 m s^-1, CBI reached the maximum of the whole day at 08:16; the sinking rate of M. aeruginosa was positively correlated with the cumulated light energy at both synoptic and pixel scale; the upward migration speed of M. aeruginosa was positively correlated with the maximum wind speed of the day before cyanobacterial bloom. Therefore, the severer cyanobacterial blooms were often observed by satellite images after strong winds. The analysis of diurnal variation, floating rate, and sinking rate of M. aeruginosa will expand our knowledge for further understanding the formation mechanism of cyanobacterial blooms and for improving the accuracy of model simulation to predict the hourly changes in cyanobacterial blooms in Lake Taihu.

Systematic evaluation of management measure effects on the water environment based on the DPSIR-Tapio decoupling model: A case study in the Chaohu Lake watershed, China

Watershed management measures have been widely implemented worldwide to reduce the water quality deterioration in rivers and lakes, which continue to face increasing stresses from human activities. Due to the complexity of influential factors within watersheds, systematic and reliable approaches are urgently needed to evaluate the effects of watershed managerial practices on scientific applications. In this study, the driving force-pressure-state-impact-response (DPSIR) model integrated by Tapio decoupling analysis was established using 30 quantitative indicators to systematically evaluate their effects on overall watershed water environmental health of Chaohu Lake watershed, China, which was under intensive management practices during 2000-2019. The DPSIR model outcomes revealed that the driving force subsystem with 7 indictors accounted for 34.2% of the watershed water environmental health, in which gross domestic product (GDP), gross industrial output value, crop planting and urbanization contributed a larger proportion. Management measure implementation positively improved the watershed water environmental health, with the second largest proportion being 23.4%. During the study period, a trend of simultaneous improvement in the water quality of the rivers and lakes existed. The Tapio decoupling analysis indicated that watershed water quality was weakly decoupled with socioeconomic development and related pressures, and management responses. The response strategy is the main force in alleviating the pressure from socioeconomic development on the watershed water quality. Overall, the method proposed in this study would improve the understanding of watershed management practice effects and provide guidance for future management measure applications.

Environmental controls of harmful cyanobacterial blooms in Chinese inland waters

Harmful cyanobacterial blooms (CyanoHABs) are expanding world-wide, adversely affecting aquatic food production, recreational and tourism activities and safe drinking water supplies. China's inland waters have been increasingly threatened by CyanoHABs during the past several decades. The environmental factors controlling CyanoHABs are highly variable in space and time in China due to significant variations in climate, geography, geological and geochemical conditions among its many regions. Here, we synthesize diverse examples among Chinese water bodies regarding interactive effects of anthropogenic, climatic and geographic drivers influencing CyanoHAB potentials and dynamics in lakes and reservoirs; in order to provide a perspective and integrative approach to mitigating CyanoHABs. In China's many shallow water bodies, water quality is highly susceptible to human activity and to changing climatic and hydrological conditions, when compared to deeper lakes. Rapid increases in population, economic activity, and wastewater have accelerated CyanoHABs in China since 1980s, especially in the heavily urbanized, agricultural and industrial regions in the middle and lower Yangtze River basins. Climatic changes have provided an additional catalyst for expansion of CyanoHABs. In particular, rising spring temperatures have accelerated the onset and proliferation of Microcystis spp, blooms in the middle and lower reaches of Yangtze River basin. Large hydroelectric and water supply projects, like the Three Gorges Reservoir (TGR), have altered hydrological regimes, and have led to an increase of CyanoHABs in reservoirs and tributaries due to increases in water residence times. Manipulating water level fluctuations in the TGR may prove useful for controlling CyanoHAB in its tributary bays. Overall,CyanoHAB mitigation strategies will have to incorporate both N and P input reductions in these shallow systems. Furthermore, nutrient reduction strategies must consider climate change-induced increases in extreme weather events, including more intense rainfall and protracted heat waves and droughts, which can extend the magnitudes and duration of CyanoHABs. Ensuring the maintenance of natural hydrologic connectivity between lakes and rivers is of utmost importance in mitigating CyanoHABs throughout China.

Atmospheric Stilling Promotes Summer Algal Growth in Eutrophic Shallow Lakes

Simple Summary

The variability of chlorophyll a yields per unit nitrogen (Chla/TN), or phosphorus (Chla/TP) and its influencing factors were evaluated in eutrophic shallow Lake Taihu, China. The results indicated warming and longer sunshine hours promoted Chla/TN and Chla/TP in winter months from 2005 to 2017, which may cause severer blooms in winter and spring. However, a more stable water column due to atmospheric stilling and water level elevation mainly led to the increasing Chla/TN and Chla/TP in remaining months from 2005 to 2017, allowing algae to grow better. The results also indicated that water stability promotes algal growth mainly due to improved light availability. As atmospheric stilling is an aspect of global climate changes, this study would affect future algal bloom mitigation efforts in shallow lakes worldwide.

