Principles and research progress of physical prevention and control technologies for algae in eutrophic water

The abnormal reproduction of algae in water worldwide is prominent in the context of human interference and global climate change. This study first thoroughly analyzed the effects of physical factors, such as light, temperature, hydrodynamics, and operational strategies, on algal growth and their mechanisms. Physical control techniques are safe and have great potential for preventing abnormal algal blooms in the absence of chemical reagents. The focus was on the principles and possible engineering applications of physical shading, ultrasound, micro-current, and ultraviolet (UV) technologies, in controlling abnormal algal reproduction. Physical shading can inhibit or weaken photosynthesis in algae, thereby inhibiting their growth. Ultrasound mainly affects the physiological and biochemical activities of cells by destroying the cell walls, air cells, and active enzymes. Micro-currents destroy the algal cell structure through direct and indirect oxidation, leading to algal cell death. UV irradiation can damage DNA, causing organisms to be unable to reproduce or algal cells to die directly. This article comprehensively summarizes and analyzes the advantages of physical prevention and control technologies for the abnormal reproduction of algae, providing a scientific basis for future research. In the future, attempts will be made toward appropriately and comprehensively utilizing various physical technologies to control algal blooms. The establishment of an intelligent, comprehensive physical prevention and control system to achieve environmentally friendly, economical, and effective physical prevention and control of algae, such as the South-to-North Water Diversion Project in China, is of great importance for specific waters.

Potential gap in understanding cyanoHABs: Light-dependent morphological variations in colonial cyanobacterium Microcystis

Colony formation is a crucial characteristic of Microcystis, a cyanobacterium known for causing cyanobacterial harmful algal blooms (cyanoHABs). It has been observed that as Microcystis colonies grow larger, they often become less densely packed, which correlates with a decrease in light penetration. The objective of this study was to investigate the effects of light limitation on the morphological variations in Microcystis, particularly in relation to the crowded cellular environment. The results indicated that when there was sufficient light (transmittance = 100 %) to support a growth rate of 0.11±0.01 day-1, a significant increase in colony size was found, from 466±15 μm to 1030±111 μm. However, under light limitation (transmittance = 50 % - 1 %) where the growth rate was lower than 0, there was no significant improvement in colony size. Microcystis in the light limitation groups exhibited a loose cell arrangement and even the presence of holes or pores within the colony, confirming the negative correlation between colony size and cell arrangement. This pattern is driven by regional differences in growth within the colony, as internal cells have a significantly lower frequency of division compared to peripheral cells, due to intra-colony self-shading (ICSS). The research demonstrates that Microcystis can adjust its cell arrangement to avoid excessive self-shading, which has implications for predicting and controlling cyanoHABs. These findings also contribute to the understanding of cyanobacterial variations and can potentially inform future research on the diverse phycosphere.

Distinct differences of vertical phytoplankton community structure in mainstream and a tributary bay of the Three Gorges Reservoir, China

The vertical distribution of phytoplankton plays a crucial role in shaping the dynamics and structure of aquatic communities. In highly dynamic reservoir systems, water level fluctuations significantly affect the physiochemical conditions and the phytoplankton community. However, the specific effects on the vertical characteristics of phytoplankton between the mainstream and the tributary bay of the reservoir remain unstudied. This study investigated the vertical aspects of phytoplankton density, biomass, α and β diversity through monthly sampling over two years in the mainstream (Chang Jiang, CJ) and a tributary bay (Xiang Xi, XX) of the Three Gorges Reservoir in China. Phytoplankton density and biomass were significantly higher in XX, indicating an increased risk of algal blooms in the tributary. The phytoplankton community in CJ showed more stable species-environment relationships, a lower Shannon index and a higher evenness index, suggesting a relatively simple structure and a more uniform distribution of phytoplankton among different water layers. Conversely, XX showed greater differences between water layers (higher β diversity), with significant negative correlations with water level and positive correlations with DO difference, dissolved silica (DSi) difference, and stratification. Peak phytoplankton density and biomass, as well as high β diversity in XX, occurred during periods of decreased water levels with strong stratification in spring and summer. A structural equation model complemented by path analysis revealed that a decrease in water level could increase β diversity either directly through internal processes with extended residence time or indirectly by modifying stratification and the vertical distribution of DSi in XX. Therefore, a proposed water quality management strategy for XX was to increase the water level or reduce β diversity by implementing artificial mixing during stratification periods. Overall, this study lies in its comprehensive investigation of the vertical characteristics of the phytoplankton community in both the mainstream and the tributary bay of the Three Gorges Reservoir, elucidating the significant impact of water level fluctuations and providing insights for targeted water quality management strategies in the tributary bay to mitigate potential ecological impacts.

Ecological evolution of algae in connected reservoirs under the influence of water transfer: Algal density, community structure, and assembly processes

Reservoir connectivity provides a solution for regional water shortages. Understanding the water quality of reservoirs and the response of algal communities to water transfer could provide the basis for a long-term evolutionary model of reservoirs. In this study, a water-algal community model was established to study the effects of water transfer on water quality and algal communities in reservoirs. The results showed that water transfer significantly decreased total nitrogen and nitrate concentrations. However, the water transfer resulted in an increase in the CODMn concentration and conductivity in the receiving reservoir. Additionally, the algal density and chlorophyll-a (chl-a) concentration showed an increase with water transfer. Bacillariophyta, Cyanophyta, and Chlorophyta were the dominant algal phyllum in all three reservoirs. Water transfer induced the evolution of the algal community by driving changes in the chemical parameters of the receiving reservoir and led to more complex relationships within the algal community. The effects of stochastic processes on algal communities were also enhanced in the receiving reservoirs. These results provide specific information for water quality safety management and eutrophication prevention in connected reservoirs.

Three-dimensional augmentation for hyperspectral image data of water quality: An Integrated approach using machine learning and numerical models

This research introduces a comprehensive methodology to enhance hyperspectral image data (HSD) utility, specifically focusing on the three-dimensional (3-D) augmentation of Chlorophyll-a (Chl-a). This study comprises three significant steps: (1) the augmentation of limited field water quality data in terms of time interval and number of variables using neural network models, (2) the generation of 3-D data using numerical models, and (3) the extension of the hyperspectral image data into 3-D data using machine learning models. In the first phase, Multilayer Perceptron (MLP) models were developed to train water quality interactions and successfully generated high-frequency water quality data by adjusting biased measurements and predicting detailed water quality variables. In the second phase, high-frequency data generated by MLP models were applied to develop two numerical models. These numerical models successfully generated 3-D data, thereby demonstrating the effectiveness of integrating numerical modeling with neural networks. In the final phase, ten machine learning models were trained to generate 3-D Chl-a data from HSD. Notably, the Gaussian Process Regression model exhibited superior performance, effectively estimating 3-D Chl-a data with robust accuracy, as evidenced by an R-square value of 0.99. The findings align with theories of algal bloom dynamics, further validating the effectiveness of the approach. This study demonstrated the successful integrated development for HSD extension using machine learning models, numerical models, and original HSD, highlighting the potential of such integrated methodologies in advancing water quality monitoring and estimation. Notably, the approach leverages readily accessible data, allowing for the swift generation of results and bypassing time-consuming data collection processes. This research marks a significant step towards more robust, comprehensive water quality monitoring and prediction, thereby facilitating better management of aquatic ecosystems.

What makes a cyanobacterial bloom disappear? A review of the abiotic and biotic cyanobacterial bloom loss factors

Cyanobacterial blooms present substantial challenges to managers and threaten ecological and public health. Although the majority of cyanobacterial bloom research and management focuses on factors that control bloom initiation, duration, toxicity, and geographical extent, relatively little research focuses on the role of loss processes in blooms and how these processes are regulated. Here, we define a loss process in terms of population dynamics as any process that removes cells from a population, thereby decelerating or reducing the development and extent of blooms. We review abiotic (e.g., hydraulic flushing and oxidative stress/UV light) and biotic factors (e.g., allelopathic compounds, infections, grazing, and resting cells/programmed cell death) known to govern bloom loss. We found that the dominant loss processes depend on several system specific factors including cyanobacterial genera-specific traits, in situ physicochemical conditions, and the microbial, phytoplankton, and consumer community composition. We also address loss processes in the context of bloom management and discuss perspectives and challenges in predicting how a changing climate may directly and indirectly affect loss processes on blooms. A deeper understanding of bloom loss processes and their underlying mechanisms may help to mitigate the negative consequences of cyanobacterial blooms and improve current management strategies.

