Eco-physiological adaptations that favour freshwater cyanobacteria in a changing climate

Declined nutrients stability shaped by water residence times in lakes and reservoirs under climate change

Water quality stability in lakes and reservoirs is essential for drinking water safety and ecosystem health, especially given the frequent occurrence of extreme climate events. However, the relationship between water quality stability and water residence time (WRT) has not been well elucidated. In this study, we explored the relationship based on nitrogen (N) and phosphorus (P) concentrations data in 11 lakes and 49 reservoirs in the Yangtze-Huaihe River basin from 2010 to 2022. Additionally, we examined the effects of hydrometeorological characteristics, the geomorphology of water bodies and catchments, and land use on the WRT, establishing a link between climate change and the stability of N and P in these water bodies. The results showed that a significant correlation between the stability of N and P in lakes and reservoirs and their WRT. The longer WRT tends to coincide with decreased stability and higher nutrient concentrations. Hydrometeorological factors are the primary factors on the WRT, with precipitation exerting the greatest effect, particularly under extreme drought. In recent years, extreme climatic events have intensified the fluctuations of WRT, resulting in a renewed increase in N and P concentrations and deterioration in stability. These findings highlight the importance of incorporating meteorological and hydrological factors alongside reinforcing ecological restoration into lake and reservoir management strategies, and providing a scientific basis for future efforts aimed at enhancing lake and reservoir water quality stability and safeguarding aquatic ecosystems.

Machine learning predicts the growth of cyanobacterial genera in river systems and reveals their different environmental responses

Cyanobacterial blooms are a common and serious problem in global freshwater environments. However, the response mechanisms of various cyanobacterial genera to multiple nutrients and pollutants, as well as the factors driving their competitive dominance, remain unclear or controversial. The relative abundance and cell density of two dominant cyanobacterial genera (i.e., Cyanobium and Microcystis) in river ecosystems along a gradient of anthropogenic disturbance were predicted by random forest with post-interpretability based on physicochemical indices. Results showed that the optimized predictions all reached strong fitting with R2 > 0.75, and conventional water quality indices played a dominant role. One-dimensional and two-dimensional partial dependence plot (PDP) revealed that the responses of Cyanobium and Microcystis to nutrients and temperature were similar, but they showed differences in preferrable nutrient utilization and response to pollutants. Further prediction and PDP for the ratio of Cyanobium and Microcystis unveiled that their distinct responses to PAHs and SPAHs were crucial drivers for their competitive dominance over each other. This study presents a new way for analyzing the response of cyanobacterial genera to multiple environmental factors and their dominance relationships by interpretable machine learning, which is suitable for the identification and interpretation of high-dimensional nonlinear ecosystems with complex interactions.

Physiological and transcriptome level responses of Microcystis aeruginosa and M. viridis to environmental concentrations of triclosan

The toxicity of triclosan (TCS) to various aquatic organisms has been demonstrated at environmental concentrations. However, the effects and mechanisms of TCS on toxic cyanobacteria remains largely unexplored. This study investigated the physiological and molecular variations in two representative toxic Microcystis species (M. aeruginosa and M. viridis) under exposure to TCS for 12 d. Our findings demonstrated that the median effective concentration (EC50) of TCS for both Microcystis species were close to the levels detected in the environment (M. aeruginosa: 9.62 μg L-1; M. viridis: 27.56 μg L-1). An increased level of reactive oxygen species (ROS) was observed in Microcystis, resulting in oxidative damage when exposed to TCS at concentrations ranging from 10 μg L-1 to 50 μg L-1. The photosynthetic activity of Microcystis had a certain degree of recovery capability at low concentrations of TCS. Compared to M. aeruginosa, the higher recovery capability of the photosynthetic system in M. viridis would be mainly attributed to the increased ability for PSII repair and phycobilisome synthesis. Additionally, the synthesis of microcystins in the two species and the release rate in M. viridis significantly increased under 10-50 μg L-1 TCS. At the molecular level, exposure to TCS at EC50 for 12 d induced the dysregulation of genes associated with photosynthesis and antioxidant system. The upregulation of genes associated with microcystin synthesis and nitrogen metabolism further increased the potential risk of microcystin release. Our results revealed the aquatic toxicity and secondary ecological risks of TCS at environmental concentrations, and provided theoretical data with practical reference value for TCS monitoring.