Abstract

Algal blooms are environmental challenges confronting lakes worldwide and are significantly influenced by chlorophyll a yields per unit phosphorus (Chla/TP), or nitrogen (Chla/TN). Here, the influence of inter-annual hydrometeorological variations on Chla/TP and Chla/TN were evaluated in eutrophic shallow Lake Taihu, China. Our results demonstrated significant increases (p < 0.001) in both Chla/TN and Chla/TP from 2005 to 2017, and increased Chla yields during the winter months were mainly correlated with higher water temperature and longer sunshine hours, which may cause severer blooms in winter and spring. In remaining months from 2005 to 2017, typical associations between atmospheric stilling (or water level elevation) and higher Chla yields were observed. The results also indicate that atmospheric stilling and water level elevation significantly (p < 0.001) decreased background turbidity and promoted buoyant cyanobacterial biomass, alleviating phytoplankton light limitation. Given the subtropical location, eutrophic status, and high background turbidity of Lake Taihu, light may be the critical limiting factor for summer phytoplankton growth; thus, improved light availability would promote Chla yields until self-shading caused further light limitations. If the mechanism is general, promoting the effect of atmospheric stilling on annual peak Chla in shallow lakes may be greatly underestimated, and our finding will affect future bloom mitigation efforts in such systems.

Effects of different fluid fields on the formation of cyanobacterial blooms

Cyanobacterial blooms have been attracting more and more attention, and the mechanism is widely studied. However, the effects of fluid fields on the bloom formation were rarely reported. In this study, the effects of fluid fields formed under different external conditions were investigated. The results indicated that low wind speed (3 m/s) was conducive to the formation of cyanobacterial blooms, while high wind speed (6 m/s) was adverse. For low wind speed, an upward fluid field was detected by particle image velocimetry. This fluid field accelerated the algal growth by 58.6%, and improved the buoyancy by up-regulating the genes involved in the synthesis of gas vesicles and extracellular polymeric substances. In addition, the boundary shear stress induced the colony formation of cyanobacteria and improved the aggregation proportion significantly (p < 0.05), which was beneficial to bloom formation. As a result, cyanobacterial blooms are more likely to form on the lake shore under moderate breeze. When wind speed increased to 6 m/s, a downward fluid field was formed, causing algal cells to gather at the bottom and hindering the bloom formation. These results provided a theoretical basis for field researches related to the formation of cyanobacterial blooms and the treatment of cyanobacteria.

The relative importance of environmental factors in predicting phytoplankton shifting and cyanobacteria abundance in regulated shallow lakes

The phytoplankton community can be affected by multiple environmental factors such as climate, meteorology, hydrology, nutrients, and grazing. The complex interactive effects of these environmental factors as well as the resilience of phytoplankton communities further make the prediction of phytoplankton communities' dynamics challenging. In this study, we analyzed multiple environmental factors and their relative importance in predicting both phytoplankton shifting and cyanobacteria abundance in two regulated shallow lakes in central China. Our results indicated that the phytoplankton community in the study areas could be mainly classified into 1. Cryptophyta dominated group, 2. Biologically diverse group, and 3. Cyanobacteria dominated group. The Multinomial Logistic Regression model indicated the Cryptophyta dominated group was sensitive to temperature, while other groups were sensitive to both temperature and nutrients. The interactive effects of temperature and nutrients were synergistic in the cyanobacteria dominated group, while they were antagonistic or minor in other groups. The Negative Binomial Regression model suggested high total phosphorus and low total nitrogen but not temperature were responsible for high cyanobacteria abundance. The conditional plot indicated nutrients affected cyanobacteria abundance more significantly under low wind speeds and lake volume fluctuations, and cyanobacteria abundance in the cyanobacteria dominated group maintained high levels with increasing hydrological dynamics. Our results demonstrated that environmental factors played inconsistently significant roles in different phytoplankton groups, and reducing nutrients could decrease adverse effects of warming and water project constructions. Our models can also be applied to forecast phytoplankton shifting and cyanobacteria abundance in the management of regulated shallow lakes.