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.

Effects of microcystin-LR on purification efficiency of simulating drinking water source by Hydrocharis dubia (Bl.) backer

The safety of drinking water source directly affects human health. Microcystin-LR (MC-LR), a toxic and common pollutant in drinking water source, is released by algae and can impede the in-situ remediation effect of aquatic plant. Finding out the effect mechanism of MC-LR on the purification of drinking water by aquatic plant is the key to its application. This study aims to explore the performance and mechanism of MC-LR on drinking water source purification by Hydrocharis dubia (Bl.) backer. The optimum removal efficiency of NH4+-N, TP and COD were 90.7%, 93.2% and 77.3% at MC-LR concentration of 0.5 μg L-1, respectively. With the increase of MC-LR concentration, the pollutants removal rate was obviously inhibited causing by concentration-dependent. Furthermore, the growth and development of the Hydrocharis dubia (Bl.) backer roots were significantly promoted at the concentration of 0.1 μg L-1. The length, tips, surface area, and average diameter of the root increased by 71.3%, 271.4%, 265.5%, and 113.0%, respectively. Chlorophyll contents under low-concentration MC-LR show a 14.5%-15.7% promoting effect compared with the control group. The activities of POD and CAT were also stimulated with the MC-LR increasing (<1.0 μg L-1). Notably, the MDA contents increased with increasing MC-LR concentration (p < 0.01). This study indicates the effect mechanism of MC-LR on Hydrocharis dubia (Bl.) backer purification performance relies on the increased growth and enzyme activity of Hydrocharis dubia (Bl.) backer.

Managing a cyanobacteria harmful algae bloom "hotspot" in the Sacramento - San Joaquin Delta, California

Cyanobacterial harmful algal blooms (CHABs) have become a persistent seasonal problem in the upper San Francisco Estuary, California also known as the Sacramento-San Joaquin Delta (Delta). The Delta is comprised of a complex network of open water bodies, channels, and sloughs. The terminus of the Stockton Channel is an area identified as a CHAB "hotspot." As CHABs increase in severity, there is an urgent need to better understand CHAB drivers to identify and implement mitigation measures that can be used in an estuarine complex like the Delta. We investigated water quality conditions and nutrient dynamics in the Stockton Channel by measuring nutrients in the water column, sediments, and pore waters. In situ nutrient addition bioassay experiments were used to assess the effects of nutrient enrichment on total algal/cyanobacterial growth and pigment concentrations. In both June and September, relative to unamended controls, total chlorophyll and cyanobacterial pigment concentrations were unaffected by nutrient additions; hence, the study area showed signs of classical hypereutrophication, with ambient nitrogen and phosphorus present in excess of algal growth requirements. A cyanobacterial bloom, dominated by Microcystis spp. was present throughout the study area but was most severe and persistent at the shallowest site at the channel terminus. At this site, Microcystis spp. created water quality conditions that allowed for a prolonged bloom from June through September. While targeted nutrient reductions are recommended for long term mitigation, on a shorter timescale, our findings suggest that physical/mechanical controls are the more promising alternative approaches to reduce the severity of CHABs in the terminus of the Stockton Channel.

Temperature driving vertical stratification regulates phytoplankton community structure in the Bohai Sea and Yellow Sea

To analyse the effects of physicochemical factors on the phytoplankton community in the Bohai Sea (BS) and Yellow Sea (YS), a investigation was conducted during 27 July to 10 August 2020. A sum of 156 species were identified in the BS and YS, including Bacillariophyta (69 species), Pyrrophyta (85 species) and Chrysophyta (2 species). The phytoplankton community were divided into four provinces according to Bray-Curtis similarity. In order to study the phytoplankton community in the BS and YS, we studied the phytoplankton community composition and their assembly mechanisms. The results showed that stochastic ecological processes had a greater effect on the province C community structure. The Raup-crick dissimilarity showed that deterministic factors had a greater effect on the province A, B and D communities structure. The habitat niche width results indicated that niche was larger in the province D, compared to the province A, B and C. Based on a structural equation model (SEM), we analyzed the effects of physicochemical factors on phytoplankton community structure and temperature was found to affect the phytoplankton community composition and structure by the vertical stratification. The result showed that temperature was an important parameter for phytoplankton abundance and revealed that temperature affected phytoplankton community structure by influencing the vertical stratification index (VSI) in the BS and YS.

Selection of photosynthetic traits by turbulent mixing governs formation of cyanobacterial blooms in shallow eutrophic lakes

Prediction of the complex cyanobacteria-environment interactions is vital for understanding harmful bloom formation. Most previous studies on these interactions considered specific properties of cyanobacterial cells as representative for the entire population (e.g. growth rate, mortality, and photosynthetic capacity (Pmax)), and assumed that they remained spatiotemporally unchanged. Although, at the population level, the alteration of such traits can be driven by intraspecific competition, little is known about how traits and their plasticity change in response to environmental conditions and affect the bloom formation. Here we test the hypothesis that intraspecific variations in Pmax of cyanobacteria (Microcystis spp.) play an important role in its population dynamics. We coupled a one-dimensional hydrodynamic model with a trait-based phytoplankton model to simulate the effects of physical drivers (turbulence and turbidity) on the Pmax of Microcystis populations for a range of dynamic conditions typical for shallow eutrophic lakes. Our results revealed that turbulence acts as a directional selective driver for changes in Pmax. Depending on the intensity of daily-periodic turbulence, representing wind-driven mixing, a shift in population-averaged phenotypes occurred toward either low Pmax, allowing the population to capture additional light in the upper layers, or high Pmax, enhancing the efficiency of light utilization. Moreover, we observed that a high intraspecific diversity in Pmax accelerated the formation of surface scum by up to more than four times compared to a lower diversity. This study offers insights into mechanisms by which cyanobacteria populations respond to turbulence and underscores the significance of intraspecific variations in cyanobacterial bloom formation.

HIGHLIGHTS

Spatio-temporal dynamics of phytoplankton in a diversion reservoir and the major influencing factors: taxonomic versus functional groups classification

Identifying factors affecting phytoplankton dynamics is crucial to the management of aquatic ecosystems. A lot of scholars have conducted intensive studies on phytoplankton in lake or reservoirs, but not many studies have been conducted on diversion reservoirs. To explore the seasonal and spatial variation of phytoplankton communities and their relationship with environmental factors in the context of water diversion, a case study was carried out at XiKeng (XK) reservoir in South China. In this study, month-by-month water samples and phytoplankton were collected from this reservoir from December, 2021, to July, 2022. The results showed that the phytoplankton community was characterized by significant spatial and temporal variations. There were significant differences in phytoplankton abundance and structure in the reservoirs in terms of time. The abundance of phytoplankton cells and the proportion of Cyanobacteria in the reservoir showed a trend of increasing from autumn to spring and then decreasing from spring to summer, while the functional group evolved from S1 in autumn to SN in spring and summer. The abundance of phytoplankton was influenced by the dynamic water division and the characteristics of the reservoir itself, resulting in a spatial distribution characteristic of AIII > AII > AI. Water temperature (WT) and nutrients were the key factors driving the changes in phytoplankton abundance and community structure in the reservoir. These findings will deepen our understanding of the spatial and temporal dynamics of phytoplankton community structure in diversion reservoirs and provide a basis for freshwater water ecological management strategies.

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.