Phytoplankton biomass in northern lakes reveals a complex response to global change

Global change may introduce fundamental alterations in phytoplankton biomass and community structure that can alter the productivity of northern lakes. In this study, we utilized Swedish and Finnish monitoring data from lakes that are spatially (135 lakes) and temporally (1995-2019, 110 lakes) extensive to assess how phytoplankton biomass (PB) of dominant phytoplankton groups related to changes in water temperature, pH and key nutrients [total phosphorus (TP), total nitrogen (TN), total organic carbon (TOC), iron (Fe)] along spatial (Fennoscandia) and temporal (25 years) gradients. Using a machine learning approach, we found that TP was the most important determinant of total PB and biomass of a specific species of Raphidophyceae - Gonyostomum semen - and Cyanobacteria (both typically with adverse impacts on food-webs and water quality) in spatial analyses, while Fe and pH were second in importance for G. semen and TN and pH were second and third in importance for Cyanobacteria. However, in temporal analyses, decreasing Fe and increasing pH and TOC were associated with a decrease in G. semen and an increase in Cyanobacteria. In addition, in many lakes increasing TOC seemed to have generated browning to an extent that significantly reduced PB. The identified discrepancy between the spatial and temporal results suggests that substitutions of data for space-for-time may not be adequate to characterize long-term effects of global change on phytoplankton. Further, we found that total PB exhibited contrasting temporal trends (increasing in northern- and decreasing in southern Fennoscandia), with the decline in total PB being more pronounced than the increase. Among phytoplankton, G. semen biomass showed the strongest decline, while cyanobacterial biomass showed the strongest increase over 25 years. Our findings suggest that progressing browning and changes in Fe and pH promote significant temporal changes in PB and shifts in phytoplankton community structures in northern lakes.

Fluvial carbon dioxide emissions peak at the permafrost thawing front in the Western Siberia Lowland

In order to foresee the impact of permafrost thaw on CO2 emissions by high-latitude rivers, in-situ measurements across a permafrost and climate/vegetation gradient, coupled with assessment of possible physico-chemical and landscape controlling factors are necessary. Here we chose 34 catchments of variable stream order (1 to 9) and watershed size (1 to >105 km2) located across a permafrost and biome gradient in the Western Siberian Lowland (WSL), from the permafrost-free southern taiga to the continuous permafrost zone of tundra. Across the south-north transect, maximal CO2 emissions (2.2 ± 1.1 g C-CO2 m-2 d-1) occurred from rivers of the discontinuous/sporadic permafrost zone, i.e., geographical permafrost thawing boundary. In this transitional zone, fluvial C emission to downstream export ratio was as high as 8.0, which greatly (x 10) exceeded the ratio in the permafrost free and continuous permafrost zones. Such a high evasion at the permafrost thawing front can stem from an optimal combination of multiple environmental factors: maximal active layer thickness, sizable C stock in soils, and mobilization of labile organic nutrients from dispersed peat ice that enhanced DOC and POC processing in the water column, likely due to priming effect. Via a substituting space for time approach, we foresee an increase in CO2 and CH4 fluvial evasion in the continuous and discontinuous permafrost zone, which is notably linked to the greening of tundra increases in biomass of the riparian vegetation, river water warming and thermokarst lake formation on the watershed.

Unprecedented Harmful algal bloom in the UK and Ireland's largest lake associated with gastrointestinal bacteria, microcystins and anabaenopeptins presenting an environmental and public health risk

Harmful Algal Blooms (HABs) are outbreaks of aquatic toxic microalgae emerging as a global problem driven by nutrient enrichment, global climate change and invasive species. We uniquely describe a HAB of unprecedented duration, extent and magnitude during 2023 in Lough Neagh; the UK and Ireland's largest freshwater lake, using an unparalleled combination of satellite imagery, nutrient analysis, 16S rRNA gene sequencing and cyanotoxin profiling. The causative agent Microcystis aeruginosa accounted for over a third of DNA in water samples though common bacterioplankton species also bloomed. Water phosphate levels were hypertrophic and drove local algal biomass. The HAB pervaded the entire ecosystem with algal mats accumulating around jetties, marinas and lock gates. Over 80 % of bacterial DNA isolated from algal mat samples consisted of species associated with wildfowl or livestock faeces and human-effluent wastewater including 13 potential pathogens that can cause serious human illness including: E. coli, Salmonella, Enterobacter and Clostridium among others. Ten microcystins, nodularin and two anabaenopeptin toxins were confirmed as present (with a further microcystin and four anabaenopeptins suspected), with MC-RR and -LR in high concentrations at some locations (1,137-18,493 μg/L) with MC-LR exceeding World Health Organisation (WHO) recreational exposure guidelines in all algal mats sampled. This is the first detection of anabaenopeptins in any waterbody on the island of Ireland. Notwithstanding the ecological impacts, this HAB represented an environmental and public health risk, curtailing recreational activities in-and-around the lake and damaging local businesses. Reducing agricultural runoff and discharge from human-effluent wastewater treatment to manage nutrient loading, and the public health risk, should be the top priority of stakeholders, especially government. Key recommendations include Nature-based Solutions that avoid conflict with the productivity and profitability of the farming sector enhancing sustainability. We hope this stimulates real-world action to resolve the problems besetting this internationally important ecosystem.