Dramatic temporal variations in methane levels in black bloom prone areas of a shallow eutrophic lake

Global lakes serve as a key natural source of methane (CH₄) and suffer from increasing hypoxia due to unprecedented anthropogenic activities and climate change. A black bloom is a temporary hypoxia triggered by a longstanding algal bloom, which facilitates CH₄ production by creating reducing conditions and abundant algae-sourced organic carbon. One-year investigations were conducted to examine temporal CH₄ dynamics in the water and sediment pore water in black bloom prone areas (BBPAs) in Lake Taihu, China, where there had been at least two recorded black bloom events. The CH₄ in the water changed significantly with time (p < 0.001), with the highest concentrations appearing in warm months when an abnormal lower dissolved oxygen content was observed at different sites, which were one to two orders of magnitude higher than other months. Compared with the control site, there were significantly higher CH₄ concentrations in BBPA waters (p < 0.001), which was consistent with the higher CH₄ in the sediment pore water. Methane dynamics in the water showed significant positive correlations with temperature, total phosphorus, total nitrogen, ammonia-N, and soluble reactive phosphorus (p < 0.05), but showed a significant inverse correlation with dissolved oxygen (p < 0.01). Redundancy analysis indicated dissolved oxygen made the largest contribution to CH₄ dynamics in the BBPAs. A significant increase in the CH₄ in water will turn BBPAs into temporary hot spots with substantial CH₄ emissions with the appearance of black blooms. The results provide new insights into understanding future CH₄ dynamics under globally prevailing algal blooms and climate change.

Simulating chlorophyll-a fluorescence changing rate and phycocyanin fluorescence by using a multi-sensor system in Lake Taihu, China

Algal pollution in water sources has posed a serious problem. Estimating algal concentration in advance saves time for drinking water plants to take measures and helps us to understand causal chains of algal dynamics. This paper explores the possibility of building a short-term algal early warning model with online monitoring systems. In this study, we collected high-frequency data for water quality and weather conditions in shallow and eutrophic Lake Taihu by an in situ multi-sensor system (BIOLIFT) combined with a weather station. Extracted chlorophyll-a from water samples and chlorophyll-a fluorescence differentiated according to different algal classeses verified that chlorophyll-a fluorescence continuously measured by BIOLIFT only represent chlorophyll-a of green algae and diatoms. Stepwise linear regression was used to simulate the chlorophyll-a fluorescence changing rate of green algae and diatoms together (ΔChl_a-f%) and phycocyanin fluorescence concentration (blue-green algae) on the water surface layer (CyanoS). The results show that nutrients (total N, NO₃-N, NH₄-N, total P) were not necessary parameters for short-term algal models. ΔChl_a-f % is greatly influenced by the seasons, so seasonal partition of data before modeling is highly recommended. CyanoS_max and ΔChl_a-f% were simulated by only using multi-sensor and meteorological data (R² = 0.73; 0.75). All the independent variables (wave, water temperature, relative humidity, depth, cloud cover) used in the model were measured online and predictable. Wave height is the most important independent variable in the shallow lake. This paper offers a new approach to simulate and predict the algal dynamics, which also can be applied in other surface water.

Lakes in the era of global change: moving beyond single-lake thinking in maintaining biodiversity and ecosystem services

The Anthropocene presents formidable threats to freshwater ecosystems. Lakes are especially vulnerable and important at the same time. They cover only a small area worldwide but harbour high levels of biodiversity and contribute disproportionately to ecosystem services. Lakes differ with respect to their general type (e.g. land-locked, drainage, floodplain and large lakes) and position in the landscape (e.g. highland versus lowland lakes), which contribute to the dynamics of these systems. Lakes should be generally viewed as 'meta-systems', whereby biodiversity is strongly affected by species dispersal, and ecosystem dynamics are contributed by the flow of matter and substances among locations in a broader waterscape context. Lake connectivity in the waterscape and position in the landscape determine the degree to which a lake is prone to invasion by non-native species and accumulation of harmful substances. Highly connected lakes low in the landscape accumulate nutrients and pollutants originating from ecosystems higher in the landscape. The monitoring and restoration of lake biodiversity and ecosystem services should consider the fact that a high degree of dynamism is present at local, regional and global scales. However, local and regional monitoring may be plagued by the unpredictability of ecological phenomena, hindering adaptive management of lakes. Although monitoring data are increasingly becoming available to study responses of lakes to global change, we still lack suitable integration of models for entire waterscapes. Research across disciplinary boundaries is needed to address the challenges that lakes face in the Anthropocene because they may play an increasingly important role in harbouring unique aquatic biota as well as providing ecosystem goods and services in the future.