Hydrodynamic regimes modulate nitrogen fixation and the mode of diazotrophy in Lake Tanganyika

The factors that govern the geographical distribution of nitrogen fixation are fundamental to providing accurate nitrogen budgets in aquatic environments. Model-based insights have demonstrated that regional hydrodynamics strongly impact nitrogen fixation. However, the mechanisms establishing this physical-biological coupling have yet to be constrained in field surveys. Here, we examine the distribution of nitrogen fixation in Lake Tanganyika - a model system with well-defined hydrodynamic regimes. We report that nitrogen fixation is five times higher under stratified than under upwelling conditions. Under stratified conditions, the limited resupply of inorganic nitrogen to surface waters, combined with greater light penetration, promotes the activity of bloom-forming photoautotrophic diazotrophs. In contrast, upwelling conditions support predominantly heterotrophic diazotrophs, which are uniquely suited to chemotactic foraging in a more dynamic nutrient landscape. We suggest that these hydrodynamic regimes (stratification versus mixing) play an important role in governing both the rates and the mode of nitrogen fixation.

The harmful cyanobacterium Microcystis aeruginosa PCC7806 is more resistant to hydrogen peroxide at elevated CO2

Rising atmospheric CO2 can intensify harmful cyanobacterial blooms in eutrophic lakes. Worldwide, these blooms are an increasing environmental concern. Low concentrations of hydrogen peroxide (H2O2) have been proposed as a short-term but eco-friendly approach to selectively mitigate cyanobacterial blooms. However, sensitivity of cyanobacteria to H2O2 can vary depending on the available resources. To find out how cyanobacteria respond to H2O2 under elevated CO2, Microcystis aeruginosa PCC 7806 was cultured in chemostats with nutrient-replete medium under C-limiting and C-replete conditions (150 ppm and 1500 ppm CO2, respectively). Microcystis chemostats exposed to high CO2 showed higher cell densities, biovolumes, and microcystin contents, but a lower photosynthetic efficiency and pH compared to the cultures grown under low CO2. Subsamples of the chemostats were treated with different concentrations of H2O2 (0-10 mg·L-1 H2O2) in batch cultures under two different light intensities (15 and 100 μmol photons m-2·s-1) and the response in photosynthetic vitality was monitored during 24 h. Results showed that Microcystis was more resistant to H2O2 at elevated CO2 than under carbon-limited conditions. Both low and high CO2-adapted cells were more sensitive to H2O2 at high light than at low light. Microcystins (MCs) leaked out of the cells of cultures exposed to 2-10 mg·L-1 H2O2, while the sum of intra- and extracellular MCs decreased. Although both H2O2 and CO2 concentrations in lakes vary in response to many factors, these results imply that it may become more difficult to suppress cyanobacterial blooms in eutrophic lakes when atmospheric CO2 concentrations continue to rise.

Algal community structure prediction by machine learning

The algal community structure is vital for aquatic management. However, the complicated environmental and biological processes make modeling challenging. To cope with this difficulty, we investigated using random forests (RF) to predict phytoplankton community shifting based on multi-source environmental factors (including physicochemical, hydrological, and meteorological variables). The RF models robustly predicted the algal communities composed by 13 major classes (Bray-Curtis dissimilarity = 9.2 ± 7.0%, validation NRMSE mostly <10%), with accurate simulations to the total biomass (validation R² > 0.74) in Norway's largest lake, Lake Mjosa. The importance analysis showed that the hydro-meteorological variables (Standardized MSE and Node Purity mostly >0.5) were the most influential factors in regulating the phytoplankton. Furthermore, an in-depth ecological interpretation uncovered the interactive stress-response effect on the algal community learned by the RF models. The interpretation results disclosed that the environmental drivers (i.e., temperature, lake inflow, and nutrients) can jointly pose strong influence on the algal community shifts. This study highlighted the power of machine learning in predicting complex algal community structures and provided insights into the model interpretability.

Subsurface Bacterioplankton Structure and Diversity in the Strongly-Stratified Water Columns within the Equatorial Eastern Indian Ocean

The consequences of climate change may directly or indirectly impact the marine biosphere. Although ocean stratification has been recognized as one of the crucial consequences of ocean warming, its impacts on several critical aspects of marine microbes remain largely unknown in the Indian Ocean. Here, we investigate the effects of water stratification, in both surface and subsurface layers, on hydrogeographic parameters and bacterioplankton diversity within the equatorial eastern Indian Ocean (EIO). Strong stratification in the upper 200 m of equatorial EIO was detected with evidential low primary productivity. The vertical bacterioplankton diversity of the whole water columns displayed noticeable variation, with lower diversity occurring in the surface layer than in the subsurface layers. Horizontal heterogeneity of bacterioplankton communities was also in the well-mixed layer among different stations. SAR11 and Prochlorococcus displayed uncharacteristic low abundance in the surface water. Some amplicon sequence variants (ASVs) were identified as potential biomarkers for their specific depths in strongly-stratified water columns. Thus, barriers resulting from stratification are proposed to function as an ‘ASV filter’ to regulate the vertical bacterioplankton community diversity along the water columns. Overall, our results suggest that the effects of stratification on the structure and diversity of bacterioplankton can extend up to the bathypelagic zone in the strongly-stratified waters of the equatorial EIO. This study provides the first insight into the effect of stratification on the subsurface microbial communities in the equatorial eastern Indian Ocean.

Anaerobic digestion as a tool to manage eutrophication and associated greenhouse gas emission

Eutrophicated inland water bodies are noticed to be one of the contributing factors to greenhouse gas (GHGs) emissions. Direct discharge of untreated or partially treated water is a major concern. Microalgae-based technology and management are regarded as one of the potential nature-based approaches to combat eutrophication. In turn, the microalgae facilitate the recovery of GHGs contributing compounds in the form of organic biomass. The recovered algal biomass can be harnessed for the production of biofuels and other bio-products, like biofertilizer, using anaerobic digestion. By virtue, circular bio-economy can be achieved alongside mitigating GHGs emissions. Before implementing, it is vital to thoroughly explore the links between the process and potential alternatives for wastewater treatment, waste valorization, biofuel production, and land usage. Thus, the present review discusses the impact of eutrophication on ecology and environment, current technologies for mitigating eutrophication and GHGs, and energy recovery through the anaerobic digestion of algal biomass. Further, the processes at the intercept of wastewater treatment and biogas production were reviewed to leverage the potential of anaerobic digestion for making a circular bioeconomy framework.

Ancient DNA reveals potentially toxic cyanobacteria increasing with climate change

Cyanobacterial blooms in freshwater systems are a global threat to human and aquatic ecosystem health, exhibiting particularly harmful effects when toxin-producing taxa are present. While climatic change and nutrient over-enrichment control the global expansion of total cyanobacterial blooms, it remains unknown to what extent this expansion reflected cyanobacterial assemblage due to the scarcity of long-term monitoring data. Here we use high-throughput sequencing of sedimentary DNA to track ∼100 years of changes in cyanobacterial community in hyper-eutrophic Lake Taihu, China's third largest freshwater lake and the key water source for ∼30 million people. A steady increase in the abundance of Microcystis (as potential toxin producers) during the past thirty years was correlated with increasing temperatures and declining wind speeds, but not with temporal trends in lakewater nutrient concentrations, highlighting recent climate effects on potentially increasing toxin-producing taxa. The socio-environmental repercussions of these findings are worrisome as continued anthropogenic climate change may counteract nutrient amelioration efforts in this critical freshwater resource.