Assessing thallium phycoremediation by applying Anabaena laxa and Nostoc muscorum and exploring its effect on cellular growth, antioxidant, and metabolic profile

Thallium (Tl), a key element in high-tech industries, is recognized as a priority pollutant by the US EPA and EC. Tl accumulation threatens aquatic ecosystems. Despite its toxicity, little is known about its impact on cyanobacteria. This study explores the biochemical mechanisms of Tl(I) toxicity in cyanobacteria, focusing on physiology, metabolism, oxidative damage, and antioxidant responses. To this end, Anabaena and Nostoc were exposed to 400 µg/L, and 800 µg/L of Tl(I) over seven days. Anabaena showed superior Tl(I) accumulation with 7.8% removal at 400 µg/L and 9.5% at 800 µg/L, while Nostoc removed 2.2% and 7.4%, respectively. Tl(I) exposure significantly reduced the photosynthesis rate and function, more than in Nostoc. It also altered primary metabolism, increasing sugar levels and led to higher amino and fatty acids levels. While Tl(I) induced cellular damage in both species, Anabaena was less affected. Both species enhanced their antioxidant defense systems, with Anabaena showing a 175.6% increase in SOD levels under a high Tl(I) dose. This suggests that Anabaena's robust biosorption and antioxidant systems could be effective for Tl(I) removal. The study improves our understanding of Tl(I) toxicity, tolerance, and phycoremediation in cyanobacteria, aiding future bioremediation strategies.

Climate change triggered planktonic cyanobacterial blooms in a regulated temperate river

Harmful algae blooms are a rare phenomenon in rivers but seem to increase with climate change and river regulation. To understand the controlling factors of cyanobacteria blooms that occurred between 2017 and 2020 over long stretches (> 250 km) of the regulated Moselle River in Western Europe, we measured physico-chemical and biological variables and compared those with a long-term dataset (1997-2016). Cyanobacteria (Microcystis) dominated the phytoplankton community in the late summers of 2017-2020 (cyano-period) with up to 110 µg Chlorophyll-a/L, but had not been observed in the river in the previous 20 years. From June to September, the average discharge in the Moselle was reduced to 69-76% and water temperature was 0.9-1.8 °C higher compared to the reference period. Nitrogen (N), phosphorus (P) and silica (Si) declined since 1997, albeit total nutrient concentrations remained above limiting conditions in the study period. Cyanobacterial blooms correlated best with low discharge, high water temperature and low nitrate. We conclude that the recent cyanobacteria blooms have been caused by dry and warm weather resulting in low flow conditions and warm water temperature in the regulated Moselle. Under current climate projections, the Moselle may serve as an example for the future of regulated temperate rivers.

The ice phenology as a predictor of Planktothrix rubescens bloom in vegetation season in temperate lakes

Introduction

Global warming affects air and water temperatures, which impacts the phenology of lakes and aquatic ecosystems. These changes are most noticeable during winter, when the potentially toxic Planktothrix rubescens forms its inoculum for annual blooms. Mostly, research has been conducted on alpine lakes, where blooms have persisted for decades, while a few have focused on temperate lakes. Our study aimed to determine the factors influencing the dynamics of the development of P. rubescens in temperate lakes where blooms occasionally occur, with a particular emphasis on the role of ice phenology.

Methods

We investigated the vertical distribution of P. rubescens in an annual cycle in three temperate lakes. Samples were collected monthly in the winter and biweekly during the vegetative seasons. Overall, 434 samples were collected and analyzed according to biological and chemical parameters. Physical parameters were measured in situ.