Bloom-forming toxic cyanobacterium Microcystis: Quantification and monitoring with a high-frequency echosounder

Harmful cyanobacterial blooms pose a serious environmental threat to freshwater lakes and reservoirs. Investigating the dynamics of toxic bloom-forming cyanobacterial genus Microcystis is a challenging task due to its huge spatiotemporal heterogeneity. The hydroacoustic technology allows for rapid scanning of the water column synoptically and has a significant potential for rapid, non-invasive in situ quantification of aquatic organisms. The aim of this work is to develop a reliable cost-effective method for the accurate quantification of the biomass (B) of gas-bearing cyanobacterium Microcystis in water bodies using a high-frequency scientific echosounder. First, we showed that gas-bearing Microcystis colonies are much stronger backscatterers than gas-free phytoplanktonic algae. Then, in the tank experiments, we found a strong logarithmic relationship between the volume backscattering coefficient (s_v) and Microcystis B proxies, such as Microcystis-bound chlorophyll a (Chl a_Micro) and particle volume concentration. The s_v/B ratio remained unchanged over a wide range of B concentrations when the same source of Microcystis material was used. Our measurements in Lake Dianchi (China) also revealed strong logarithmic relationship between s_v and Chl a_Micro. The biomass-calibrated echosounder was used to study the diurnal variability of Microcystis B in the lake. We found a sharp increase in the cyanobacterium B and s_v/Chl a_Micro ratio near the water surface during the daytime and more uniform distribution of these parameters during the nighttime. We argue that the variations in B and s_v/Chl a_Micro ratio could be associated with temporal changes in thermal stratification and turbulent mixing. Our data suggest that the s_v/Chl a_Micro ratio positively correlates with (i) the percentage of larger colonies in population and/or (ii) the content of free gas in cells. The last properties allow Microcystis colonies to attain rapid floating, which enables them to concentrate at the water surface at conducive ambient conditions. The s_v/Chl a_Micro ratio can be a new important variable reflecting the ability of Microcystis colonies to migrate vertically. Monitoring of this ratio may help to determine the early warning threshold for Microcystis scum formation. The proposed acoustic technology for in situ quantification of Microcystis biomass can be a powerful tool for accurate monitoring and assessment of this cyanobacterium at high spatiotemporal resolution in water bodies.

Identifying spatio-temporal dynamics of trace metals in shallow eutrophic lakes on the basis of a case study in Lake Taihu, China

In shallow eutrophic lakes, metal remobilization is closely related to the resuspension and eutrophication. An improved understanding of metal dynamics by biogeochemical processes is essential for effective management strategies. We measured concentrations of nine metals (Cr, Cu, Zn, Ni, Pb, Fe, Al, Mg, and Mn) in water and sediments during seven periods from 2014 to 2018 in northern Lake Taihu, to investigate the metal pollution status, spatial distributions, mineral constituents, and their interactions with P. Moreover, an automatic weather station and online multi-sensor systems were used to measure meteorological and physicochemical parameters. Combining these measurements, we analyzed the controlling factors of metal dynamics. Shallow and eutrophic northern Lake Taihu presents more serious metal pollution in sediments than the average of lakes in Jiangsu Province. We found chronic and acute toxicity levels of dissolved Pb and Zn (respectively), compared with US-EPA "National Recommended Water Quality Criteria". Suspended particles and sediment have been polluted in different degrees from uncontaminated to extremely contaminated according to German pollution grade by LAWA (Bund/Länder-Arbeitsgemeinschaft Wasser). Polluted particles might pose a risk due to high resuspension rate and intense algal activity in shallow eutrophic lakes. Suspended particles have similar mineral constituents to sediments and increased with increasing wind velocity. Al, Fe, Mg, and Mn in the sediment were rarely affected by anthropogenic pollution according to the geoaccumulation index. Among them, Mn dynamics is very likely associated with algae. Micronutrient uptake by algal will affect the migration of metals and intensifies their remobilization. Intensive pollution of most particulate metals were in the industrialized and down-wind area, where algae form mats and decompose. Moreover, algal decomposition induced low-oxygen might stimulate the release of metals from sediment. Improving the eutrophication status, dredging sediment, and salvaging cyanobacteria biomass are possible ways to remove or reduce metal contaminations.