Co-occurrence patterns and environmental factors associated with rapid onset of Microcystis aeruginosa bloom in a tropical coastal lagoon

The environmental factors contributing to the Microcystis aeruginosa bloom (hereafter referred to as Microcystis bloom) are still debatable as they vary with season and geographic settings. We examined the environmental factors that triggered Microcystis bloom outbreak in India's largest brackish water coastal lagoon, Chilika. The warmer water temperature (25.31-32.48 °C), higher dissolved inorganic nitrogen (DIN) loading (10.15-13.53 μmol L^-1), strong P-limitation (N:P ratio 138.47-246.86), higher water transparency (46.62-73.38 cm), and low-salinity (5.45-9.15) exerted a strong positive influence on blooming process. During the bloom outbreak, M. aeruginosa proliferated, replaced diatoms, and constituted 70-88% of the total phytoplankton population. The abundances of M. aeruginosa increased from 0.89 × 10⁴ cells L^-1 in September to 1.85 × 10⁴ cells L^-1 in November and reduced drastically during bloom collapse (6.22 × 10³ cells L^-1) by the late November of year 2017. The decrease in M. aeruginosa during bloom collapse was associated with a decline in DIN loading (2.97 μmol L^-1) and N:P ratio (73.95). Sentinel-3 OLCI-based satellite monitoring corroborated the field observations showing Cyanophyta Index (CI) > 0.01 in September, indicative of intense bloom and CI < 0.0001 during late November, suggesting bloom collapse. The presence of M. aeruginosa altered the phytoplankton community composition. Furthermore, co-occurrence network indicated that bloom resulted in a less stable community with low diversity, inter-connectedness, and prominence of a negative association between phytoplankton taxa. Variance partitioning analysis revealed that TSM (16.63%), salinity (6.99%), DIN (5.21%), and transparency (5.15%) were the most influential environmental factors controlling the phytoplankton composition. This study provides new insight into the phytoplankton co-occurrences and combination of environmental factors triggering the rapid onset of Microcystis bloom and influencing the phytoplankton composition dynamics of a large coastal lagoon. These findings would be valuable for future bloom forecast modeling and aid in the management of the lagoon.

Phytoplankton and benthic infauna responses to aeration, an experimental ecological remediation, in a polluted subtropical estuary with organic-rich sediments

Fine-grained organic-rich sediments (FGORS) are accumulating in estuaries worldwide, with multi-faceted negative ecosystem impacts. A pilot experiment was carried out in a residential canal of the Indian River Lagoon estuary (IRL, Florida, USA) using an aeration treatment intended to mitigate the harmful ecological effects of organic-rich sediment pollution. Planktonic and benthic communities were monitored, and environmental data collected throughout the aeration process. Results were compared against control conditions to evaluate the efficacy of aeration in the mitigation of FGORS. During the aeration process, hurricane Irma impacted the study area, bringing heavy rainfall and spawning a brown tide event (Aureoumbra lagunensis). The overall thickness and volume of FGORS, and the organic content of surface sediments did not change during the aeration treatment. Dissolved oxygen was higher and ammonium concentrations were lower in aeration canal bottom water compared to the control canal. During treatment, aeration did facilitate benthic animal life when temperatures dropped below 25°C, likely due to water column mixing and the increased capacity of water to hold dissolved gasses. In general, aeration did not significantly change the planktonic community composition relative to the control canal, but, during the post-bloom period, aeration helped to weaken the brown tide and phytoplankton densities were 35-50% lower for A. lagunensis in aeration canal surface water compared to the control canal. Aeration has important management applications and may be useful for mitigating algal blooms in flow-restricted areas and promoting benthic communities in cooler environments.

Effect of different mixing modes on the abundance of Microcystis in Lake Taihu under green light

Light and hydrodynamic force are important physical factors affecting growth of Microcystis. The most recent study found that green light has good effect in inhibiting growth of Microcystis. To understand the effect of mixing modes on Microcystis under the green light, we investigated the effects of continuous mixing and intermittent mixing on the abundance of Microcystis in Taihu Lake under field conditions. The study results found that abundance of Microcystis in control, intermittent mixing group, and continuous mixing group decreased 76.62%, 40.36%, and 95.18% on day 7 compared with that on day 1 in this experiment. At the end of the experiment, abundance percentages of diatoms and green algae to total phytoplankton abundance were 1.57% and 0.48% in control, 2.32% and 0.67% in intermittent mixing group, and 22.47% and 20.27% in continuous mixing group. The results indicated that continuous mixing favored the removal of Microcystis under green light conditions and was helpful for the growth of green algae and diatoms. The results provide a new approach for the control of Microcystis blooms.

Effects of physiologic activities of plankton on CO2 flux in the Three Gorges Reservoir after rainfall during algal blooms

The nutrient supply to the freshwater system may be changed by rainfall, which also encourages the cyclic succession of microorganisms. However, in a highly dynamic land-water reservoir, the microbial metabolic changes brought on by the changes of water nutrients following rainfall are not clearly documented. The study selected the Three Gorges Reservoir (TGR) backwater region during algal bloom seasons as the study area and time, and used the Biolog-EcoPlates technique to examine the heterotrophic metabolism conditions of the water before and after rain. The field monitoring assessed how biotic and abiotic variables affected CO₂ flux at the water-air interface. The tests conducted in the laboratory investigated the water-integrated metabolic process was affected by post-rainfall environmental changes. The results showed that the average flux of CO₂ at the water-air interface before rainfall was -489.17 ± 506.66 mg·(m²·d)^-1, while the average CO₂ flux reached 393.35 ± 793.49 mg·(m²·d)^-1 after rainfall. This is mostly explained by the heterotrophic metabolic variability of plankton in response to changes in the aqueous environment brought on by precipitation. These discoveries help us better understand how biological metabolisms after rain affect the CO₂ flux at the water-air interface and reservoir greenhouse gas (GHG) emission equivalents can be evaluated more accurately.

The biomass of bloom-forming colonial Microcystis affects its response to aeration disturbance

The algal succession in Microcystis blooms of varying biomass under continuous aeration was studied in a greenhouse. There were four treatments (control, Low, Medium, and High) with initial chlorophyll a (Chl-a) of 32.5, 346.8, 1413.7, and 14,250.0 μg L^-1, respectively. During the experiment, Cyanophyta biomass was the lowest in the Medium treatment (P < 0.05), while its Chlorophyta biomass was the highest (P < 0.05). Both Chlorophyta and Bacillariophyta biomass were the lowest in the High treatment (P < 0.05). Bacillariophyta biomass, particularly the diatom Nitzschia palea was the highest in the Low treatment (P < 0.05), and Nitzschia palea cells were attached to the Microcystis colonies. Thus, the algal shift in Microcystis blooms under aeration disturbance depends on its initial biomass, and it shift to green algae or/and diatom dominance in the control, Low, Medium treatments. Diatom cells, particularly N. palea, grew in an attached form on Microcystis colonies in treatment Low, in which the colonies provided media for the adherence. The mechanism of the algal shift with different biomass must be related to the nutrient level, low light and aerobic conditions under aeration disturbance as well as the aeration itself, which destroyed the Microcystis colonies' advantage of floating on the water.

Controlling spring Dinoflagellate blooms in a stratified drinking water reservoir via artificial mixing: Effects, mechanisms, and operational thresholds

Water-lifting aerators (WLAs) are often applied in stratified reservoirs to activate artificial mixing to inhibit harmful algal blooms (HABs). Here, the effects, mechanisms, and operational thresholds of spring Dinoflagellate control via artificial mixing were studied using a combination of taxonomic and functional groups and boundary line models. Algal cell density at two sampling sites (i.e., S1 and S2) decreased to below 1.0 × 10⁶ cells/L (corresponding chlorophyll-a content under 10 μg/L) during artificial mixing, with a Dinoflagellate removal efficiency of 97.1 % at S1 and 95.5 % at S2, respectively. The succession patterns of main phytoplankton taxonomic and functional groups changed greatly during artificial mixing at the sites: from Dinoflagellate and motile Chlorophyta to Bacillariophyta from groups A/L_O/P to A, respectively. Water temperature (WT), light availability (Z_eu/Z_mix), and mixing depth (Z_mix) were more effective factors influencing phytoplankton dynamics at a short-term scale, followed by total phosphorus (TP). A decrease in surface WT and Z_eu/Z_mix, and increase in Z_mix alongside the improvement of TP levels, which were induced by WLAs, drove the Dinoflagellate bloom control by a shift of phytoplankton structure from large, motile, and low surface to volume ratio (S/V) to small, immobile, and high S/V algae. The operational threshold values of WT, Z_eu/Z_mix, Z_mix and TP concentration for the suppression of Dinoflagellate growth using mixing systems are recommended as 9.6 °C, 0.17, 11.5 m, and 0.020 mg/L, respectively, based on a boundary line analysis. This work can help improve the cognition of mechanisms controlling HABs using mixing and aeration techniques in reservoirs.