Results

The vegetation seasons in temperate lakes showed a similar development pattern in the P. rubescens population as that in alpine lakes. Our results also show the influence of physical and chemical factors on the vertical distribution of this cyanobacterium. These results revealed the significant impact of P. rubescens filaments on phytoplankton biodiversity and biomass. Our data show the role of ice phenology in the establishment of the winter inoculum of P. rubescens and its further mass development until its disappearance in autumn.

Conclusion

A climate-zone-independent pattern of P. rubescens blooms was observed during the vegetation periods. The population of P. rubescens was more influenced by physical factors than by the availability of dissolved nutrients in the water. Despite the same etiology, global warming has been shown to cause different responses in aquatic ecosystems, which affect the different nature of P. rubescens appearances. We associated blooms in temperate lakes, in contrast to alpine lakes, mainly with the presence of ice cover during severe winters, when the species establishes its inoculum. Hence, blooms in temperate lakes occur at different time intervals. Therefore, the dynamics of periodic blooms of P. rubescens in temperate lakes provide novel knowledge to the case study and a counterpoint to permanent blooms found in deep alpine lakes.

An investigation of cyanobacteria, cyanotoxins and environmental variables in selected drinking water treatment plants in New Jersey

Harmful Algal Blooms (HAB) have the potential to impact human health primarily through their possible cyanotoxins production. While conventional water treatments can result in the removal of unlysed cyanobacterial cells and low levels of cyanotoxins, during severe HAB events, cyanotoxins can break through and can be present in the treated water due to a lack of adequate toxin treatment. The objectives of this study were to assess the HAB conditions in drinking water sources in New Jersey and investigate relationships between environmental variables and cyanobacterial communities in these drinking water sources. Source water samples were collected monthly from May to October 2019 and analyzed for phytoplankton and cyanobacterial cell densities, microcystins, cylindrospermopsin, Microcystis 16S rRNA gene, microcystin-producing mcyB gene, Raphidiopsis raciborskii-specific rpoC1 gene, and cylindrospermopsin-producing pks gene. Water quality parameters included water temperature, pH, dissolved oxygen, specific conductance, fluorescence of phycocyanin and chlorophyll, chlorophyll-a, total suspended solids, total dissolved solids, dissolved organic carbon, total nitrogen, ammonia, and total phosphorus. In addition to source waters, microcystins and cylindrospermopsin were analyzed for treated waters. The results showed all five selected New Jersey source waters had high total phosphorus concentrations that exceeded the established New Jersey Surface Water Quality Standards for lakes and rivers. Commonly found cyanobacteria were identified, such as Microcystis and Dolichospermum. Site E was the site most susceptible to HABs with significantly greater HAB variables, such as extracted phycocyanin, fluorescence of phycocyanin, cyanobacterial cell density, microcystins, and Microcystis 16S rRNA gene. All treated waters were undetected with microcystins, indicating treatment processes were effective at removing toxins from source waters. Results also showed that phycocyanin values had a significantly positive relationship with microcystin concentration, copies of Microcystis 16S rRNA and microcystin-producing mcyB genes, suggesting these values can be used as a proxy for HAB monitoring. This study suggests that drinking water sources in New Jersey are vulnerable to forthcoming HAB. Monitoring and management of source waters is crucial to help safeguard public health.

Dependence of evolution of Cyanobacteria superiority on temperature and nutrient use efficiency in a meso-eutrophic plateau lake

Algal blooms in lakes have been a challenging environmental issue globally under the dual influence of human activity and climate change. Considerable progress has been made in the study of phytoplankton dynamics in lakes; The long-term in situ evolution of dominant bloom-forming cyanobacteria in meso-eutrophic plateau lakes, however, lacks systematic research. Here, the monthly parameters from 12 sampling sites during the period of 1997-2022 were utilized to investigate the underlying mechanisms driving the superiority of bloom-forming cyanobacteria in Erhai, a representative meso-eutrophic plateau lake. The findings indicate that global warming will intensify the risk of cynaobacteria blooms, prolong Microcystis blooms in autumn to winter or even into the following year, and increase the superiority of filamentous Planktothrix and Cylindrospermum in summer and autumn. High RUETN (1.52 Biomass/TN, 0.95-3.04 times higher than other species) under N limitation (TN < 0.5 mg/L, TN/TP < 22.6) in the meso-eutrophic Lake Erhai facilitates the superiority of Dolichospermum. High RUETP (43.8 Biomass/TP, 2.1-10.2 times higher than others) in TP of 0.03-0.05 mg/L promotes the superiority of Planktothrix and Cylindrospermum. We provided a novel insight into the formation of Planktothrix and Cylindrospermum superiority in meso-eutrophic plateau lake with low TP (0.005-0.07 mg/L), which is mainly influenced by warming, high RUETP and their vertical migration characteristics. Therefore, we posit that although the obvious improvement of lake water quality is not directly proportional to the control efficacy of cyanobacterial blooms, the evolutionary shift in cyanobacteria population structure from Microcystis, which thrives under high nitrogen and phosphorus conditions, to filamentous cyanobacteria adapted to low nitrogen and phosphorus levels may serve as a significant indicator of water quality amelioration. Therefore, we suggest that the risk of filamentous cyanobacteria blooms in the meso-eutrophic plateau lake should be given attention, particularly in light of improving water quality and global warming, to ensure drinking water safety.