Storm impacts on phytoplankton community dynamics in lakes

In many regions across the globe, extreme weather events such as storms have increased in frequency, intensity, and duration due to climate change. Ecological theory predicts that such extreme events should have large impacts on ecosystem structure and function. High winds and precipitation associated with storms can affect lakes via short-term runoff events from watersheds and physical mixing of the water column. In addition, lakes connected to rivers and streams will also experience flushing due to high flow rates. Although we have a well-developed understanding of how wind and precipitation events can alter lake physical processes and some aspects of biogeochemical cycling, our mechanistic understanding of the emergent responses of phytoplankton communities is poor. Here we provide a comprehensive synthesis that identifies how storms interact with lake and watershed attributes and their antecedent conditions to generate changes in lake physical and chemical environments. Such changes can restructure phytoplankton communities and their dynamics, as well as result in altered ecological function (e.g., carbon, nutrient and energy cycling) in the short- and long-term. We summarize the current understanding of storm-induced phytoplankton dynamics, identify knowledge gaps with a systematic review of the literature, and suggest future research directions across a gradient of lake types and environmental conditions.

Variations in the Distribution of Chl-a and Simulation Using a Multiple Regression Model

Chlorophyll a (Chl-a) is an important indicator of algal biomass in aquatic ecosystems. In this study, monthly monitoring data for Chl-a concentration were collected between 2005 and 2015 at four stations in Meiliang Bay, a eutrophic bay in Lake Taihu, China. The spatiotemporal distribution of Chl-a in the bay was investigated, and a statistical model to relate the Chl-a concentration to key driving variables was also developed. The monthly Chl-a concentration in Meiliang Bay changed from 2.6 to 330.0 μg/L, and the monthly mean Chl-a concentration over 11 years was found to be higher at sampling site 1, the northernmost site near Liangxihe River, than at the three other sampling sites. The annual mean Chl-a concentration fluctuated greatly over time and exhibited an upward trend at all sites except sampling site 3 in the middle of Meiliang Bay. The Chl-a concentration was positively correlated with total phosphorus (TP; r = 0.57, p < 0.01), dissolved organic matter (DOM; r = 0.73, p < 0.01), pH (r = 0.44, p < 0.01), and water temperature (WT; r = 0.37, p < 0.01), and negatively correlated with nitrate (NO3--N; r = -0.28, p < 0.01), dissolved oxygen (DO; r = -0.12, p < 0.01), and Secchi depth (ln(SD); r = -0.11, p < 0.05). A multiple linear regression model integrating the interactive effects of TP, DOM, WT, and pH on Chl-a concentrations was established (R = 0.80, F = 230.7, p < 0.01) and was found to adequately simulate the spatiotemporal dynamics of the Chl-a concentrations in other regions of Lake Taihu. This model provides lake managers with an alternative for the control of eutrophication and the suppression of aggregations of phytoplankton biomass at the water surface.

Automated Subdaily Sampling of Cyanobacterial Toxins on a Buoy Reveals New Temporal Patterns in Toxin Dynamics

Temporal variability of toxins produced by cyanobacteria in lakes is relatively unknown at time scales relevant to public health (i.e., hourly). In this study, a water quality monitoring buoy was outfitted with an automated water sampler taking preserved samples every 6 h for 68.75 days over a drinking water intake. A total of 251 samples were analyzed by tandem mass spectrometry for 21 cyanotoxin congeners in 5 classes producing 5020 data points. Microcystins (MCs) were the most abundant toxins measured (mean ± sd = 3.9 ± 3.3 μg/L) followed by cyanopeptolins (CPs) (1.1 ± 1.5 μg/L), anabaenopeptins (APs) (1.0 ± 0.6 μg/L), anatoxin-a (AT-A) (0.03 ± 0.06 μg/L), and microginin-690 (MG-690) (0.002 ± 0.01 μg/L). Advanced time series analyses uncovered patterns in cyanotoxin production. The velocity of cyanotoxin concentration varied from -0.7 to 0.9 μg/L/h with a maximum positive velocity just prior to peak toxin concentration during nonbloom periods. A backward-looking moving window of variance analysis detected major increases in cyanotoxin concentration and predicted the two greatest increases in MC. A wavelet analysis identified a significant ( p < 0.01) 2.8-4.2 day periodicity in toxin concentration over a ∼25 day period during peak toxin production, which is partially explained by easterly wind velocity ( R = -0.2, p < 0.05). Diversity in congener profiles was explored with principle component analysis showing that cyanotoxin dynamics followed a seasonal trajectory where toxin profiles were significantly clustered (ANOSIM R = 0.7, p < 0.05) on a daily basis. Variability in toxin profiles was strongly correlated with time ( R = -0.8, p < 0.001) as well as the C:N ratio of the toxin pool ( R = 0.17, p < 0.05). The methods employed here should be useful for uncovering patterns in cyanotoxin dynamics in other systems.