Decomposing predictability to identify dominant causal drivers in complex ecosystems

Ecosystems are complex systems of various physical, biological, and chemical processes. Since ecosystem dynamics are composed of a mixture of different levels of stochasticity and nonlinearity, handling these data is a challenge for existing methods of time series-based causal inferences. Here, we show that, by harnessing contemporary machine learning approaches, the concept of Granger causality can be effectively extended to the analysis of complex ecosystem time series and bridge the gap between dynamical and statistical approaches. The central idea is to use an ensemble of fast and highly predictive artificial neural networks to select a minimal set of variables that maximizes the prediction of a given variable. It enables decomposition of the relationship among variables through quantifying the contribution of an individual variable to the overall predictive performance. We show how our approach, EcohNet, can improve interaction network inference for a mesocosm experiment and simulated ecosystems. The application of the method to a long-term lake monitoring dataset yielded interpretable results on the drivers causing cyanobacteria blooms, which is a serious threat to ecological integrity and ecosystem services. Since performance of EcohNet is enhanced by its predictive capabilities, it also provides an optimized forecasting of overall components in ecosystems. EcohNet could be used to analyze complex and hybrid multivariate time series in many scientific areas not limited to ecosystems.

Combined effects of eutrophication and warming on polyunsaturated fatty acids in complex phytoplankton communities: A mesocosm experiment

Climate change and eutrophication are among the main stressors of shallow freshwater ecosystems, and their effects on phytoplankton community structure and primary production have been studied extensively. However, their combined effects on the algal production of polyunsaturated fatty acids (PUFA), specifically, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are currently unresolved. Moreover, the proximate reasons for changes in phytoplankton EPA and DHA concentrations are unclear, i.e., the relative importance of ecological (changes in the community composition) vs. ecophysiological (within taxa changes in EPA and DHA levels) factors. We investigated the responses of phytoplankton EPA and DHA concentrations to warming (IPCC climate scenario) and nutrient additions in mesocosms which had been run continuously at varying temperature and nutrient levels for 15 years prior to this study. Nutrient treatment had a significant effect on phytoplankton EPA and DHA concentrations and about 59 % of the variation in EPA and DHA concentrations could be explained by changes in the phytoplankton community structure. Increased biomass of diatoms corresponded with high EPA and DHA concentrations, while cyanobacteria/chlorophyte dominated mesocosm had low EPA and DHA concentrations. Warming had only a marginal effect on the EPA and DHA concentrations in these mesocosms. However, a significant interaction was observed with warming and N:P ratio. Our findings indicate that direct nutrient/temperature effects on algal physiology and PUFA metabolism were negligible and the changes in EPA and DHA concentrations were mostly related to the phytoplankton community structure and biomass. These results also imply that in shallow temperate lakes eutrophication, leading to increased dominance of cyanobacteria, will probably be a greater threat to phytoplankton EPA and DHA production than warming. EPA and DHA are nutritionally important for upper trophic level consumers and decreased production may impair secondary production.

Dam-induced flow velocity decrease leads to the transition from heterotrophic to autotrophic system through modifying microbial food web dynamics

The impoundment of reservoirs changes the river from a riverine heterotrophic system to a lacustrine autotrophic system, which could be attributed to the shift of pelagic microbial food webs in response to the dam-induced disturbances. However, little is known about what is the key factor controlling this variation and how different underlying interactions affect the food web dynamics. This study investigated the effects of flow velocity and nutrient supply on microbial plankton using a microcosm experiment. The results showed that flow velocity decrease was the main factor inducing the detritus-based food web transformed to the autotroph-based food web, with heterotrophic bacteria and protozoan dominated at high velocity, whereas phytoplankton and metazoan were prevalent in the lentic environment. The lentic-acclimated genera, such as Chlorella sp., Mallomonas sp. and Microcystis sp., showed hysteresis after the velocity recovery, suggesting the potential of algae bloom in reservoirs and even downstream of dams. We further conducted a flow-velocity manipulating experiment and constructed a multi-trophic nitrogen cycling model to provide a mechanistic explanation for the microbial food web dynamics and the nitrogen transformation performances. As indicated in model prediction and sensitivity analysis, the abiotic and biotic variations were directly or indirectly controlled by nutrient utilization and predator-prey interactions. Quantification of these bottom-up and top-down forces revealed the buffer role of predators in mitigating the positive effects of nutrient availability on autotrophs at low velocity and on heterotrophs at high velocity, respectively. This study highlights the importance of mastering the whole information of different trophic levels, in order to better capture the complex microbial food web interactions and the consequent biogeochemical processes in river-reservoir systems.

Length, width, shape regularity, and chain structure: time series analysis of phytoplankton morphology from imagery

Functional traits are increasingly used to assess changes in phytoplankton community structure and to link individual characteristics to ecosystem functioning. However, they are usually inferred from taxonomic identification or manually measured for each organism, both time consuming approaches. Instead, we focus on high throughput imaging to describe the main temporal variations of morphological changes of phytoplankton in Narragansett Bay, a coastal time-series station. We analyzed a 2-yr dataset of morphological features automatically extracted from continuous imaging of individual phytoplankton images (~ 105 million images collected by an Imaging FlowCytobot). We identified synthetic morphological traits using multivariate analysis and revealed that morphological variations were mainly due to changes in length, width, shape regularity, and chain structure. Morphological changes were especially important in winter with successive peaks of larger cells with increasing complexity and chains more clearly connected. Small nanophytoplankton were present year-round and constituted the base of the community, especially apparent during the transitions between diatom blooms. High inter-annual variability was also observed. On a weekly timescale, increases in light were associated with more clearly connected chains while more complex shapes occurred at lower nitrogen concentrations. On an hourly timescale, temperature was the determinant variable constraining cell morphology, with a general negative influence on length and a positive one on width, shape regularity, and chain structure. These first insights into the phytoplankton morphology of Narragansett Bay highlight the possible morphological traits driving the phytoplankton succession in response to light, temperature, and nutrient changes.

Impacts of atmospheric stilling and climate warming on cyanobacterial blooms: An individual-based modelling approach

Harmful algal blooms of the freshwater cyanobacteria genus Microcystis are a global problem and are expected to intensify with climate change. In studies of climate change impacts on Microcystis blooms, atmospheric stilling has not been considered. Stilling is expected to occur in some regions of the world with climate warming, and it will affect lake stratification regimes. We tested if stilling could affect water column Microcystis distributions using a novel individual-based model (IBM). Using the IBM coupled to a three-dimensional hydrodynamic model, we assessed responses of colonial Microcystis biomass to wind speed decrease and air temperature increase projected under a future climate. The IBM altered Microcystis colony size using relationships with turbulence from the literature, and included light, temperature, and nutrient effects on Microcystis growth using input data from a shallow urban lake. The model results show that dynamic variations in colony size are critical for accurate prediction of cyanobacterial bloom development and decay. Colony size (mean and variability) increased more than six-fold for a 20% decrease in wind speed compared with a 2 °C increase in air temperature. Our results suggest that atmospheric stilling needs to be included in projections of changes in the frequency, distribution and magnitude of blooms of buoyant, colony-forming cyanobacteria under climate change.