Development of a digital droplet PCR approach for the quantification of soil micro-organisms involved in atmospheric CO2 fixation

Carbon-fixing micro-organisms (CFMs) play a pivotal role in soil carbon cycling, contributing to carbon uptake and sequestration through various metabolic pathways. Despite their importance, accurately quantifying the absolute abundance of these micro-organisms in soils has been challenging. This study used a digital droplet polymerase chain reaction (ddPCR) approach to measure the abundance of key and emerging CFMs pathways in fen and bog soils at different depths, ranging from 0 to 15 cm. We targeted total prokaryotes, oxygenic phototrophs, aerobic anoxygenic phototrophic bacteria and chemoautotrophs, optimizing the conditions to achieve absolute quantification of these genes. Our results revealed that oxygenic phototrophs were the most abundant CFMs, making up 15% of the total prokaryotic abundance. They were followed by chemoautotrophs at 10% and aerobic anoxygenic phototrophic bacteria at 9%. We observed higher gene concentrations in fen than in bog. There were also variations in depth, which differed between fen and bog for all genes. Our findings underscore the abundance of oxygenic phototrophs and chemoautotrophs in peatlands, challenging previous estimates that relied solely on oxygenic phototrophs for microbial carbon dioxide fixation assessments. Incorporating absolute gene quantification is essential for a comprehensive understanding of microbial contributions to soil processes. This approach sheds light on the complex mechanisms of soil functioning in peatlands.

Multivariate extremes in lakes

Extreme within-lake conditions have the potential to exert detrimental effects on lakes. Here we use satellite observations to investigate how the occurrence of multiple types of extremes, notably algal blooms, lake heatwaves, and low lake levels, have varied in 2724 lakes since the 1980s. Our study, which focuses on bloom-affected lakes, suggests that 75% of studied lakes have experienced a concurrent increase in at least two of the extremes considered (27% defined as having a notable increase), with 25% experiencing an increase in frequency of all three extremes (5% had a notable increase). The greatest increases in the frequency of these extremes were found in regions that have experienced increases in agricultural fertilizer use, lake warming, and a decline in water availability. As extremes in lakes become more common, understanding their impacts must be a primary focus of future studies and they must be carefully considered in future risk assessments.

Characterizing the Impact of Cyanobacterial Blooms on the Photoreactivity of Surface Waters from New York Lakes: A Combined Statewide Survey and Laboratory Investigation

Cyanobacterial blooms introduce autochthonous dissolved organic matter (DOM) into aquatic environments, but their impact on surface water photoreactivity has not been investigated through collaborative field sampling with comparative laboratory assessments. In this work, we quantified the apparent quantum yields (Φapp,RI) of reactive intermediates (RIs), including excited triplet states of dissolved organic matter (3DOM*), singlet oxygen (1O2), and hydroxyl radicals (•OH), for whole water samples collected by citizen volunteers from more than 100 New York lakes. Multiple comparisons tests and orthogonal partial least-squares analysis identified the level of cyanobacterial chlorophyll a as a key factor in explaining the enhanced photoreactivity of whole water samples sourced from bloom-impacted lakes. Laboratory recultivation of bloom samples in bloom-free lake water demonstrated that apparent increases in Φapp,RI during cyanobacterial growth were likely driven by the production of photoreactive moieties through the heterotrophic transformation of freshly produced labile bloom exudates. Cyanobacterial proliferation also altered the energy distribution of 3DOM* and contributed to the accelerated transformation of protriptyline, a model organic micropollutant susceptible to photosensitized reactions, under simulated sunlight conditions. Overall, our study provides insights into the relationship between the photoreactivity of surface waters and the limnological characteristics and trophic state of lakes and highlights the relevance of cyanobacterial abundance in predicting the photoreactivity of bloom-impacted surface waters.