Meteorological factors and water quality changes of Plateau Lake Dianchi in China (1990-2015) and their joint influences on cyanobacterial blooms

Cyanobacterial blooms (CBs) in eutrophic lakes can cause various harmful issues to both humans and animals, disturb drinking water supply, and devastate lake ecosystems. Although great progresses have been made in many lakes from China and abroad on CBs prevention, mitigation and control, systematic research on the influencing factors of CBs in hypereutrophic plateau Lake Dianchi over a long time span is so far unavailable. This study comprehensively generalized both meteorological and water quality changes in Lake Dianchi during 1990-2015 on both yearly and monthly basis, separated Caohai from Waihai of Lake Dianchi regarding water quality variations, and investigated the individual and joint influencing meteorological and water quality factors on CBs using Spearman correlation, principal component analysis, and multivariate linear stepwise regression. Four specific lake regions, i.e. Caohai, northern Waihai, central Waihai, and southern Waihai, were respectively analyzed due to significant water quality heterogeneity. Results indicated that mild temperatures, low wind velocities, and hypereutrophic water conditions all favor CBs in Lake Dianchi, and the significant temperature rising trend may exacerbate severer CBs in the future. Despite configuration differences, the first principal components on CBs in the four sub-regions of Lake Dianchi were all consisted of meteorological factors, while water quality parameters especially total phosphorus concentrations contributed to the second principal component. Quantification of joint meteorological and water quality influencing factors on CBs needs further improvement, and largely relies on the accuracy of future weather forecasts, in order to set the goal of water quality improvement in each specific lake region for effective CBs management.

Long-term observation of cyanobacteria blooms using multi-source satellite images: a case study on a cloudy and rainy lake

High-frequency and reliable data on cyanobacteria blooming over a long time period is crucial to identify the outbreak mechanism of blooms and to forecast future trends. However, in cloudy and rainy areas, it is difficult to retrieve useful satellite images, especially in the rainy season. To address this problem, we used data from the HJ-1/CCD (Chinese environment and disaster monitoring and forecasting satellite/charge coupled device), GF-1/WFV (Chinese high-resolution satellite/wide field of view), and Landsat-8/OLI (Operational Land Imager) satellites to generate a time series of the bloom area from 2009 to 2016 in Dianchi Lake, China. We then correlated the responses of bloom dynamics to meteorological factors. Several findings can be drawn: (1) a higher bloom frequency and a larger bloom area occurred in 2011, 2013, and 2016, compared to the other years; (2) the frequency of blooms peaked in April, August, and November each year and expanded from north to south starting in July; (3) air temperature in spring and sunshine hours in summer greatly correlated to the yearly bloom area; (4) wind speed and sunshine hours strongly affected the short-term expansion of blooms and thereafter influenced the monthly bloom scale; and (5) rainfall had a strong short-term influence on the occurrence of blooms. Cyanobacteria blooms often occurred when wind speeds were less than 2.35 ± 0.78 m/s in the dry season and 2.01 ± 0.75 m/s in the rainy season, when there were 48 to 72 h of sunshine in the dry season and 35 to 57 h of sunshine in the rainy season, and when there was more than 10 mm of daily precipitation.

Assessment of surface water quality using water quality index and multivariate statistical analyses in Saraydüzü Dam Lake, Turkey

In this study, observations were carried out in the surface waters of Saraydüzü Dam Lake within Sinop provincial borders for 1 year to determine water quality. The basic 28 variables used to determine water quality were measured monthly at six stations. Taking into account the World Health Organization's drinking water standards, the water quality index (WQI) and Turkey's Ministry of Forestry and Water Affairs Surface Water Quality Regulations (SWQR) were used in determining the water quality. In addition, irrigation water quality was examined. For this, sodium absorption rates (SAR), sodium percentage and residual sodium carbonate (RSC) values were calculated. WQI values in the lake were found to be between 17.62 and 29.88. Water quality parameters did not exceed the recommended limit values in all months and at all stations. According to these values, the Saraydüzü Dam Lake water belongs to the 'very good' class in terms of drinking water quality. The results obtained showed that there were no nitrogen or phosphate inputs that could harm the ecosystem in the lake and that there were no low/insufficient ambient oxygen conditions resulting from excessive oxygen consumption during the degradation process of organic matter. All water quality parametres are well below the permissible limits except some heavy metals according to SWQR. Cu, Zn and Fe were found to exceed the limit values. The water quality of irrigation water was found to be good in terms of SAR and sodium percentage, whereas RSC was observed to have varying qualities during the year and not be suitable for irrigation in some months. According to results of factor analysis (FA), pH, temperature, electrical conductivity, suspended solid matter (SSM), biological oxygen demand (BOD), total hardness (TH),total alkalinity (TA), calcium, nitrate, ammonium, mercury and dissolved oxygen are the main variables responsible for the processes in the ecosystem.