Characterization of Fine-Scale Turbulence Generated in a Laboratory Orbital Shaker and Its Influence on Skeletonema costatum

Turbulence is one of the ubiquitous aspects of aquatic systems and affects many physical and biological processes. Based on direct velocity measurements and a computational fluid dynamics (CFD) simulation, we characterized the distribution of the turbulent kinetic dissipations rates (ε) in an orbital shaker system within a range of rotation frequencies. CFD was able to estimate the ε distribution in containers accurately, which was confirmed by other two methods and was independent of velocity measurement. The results showed that ε was linearly correlated with the rotational frequencies. Despite the existence of gradients of ε and the fact that a mean circular horizontal flow was formed within the tank, the energy levels of the whole tank varied spatially within an order of magnitude and the ε distributions at different rotational frequencies were similar, suggesting that the ε distribution in the whole tank could be seen as quasi-homogeneous. To investigate the influence of turbulence on algae growth, culture experiments of a typical diatom—Skeletonema costatum were carried out under different turbulence conditions. Our results suggested turbulence mixing promoted nutrient uptake and growth of Skeletonema costatum, which could be attributed to the break of the diffusion-limited resource concentration boundary layer surrounding phytoplankton.

Evolution of toxins as a public good in phytoplankton

Toxic phytoplankton blooms have increased in many waterbodies worldwide with well-known negative impacts on human health, fisheries and ecosystems. However, why and how phytoplankton evolved toxin production is still a puzzling question, given that the producer that pays the costs often shares the benefit with other competing algae and thus provides toxins as a 'public good' (e.g. damaging a common competitor or predator). Furthermore, blooming phytoplankton species often show a high intraspecific variation in toxicity and we lack an understanding of what drives the dynamics of coexisting toxic and non-toxic genotypes. Here, by using an individual-based two-dimensional model, we show that small-scale patchiness of phytoplankton strains caused by demography can explain toxin evolution in phytoplankton with low motility and the maintenance of genetic diversity within their blooms. This patchiness vanishes for phytoplankton with high diffusive motility, suggesting different evolutionary pathways for different phytoplankton groups. In conclusion, our study reveals that small-scale spatial heterogeneity, generated by cell division and counteracted by diffusive cell motility and turbulence, can crucially affect toxin evolution and eco-evolutionary dynamics in toxic phytoplankton species. This contributes to a better understanding of conditions favouring toxin production and the evolution of public goods in asexually reproducing organisms in general.

Effects of zinc and iron on the abundance of Microcystis in Lake Taihu under green light and turbulence conditions

Trace element is one of the important factors affecting the growth of Microcystis. The effects of zinc (0.4 mg/L) and iron (2 mg/L) on the abundance of Microcystis in Lake Taihu were investigated under continuous turbulence and green light conditions in a microcosm experiment. The study results showed that the abundance of Microcystis in the zinc treatment and the iron treatment group was 8.30% and 214% of that in the control group at the end of the experiment, respectively. The proportion of Cyanobacteria in the total phytoplankton biomass in the control, iron treatment, and zinc treatment group decreased from 99.99% at the beginning of the experiment to 13%, 18%, and 1% at the end of the experiment, respectively. At the end of the microcosm experiment, the phytoplankton community was dominated by Bacillariophyta in the control group, accounting for 63%, but it was dominated by Chlorophyta in the zinc treatment and the iron treatment group, accounting for 89% and 42%, respectively. The study results showed that under green light and turbulence, 0.4 mg/L zinc remarkably decreased the abundance of Microcystis, but 2 mg/L iron effectively increased the number of Microcystis and other algae. This research results provided a new idea for controlling Microcystis blooms.

Ecological impacts of photosynthetic light harvesting in changing aquatic environments: A systematic literature map

Underwater light is spatially as well as temporally variable and directly affects phytoplankton growth and competition. Here we systematically (following the guidelines of PRISMA‐EcoEvo) searched and screened the published literature resulting in 640 individual articles. We mapped the conducted research for the objectives of (1) phytoplankton fundamental responses to light, (2) effects of light on the competition between phytoplankton species, and (3) effects of climate‐change‐induced changes in the light availability in aquatic ecosystems. Among the fundamental responses of phytoplankton to light, the effects of light intensity (quantity, as measure of total photon or energy flux) were investigated in most identified studies. The effects of the light spectrum (quality) that via species‐specific light absorbance result in direct consequences on species competition emerged more recently. Complexity in competition arises due to variability and fluctuations in light which effects are sparsely investigated on community level. Predictions regarding future climate change scenarios included changes in in stratification and mixing, lake and coastal ocean darkening, UV radiation, ice melting as well as light pollution which affect the underwater light‐climate. Generalization of consequences is difficult due to a high variability, interactions of consequences as well as a lack in sustained timeseries and holistic approaches. Nevertheless, our systematic literature map, and the identified articles within, provide a comprehensive overview and shall guide prospective research.

Temporal dependence of chlorophyll a-nutrient relationships in Lake Taihu: Drivers and management implications

Eutrophication and its associated algal blooms are principal environmental challenges confronting lakes worldwide. The empirical relationships between nutrient (total nitrogen, TN; total phosphorus, TP) and chlorophyll a (Chla) level are widely used as a theoretical basis for lake eutrophication management. Here, seasonal environmental variables and Chla from 2005 to 2020 in Chinese shallow eutrophic Lake Taihu were examined and Chla-nutrient equations in the entire period and annually from 2005 to 2020 were explored using 95% quantile regression model. The results showed robust linear relationships of logChla-logTN and logChla-logTP in the vast majority of cases. Based on Chla-nutrient equations in the entire study period, 0.69 mg/L TN and 52 μg/L TP are recommended as nutrient threshold in Lake Taihu. Furthermore, the results revealed increasing Chla sensitivity to nutrient for each study month (i.e. February, May, August, and November) from 2005 to 2020, whose drivers included increase in water temperature and water level, decrease in wind speed, mass ratio of nitrogen to phosphorus, and grazing effect. It is noteworthy that atmospheric stilling is likely to be the key climatic factor promoting annual peak Chla in Lake Taihu. For one, the deviations of the sub-index of Trophic State Index indicated that light is a critical limiting factor of summer Chla in Lake Taihu. For another, calmer water mainly due to atmospheric stilling decreased near 40% non-algal turbidity and a substantially increased buoyant cyanobacteria during the study period, improving phytoplankton "light niche". Thus, increasing algal sensitivity to nutrient occurred until the additional algal-turbidity induce further light limitations or the exhaustion of TN (or TP) cause nutrient limitation. Given atmospheric stilling is a global phenomenon, this study would affect future algal bloom mitigation efforts in shallow lakes as temperature is always the focus in the recent literatures on global climate change.

A deep learning method for cyanobacterial harmful algae blooms prediction in Taihu Lake, China

Cyanobacterial Harmful Algae Blooms (CyanoHABs) in the eutrophic lakes have become a global environmental and ecological problem. In this study, a CNN-LSTM integrated model for predicting the CyanoHABs area was proposed and applied to the prediction of the CyanoHABs area in Taihu Lake. Firstly, the time-series data of the CyanoHABs area in Taihu Lake for 20 years were accurately obtained using MODIS images from 2000 to 2019 based on the FAI method. Then, a principal component analysis was performed on the daily meteorological data for the month before the outbreak of CyanoHABs in Taihu Lake from 2000 to 2019 to determine the meteorological factors closely related to the outbreak of CyanoHABs. Finally, the features of CyanoHABs area and meteorological data were extracted by Convolutional Neural Networks (CNN) model and used as the input of Long Short Term Memory Network (LSTM). An integrated CNN-LSTM model approach was constructed for predicting the CyanoHABs area. The results show that high R² (0.91) and low mean relative error (17.42%) verified the validity of the FAI index to extract the CyanoHABs area in Taihu Lake; the meteorological factors closely related to the CyanoHABs outbreak in Taihu Lake are mainly temperature, relative humidity, wind speed, and precipitation; the CNN-LSTM integrated model has better prediction effect for both training and test sets compared with the CNN and LSTM models. This study provides an effective method for predicting temporal changes in the CyanoHABs area and offers new ideas for scientific and effective regulation of inland water safety.

Interactions of E. coli with algae and aquatic vegetation in natural waters

Both algae and bacteria are essential inhabitants of surface waters. Their presence is of ecological significance and sometimes of public health concern triggering various control actions. Interactions of microalgae, macroalgae, submerged aquatic vegetation, and bacteria appear to be important phenomena necessitating a deeper understanding by those involved in research and management of microbial water quality. Given the long-standing reliance on Escherichia coli as an indicator of the potential presence of pathogens in natural waters, understanding its biology in aquatic systems is necessary. The major effects of algae and aquatic vegetation on E. coli growth and survival, including changes in the nutrient supply, modification of water properties and constituents, impact on sunlight radiation penetration, survival as related to substrate attachment, algal mediation of secondary habitats, and survival inhibition due to the release of toxic substances and antibiotics, are discussed in this review. An examination of horizontal gene transfer and antibiotic resistance potential, strain-specific interactions, effects on the microbial, microalgae, and grazer community structure, and hydrodynamic controls is given. Outlooks due to existing and expected consequences of climate change and advances in observation technologies via high-resolution satellite imaging, unmanned aerial vehicles (drones), and mathematical modeling are additionally covered. The multiplicity of interactions among bacteria, algae, and aquatic vegetation as well as multifaceted impacts of these interactions, create a wide spectrum of research opportunities and technology developments.

Effects of light and water disturbance on the growth of Microcystis aeruginosa and the release of algal toxins

Eutrophication of water constitutes a serious threat to global water quality. Light intensity and water disturbance are important factors affecting the growth of algae and the release of algal toxins. In this study, algal growth indicators, algal enzyme systems, and algal toxin release in Microcystis aeruginosa under different light intensities and water disturbances were determined. The results showed that 2500 lx and 120 rpm were the optimal conditions for the growth of M. aeruginosa. The growth of algal cells was inhibited by high light intensity and high water disturbance. However, the optimal conditions for algal growth were not favorable conditions for the release of algal toxin. The highest concentration of microcystin-LR (MC-LR), observed at 4500 lx and 80 rpm, was 198.1 μg/L, whereas the highest single cell toxin production reached up to 10.49 × 10^-9  μg/cell at 7000 lx and 120 rpm. Redundancy analysis results showed that the concentration of MC-LR was positively correlated with algal cell density and antioxidant enzyme activities (superoxide dismutase, catalase, peroxidase, and malondialdehyde [MDA]) and negatively correlated with the total nitrogen and total phosphorus consumption rates and MDA. Single cell toxin production was negatively correlated with algal cell density and antioxidant enzyme activity but positively correlated with MDA content. PRACTITIONER POINTS: There was an optimal water disturbance condition for algae growth affected by the light intensity. Optimal conditions for algae cell growth are not necessarily the optimal conditions for algal toxin release. Enzyme indicators have correlation with the release of algae toxins and the growth of algae cells.

Effects of Vertical Spatial Overlap on Phytoplankton Diversity under Experimentally Altered Lake Stratification Regimes

In phytoplankton communities, competitive exclusion might occur when functionally similar species are impeded from regulating their positions along light and nutrient gradients to reduce niche overlap. Greater spatial overlap (SO) between species due to water column mixing could thus promote competitive exclusion, reducing community taxonomic diversity. However, greater SO could also promote coexistence of functionally different taxa. Using data from a whole-lake experiment, we investigated the effects of SO and other relevant environmental factors on phytoplankton diversity across the water columns of lake basins with different thermocline manipulations. We estimated SO using an in situ fluorometer, and overall community diversity microscopically. Using structured equation models, we estimated directional relationships between phytoplankton diversity, SO, the lake physical structure and the zooplankton community. No significant effect of SO on phytoplankton taxonomic diversity was observed, but higher SO was associated with greater functional diversity. Change in lake physical structure and in the zooplankton community also affected diversity, with a negative response to increased top-down interactions. Overall, despite the fact that the alteration of water column stratification structure and top-down interactions were stronger drivers of phytoplankton diversity in our system, some effect of spatial overlap on the outcome of inferred competitive interactions were observable.

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.

A critical review on operation and performance of source water control strategies for cyanobacterial blooms: Part II-mechanical and biological control methods

This review summarizes current knowledge on mechanical (artificial mixing, hypolimnetic aeration, dredging, and sonication) and biological (biomanipulation, macrophytes, and straws) methods for the management of cyanobacterial blooms in drinking water sources. Emphasis has been given to (i) the mechanism of cyanobacterial control, (ii) successful and unsuccessful case studies, and (iii) factors influencing successful implementation. Most mechanical and biological control strategies offer long-term control. However, their application can be cost-prohibitive and treatment efficacy is influenced by source water geometry and continual nutrient inputs from external sources. When artificial mixing and hypolimnetic oxygenation units are optimized based on source water characteristics, observed water quality benefits included increased dissolved oxygen contents, reduced internal loading of nutrients, and lower concentrations of reduced ions . Treatment efficacy during oxygenation and aeration was derailed by excessive sedimentation of organic matter and sediment characteristics such as low Fe/P ratios. Dredging is beneficial for contaminated sediment removal, but it is too costly to be a practical bloom control strategy for most systems. Sonication control methods have contradictory findings requiring further research to evaluate the efficacy and applicability for field-scale control of cyanobacteria. Biological control methods such as biomanipulation offer long-term treatment benefits; however, investigations on the mechanisms of field-scale cyanobacterial control are still limited, particularly with the use of macrophytes and straws. Each control method has site-specific strengths, limitations, and ecological impacts. Reduction of external nutrient inputs should still be a significant focus of restoration efforts as treatment benefits from mechanical and biological control were commonly offset by continued nutrient inputs.

Impact of light quality on freshwater phytoplankton community in outdoor mesocosms

In shallow lakes, wind wave turbulence alters underwater spectral composition, but the influence of this phenomenon on phytoplankton community structure is poorly understood. We used 100L mesocosms to investigate the influence of light quality on a natural phytoplankton community collected from Taihu Lake in China. The communities in mesocosms were exposed to sunlight filtered for white, blue, green, and red light, while wave-making pumps simulated wind wave turbulence similar to Taihu Lake. Over the course of experiment, each filtered light reduced the total phytoplankton abundance compared to white light. The mean abundance of phytoplankton in controls was 1.72, 1.78, and 7.89 times of that in the red, blue, and green light treatments. Red, blue, and green light significantly promoted the growth of cyanobacteria, green algae, and diatoms, respectively, and induced successional change of the phytoplankton species under the tested conditions. The proportion of Microcystis to total phytoplankton abundance in controls and red light shifted from 87.09% at the beginning to 37.95% and 56.30% at the end of the experiment, respectively, and maintained its dominance, whereas Microcystis lost its dominance and was replaced by Scenedesmus (53.78%) and Synedra (53.18%) in the blue and green light, respectively. Given the process of how these phytoplankton compete in designated spectrum, exploring these influences could help provide new insights into the dominance formation of toxic cyanobacteria.

Co-occurring microorganisms regulate the succession of cyanobacterial harmful algal blooms

Cyanobacterial harmful algal blooms (CyanoHABs) have been found to transmit from N₂ fixer-dominated to non-N₂ fixer-dominated in many freshwater environments when the supply of N decreases. To elucidate the mechanisms underlying such "counter-intuitive" CyanoHAB species succession, metatranscriptomes (biotic data) and water quality-related variables (abiotic data) were analyzed weekly during a bloom season in Harsha Lake, a multipurpose lake that serves as a drinking water source and recreational ground. Our results showed that CyanoHABs in Harsha Lake started with N₂-fixing Anabaena in June (ANA stage) when N was high, and transitioned to non-N₂-fixing Microcystis- and Planktothrix-dominated in July (MIC-PLA stage) when N became limited (low TN/TP). Meanwhile, the concentrations of cyanotoxins, i.e., microcystins were significantly higher in the MIC-PLA stage. Water quality results revealed that N species (i.e., TN, TN/TP) and water temperature were significantly correlated with cyanobacterial biomass. Expression levels of several C- and N-processing-related cyanobacterial genes were highly predictive of the biomass of their species. More importantly, the biomasses of Microcystis and Planktothrix were also significantly associated with expressions of microbial genes (mostly from heterotrophic bacteria) related to processing organic substrates (alkaline phosphatase, peptidase, carbohydrate-active enzymes) and cyanophage genes. Collectively, our results suggest that besides environmental conditions and inherent traits of specific cyanobacterial species, the development and succession of CyanoHABs are regulated by co-occurring microorganisms. Specifically, the co-occurring microorganisms can alleviate the nutrient limitation of cyanobacteria by remineralizing organic compounds.