Effects of climatically-modulated changes in solar radiation and wind speed on spring phytoplankton community dynamics in Lake Taihu, China

Many studies have focused on the interactive effects of temperature increases due to global warming and nutrient enrichment on phytoplankton communities. Recently, non-temperature effects of climate change (e.g., decreases in wind speed and increases in solar radiation) on large lakes have received increasing attention. To evaluate the relative contributions of both temperature and non-temperature effects on phytoplankton communities in a large eutrophic subtropical shallow lake, we analyzed long-term monitoring data from Lake Taihu, China from 1997 to 2016. Results showed that Lake Taihu’s spring phytoplankton biovolume and composition changed dramatically over this time frame, with a change in dominant species. Stepwise multiple linear regression models indicated that spring phytoplankton biovolume was strongly influenced by total phosphorus (TP), light condition, wind speed and total nitrogen (TN) (r_adj² = 0.8, p < 0.01). Partial redundancy analysis (pRDA) showed that light condition accounted for the greatest variation of phytoplankton community composition, followed by TP and wind speed, as well as the interactions between TP and wind speed. Our study points to the additional importance of non-temperature effects of climate change on phytoplankton community dynamics in Lake Taihu.

How physiological and physical processes contribute to the phenology of cyanobacterial blooms in large shallow lakes: A new Euler-Lagrangian coupled model

Cyanobacterial blooms have emerged as one of the most severe ecological problems affecting large and shallow freshwater lakes. To improve our understanding of the factors that influence, and could be used to predict, surface blooms, this study developed a novel Euler-Lagrangian coupled approach combining the Eulerian model with agent-based modelling (ABM). The approach was subsequently verified based on monitoring datasets and MODIS data in a large shallow lake (Lake Taihu, China). The Eulerian model solves the Eulerian variables and physiological parameters, whereas ABM generates the complete life cycle and transport processes of cyanobacterial colonies. This model ensemble performed well in fitting historical data and predicting the dynamics of cyanobacterial biomass, bloom distribution, and area. Based on the calculated physical and physiological characteristics of surface blooms, principal component analysis (PCA) captured the major processes influencing surface bloom formation at different stages (two bloom clusters). Early bloom outbreaks were influenced by physical processes (horizontal transport and vertical turbulence-induced mixing), whereas buoyancy-controlling strategies were essential for mature bloom outbreaks. Canonical correlation analysis (CCA) revealed the combined actions of multiple environment variables on different bloom clusters. The effects of buoyancy-controlling strategies (ISP), vertical turbulence-induced mixing velocity of colony (VMT) and horizontal drift velocity of colony (HDT) were quantitatively compared using scenario simulations in the coupled model. VMT accounted for 52.9% of bloom formations and maintained blooms over long periods, thus demonstrating the importance of wind-induced turbulence in shallow lakes. In comparison, HDT and buoyancy controlling strategies influenced blooms at different stages. In conclusion, the approach developed here presents a promising tool for understanding the processes of onshore/offshore algal blooms formation and subsequent predicting.

Multi-sensor satellite and in situ monitoring of phytoplankton development in a eutrophic-mesotrophic lake

Phytoplankton indicated by its photosynthetic pigment chlorophyll-a is an important pointer on lake ecology and a regularly monitored parameter within the European Water Framework Directive. Along with eutrophication and global warming cyanobacteria gain increasing importance concerning human health aspects. Optical remote sensing may support both the monitoring of horizontal distribution of phytoplankton and cyanobacteria at the lake surface and the reduction of spatial uncertainties associated with limited water sample analyses. Temporal and spatial resolution of using only one satellite sensor, however, may constrain its information value. To discuss the advantages of a multi-sensor approach the sensor-independent, physically based model MIP (Modular Inversion and Processing System) was applied at Lake Kummerow, Germany, and lake surface chlorophyll-a was derived from 33 images of five different sensors (MODIS-Terra, MODIS-Aqua, Landsat 8, Landsat 7 and Sentinel-2A). Remotely sensed lake average chlorophyll-a concentration showed a reasonable development and varied between 2.3±0.4 and 35.8±2.0mg·m^-3 from July to October 2015. Match-ups between in situ and satellite chlorophyll-a revealed varying performances of Landsat 8 (RMSE: 3.6 and 19.7mg·m^-3), Landsat 7 (RMSE: 6.2mg·m^-3), Sentinel-2A (RMSE: 5.1mg·m^-3) and MODIS (RMSE: 12.8mg·m^-3), whereas an in situ data uncertainty of 48% needs to be respected. The temporal development of an index on harmful algal blooms corresponded well with the cyanobacteria biomass development during summer months. Satellite chlorophyll-a maps allowed to follow spatial patterns of chlorophyll-a distribution during a phytoplankton bloom event. Wind conditions mainly explained spatial patterns. Integrating satellite chlorophyll-a into trophic state assessment resulted in different trophic classes. Our study endorsed a combined use of satellite and in situ chlorophyll-a data to alleviate weaknesses of both approaches and to better characterise and understand phytoplankton development in lakes.