Individual-based modelling of cyanobacteria blooms: Physical and physiological processes

Lakes and reservoirs throughout the world are increasingly adversely affected by cyanobacterial harmful algal blooms (CyanoHABs). The development and spatiotemporal distributions of blooms are governed by complex physical mixing and transport processes that interact with physiological processes affecting the growth and loss of bloom-forming species. Individual-based models (IBMs) can provide a valuable tool for exploring and integrating some of these processes. Here we contend that the advantages of IBMs have not been fully exploited. The main reasons for the lack of progress in mainstreaming IBMs in numerical modelling are their complexity and high computational demand. In this review, we identify gaps and challenges in the use of IBMs for modelling CyanoHABs and provide an overview of the processes that should be considered for simulating the spatial and temporal distributions of cyanobacteria. Notably, important processes affecting cyanobacteria distributions, in particular their vertical passive movement, have not been considered in many existing lake ecosystem models. We identify the following research gaps that should be addressed in future studies that use IBMs: 1) effects of vertical movement and physiological processes relevant to cyanobacteria growth and accumulations, 2) effects and feedbacks of CyanoHABs on their environment; 3) inter and intra-specific competition of cyanobacteria species for nutrients and light; 4) use of high resolved temporal-spatial data for calibration and verification targets for IBMs; and 5) climate change impacts on the frequency, intensity and duration of CyanoHABs. IBMs are well adapted to incorporate these processes and should be considered as the next generation of models for simulating CyanoHABs.

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.

Temporal-spatial features and key factors' analysis of vertical eddy diffusivities in Taihu Lake, China

Vertical eddy diffusivity (VED) is used to quantify the vertical mixing of water column, which has a profound influence on the evolution of aquatic ecosystems. Based on half-hourly water temperature measured at -20 cm and -150 cm depths from 2015 to 2017 at stations of Pingtaishan (PTS), Dapukou (DPK), Bifenggang (BFG), and Xiaoleishan (XLS) in Taihu Lake, the daily average VED is calculated according to the phase lag of water temperature series at two depths. The temporal and spatial features and possible evolution characters of vertical turbulences are then deliberated. The results show that the VED in Taihu Lake varies by several orders of magnitude. The weak VED exhibits stronger spatial heterogeneity and high frequency characteristics and vice versa for the strong VED. The VED in the center region of the lake is stronger, in comparison to bay areas. On seasonality, the VED is the strongest in winter, moderate in spring and autumn, and the weakest in summer. Analyses show that solar radiation and wind forcing are the key meteorological factors regulating VED changes, with the solar effect somewhat stronger than wind. It is also discussed potential roles of vertical mixing in cyanobacteria becoming dominant population in Taihu Lake.

Evidence of a rapid phosphorus-induced regime shift in a large deep reservoir

Ecological regime shift studies in freshwater systems are mainly limited to shallow lakes and reservoirs, while abrupt changes in deeper lakes are often attributed to climate change. Here, we demonstrate the application of regime shift theory to one of California's newest and deepest reservoirs, Diamond Valley Lake (DVL), which in recent years showed an unexpected rapid departure from its water quality conditions of the previous decade. The reservoir shifted from a well oxygenated condition with low phytoplankton growth to a hypoxic, phytoplankton-dominated turbid system. We statistically identified the critical stressor (phosphorus (P)), switch points, and its load threshold and characterized its transition to an alternative stable state and the stabilizing mechanisms contributing to hysteresis. We analyzed long-term environmental, chemical and flow data, conducted a hydrographic survey, and developed a hydrodynamic model to characterize the factors that contributed to regime shift and to evaluate different management strategies that might reverse this shift. Our findings indicate that large deep systems exhibit different transition dynamics in the presence of an acute stressor compared to regime shifts in shallow systems. A cumulative external TP load threshold of 4.6 mg m^-2 d^-1 added to the reservoir over nearly 11 months was identified as the critical stressor. For large deep systems, inherent morphometric features such as large relative depth combine with external stressors to drive regime shifts. Light winds, morphometric conditions impeding deep mixing, and a stable stratification that lasts up to 9 months makes DVL more susceptible to hypolimnetic hypoxia, an intrinsic factor accelerating regime shift. Results also suggest regime shift occurred in 2013, when new limnological processes were established to reinforce the new alternative stable state and existing ecosystem services were impaired. Interactions between hypoxia, internal P loading (~2.1 mg m^-2 d^-1), and seasonal cyanobacterial blooms were identified as mechanisms perpetuating the new alternative state.

Comparative analysis of Microcystis buoyancy in western Lake Erie and Saginaw Bay of Lake Huron

Microcystis is the predominant genus of harmful cyanobacterium in both Lake Erie and Saginaw Bay of Lake Huron and has the capacity to regulate the buoyancy of its colonies, sinking under certain conditions while floating towards the surface in others. Understanding the factors that control buoyancy is critical for interpretation of remote sensing data, modeling and forecasting harmful algal blooms within these two systems. To determine if Microcystis colony buoyancy in the two lakes responds similarly to diurnal light cycles, colony buoyant velocity (floating/sinking terminal velocity in a quiescent water column) and size were measured after manipulating the intensity of sunlight. Overall, there were more positively buoyant (floating) colonies in Lake Erie while most of the colonies in Saginaw Bay were negatively buoyant (sinking). In Lake Erie the colonies became less buoyant at increased light intensities and were less buoyant in the afternoon than in the morning. In both lakes, apparent colony density was more variable among small colonies (< 200 µm), whereas larger colonies showed a diminished response of density to light intensity and duration. These findings suggest that colony density becomes less plastic as colonies increase in size, leading to a weak relationship between size and velocity. These relationships may ultimately affect how the bloom is transported throughout each system and will help explain observed differences in vertical distribution and movement of Microcystis in the two lakes.

Stoichiometric imbalances complicate prediction of phytoplankton biomass in U.S. lakes: implications for nutrient criteria

Using National Lakes Assessment data, we evaluated the influence of total N (TN), total P (TP), and other variables on lake chlorophyll-a concentrations. With simple linear regressions, high TN/TP samples biased predictions based on TN, and low TN/TP samples biased predictions based on TP. The bias problem was corrected, and correlation was improved, by splitting the dataset at the TN/TP ratio we estimated to be indicative of a balanced supply and developing separate regressions that predict chlorophyll-a based on TP, TN, dissolved inorganic N (DIN), dissolved organic carbon (DOC), non-algal light attenuation, depth, area, latitude, elevation, and conductivity. Both nutrients were excellent predictors, and non-algal light attenuation was the next most influential predictor. The regression analysis suggested that a potential for P only limitation (high TN/TP, 17% of samples) or N only limitation (low TN/TP, 14% of samples) can be inferred at the extremes of the TN/TP range. However, 69% of samples had an intermediate TN/TP ratio where it is difficult to infer anything about potential nutrient limitations (biomass could be N limited, P limited, N and P co-limited, or not limited by nutrients at all). Our results show that when developing phytoplankton response relationships using cross-lake datasets that span a wide range of trophic states, it is important to consider whether and how biomass is influenced by confounding factors - such as differences in the relative supply of N and P - so that biomass is not underestimated or overestimated, and nutrient criteria are not under-protective or over-protective.