Influences of environmental factors on biomass of phytoplankton in the northern part of Tai Lake, China, from 2000 to 2012

Long-term (2000 to 2012) monthly data on communities of phytoplankton, and environmental variables were measured in water collected from Meiliang Bay and Wuli Lake of Tai Lake, China. Redundancy analysis (RDA) was conducted to explore relationships between the phytoplankton communities and environmental variables. Change points for concentrations of nutrients, which serve as early warnings of state shifts in lacustrine ecosystems, were identified using the Threshold Indicator Taxa Analysis (TITAN). The biomass of phytoplankton was positively correlated with the concentrations of total phosphorus (TP), suspended solids (SS), water temperature (WT), and pH but negatively correlated with the N/P ratio (by mass) and Secchi disk depth (SD). Furthermore, TP, rather than other factors, was a controlling factor limiting the primary production of phytoplankton in most of this region. The change points for concentrations of TP controlling the occurrences of sensitive and tolerant taxa were 56.1 and 103.5 μg TP/L, respectively. These results imply that an abrupt change in this lacustrine ecosystem has occurred in most parts of the study area, and the turbid state of this lake can be altered by reducing TP loading. This study provides an alternative ecological method for exploring the production of algal blooms and could advance the understanding of HABs.

Remote estimation of cyanobacterial blooms using the risky grade index (RGI) and coverage area index (CAI): a case study in the Three Gorges Reservoir, China

Harmful cyanobacterial blooms are exemplified as a major environmental concern due to producing toxin, and have generated a serious threat to public health. Knowledge on the spatial-temporal distribution of cyanobacterial blooms is therefore crucial for public health organizations and environmental agencies. In this study, field data and charge coupled device (CCD) image were collected in Lakes Gaoyang and Hanfeng of the Three Gorges Reservoir (TGR), China. We conducted the risky grade index (RGI) and coverage area index to develop a feasible estimation framework of cyanobacterial blooms. First, the close relationships between CCD reflectance spectral indices and water quality parameters were constructed based on water optical classification. Then, a regional algorithm for the RGI classification was established by density peaks. Finally, our proposed algorithm was applied to investigate dynamics of cyanobacterial blooms in the two lakes from 6-year series of CCD images. Encouraging results demonstrated that satellite remote sensing in conjunction with field observation can aid in the estimation of cyanobacterial blooms in the TGR.

Spatial identification of critical nutrient loads of large shallow lakes: Implications for Lake Taihu (China)

Ongoing eutrophication frequently causes toxic phytoplankton blooms. This induces huge worldwide challenges for drinking water quality, food security and public health. Of crucial importance in avoiding and reducing blooms is to determine the maximum nutrient load ecosystems can absorb, while remaining in a good ecological state. These so called critical nutrient loads for lakes depend on the shape of the load-response curve. Due to spatial variation within lakes, load-response curves and therefore critical nutrient loads could vary throughout the lake. In this study we determine spatial patterns in critical nutrient loads for Lake Taihu (China) with a novel modelling approach called Spatial Ecosystem Bifurcation Analysis (SEBA). SEBA evaluates the impact of the lake's total external nutrient load on the local lake dynamics, resulting in a map of critical nutrient loads for different locations throughout the lake. Our analysis shows that the largest part of Lake Taihu follows a nonlinear load-response curve without hysteresis. The corresponding critical nutrient loads vary within the lake and depend on management goals, i.e. the maximum allowable chlorophyll concentration. According to our model, total nutrient loads need to be more than halved to reach chlorophyll-a concentrations of 30-40 μg L^-1 in most sections of the lake. To prevent phytoplankton blooms with 20 μg L^-1 chlorophyll-a throughout Lake Taihu, both phosphorus and nitrogen loads need a nearly 90% reduction. We conclude that our approach is of great value to determine critical nutrient loads of lake ecosystems such as Taihu and likely of spatially heterogeneous ecosystems in general.