Employing hybrid deep learning for near-real-time forecasts of sensor-based algal parameters in a Microcystis bloom-dominated lake

Harmful cyanobacterial blooms (CyanoHABs) are increasingly impacting the ecosystem of lakes, reservoirs and estuaries globally. The integration of real-time monitoring and deep learning technology has opened up new horizons for early warnings of CyanoHABs. However, unlike traditional methods such as pigment quantification or microscopy counting, the high-frequency data from in-situ fluorometric sensors display unpredictable fluctuations and variability, posing a challenge for predictive models to discern underlying trends within the time-series sequence. This study introduces a hybrid framework for near-real-time CyanoHABs predictions in a cyanobacterium Microcystis-dominated lake - Lake Dianchi, China. The proposed model was validated using hourly Chlorophyll-a (Chl a) concentrations and algal cell densities. Our results demonstrate that applying decomposition-based singular spectrum analysis (SSA) significantly enhances the prediction accuracy of subsequent CyanoHABs models, particularly in the case of temporal convolutional network (TCN). Comparative experiments revealed that the SSA-TCN model outperforms other SSA-based deep learning models for predicting Chl a (R2 = 0.45-0.93, RMSE = 2.29-5.89 μg/L) and algal cell density (R2 = 0.63-0.89, RMSE = 9489.39-16,015.37 cells/mL) at one to four steps ahead predictions. The forecast of bloom intensities achieved a remarkable accuracy of 98.56 % and an average precision rate of 94.04 % ± 0.05 %. In addition, scenarios involving various input combinations of environmental factors demonstrated that water temperature emerged as the most effective driver for CyanoHABs predictions, with a mean RMSE of 2.94 ± 0.12 μg/L, MAE of 1.55 ± 0.09 μg/L, and R2 of 0.83 ± 0.01. Overall, the newly developed approach underscores the potential of a well-designed hybrid deep-learning framework for accurately predicting sensor-based algal parameters. It offers novel perspectives for managing CyanoHABs through online monitoring and artificial intelligence in aquatic ecosystems.

Experimental warming promotes CO2 uptake but hinders carbon incorporation toward higher trophic levels in cyanobacteria-dominated freshwater communities

Shallow freshwaters can exchange large amounts of carbon dioxide (CO2) with the atmosphere and also store significant quantities of carbon (C) in their sediments. Current warming and eutrophication pressures might alter the role of shallow freshwater ecosystems in the C cycle. Although eutrophication has been widely associated to an increase in total phytoplankton biomass and particularly of cyanobacteria, it is still poorly understood how warming may affect ecosystem metabolism under contrasting phytoplankton community composition. We studied the effects of experimental warming on CO2 fluxes and C allocation on two contrasting natural phytoplankton communities: chlorophytes-dominated versus cyanobacteria-dominated, both with a similar zooplankton community with a potentially high grazing capacity (i.e., standardized density of large-bodied cladocerans). The microcosms were subject to two different constant temperatures (control and +4 °C, i.e., 19.5 vs 23.5 °C) and we ensured no nutrient nor light limitation. CO2 uptake increased with warming in both communities, being the strongest in the cyanobacteria-dominated communities. However, only a comparatively minor share of the fixed C translated into increased phytoplankton (Chl-a), and particularly a negligible share translated into zooplankton biomass. Most C was either dissolved in the water (DIC) or sedimented, the latter being potentially available for mineralization into DIC and CO2, or methane (CH4) when anoxic conditions prevail. Our results suggest that C uptake increases with warming particularly when cyanobacteria dominate, however, due to the low efficiency in transfer through the trophic web the final fate of the fixed C may be substantially different in the long run.

Quorum sensing regulation in Microcystis aeruginosa: Insights into AHL-mediated physiological processes and MC-LR production

Quorum sensing (QS) is a widespread regulatory mechanism in Gram-negative bacteria, primarily involving the secretion of N-acyl homoserine lactone (AHL) to facilitate population density sensing. However, the existence of QS in blue-green algae, a subset of photoautotrophic Gram-negative bacteria forming high-density communities in water blooms, remains elusive. This study delves into the unexplored realm of QS in Microcystis aeruginosa (M. aeruginosa) by investigating AHL-related regulatory mechanisms and their impact on various physiological processes. Utilizing high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS) and biosensors, a hitherto unknown long-chain AHL exhibiting a mass-to-charge ratio of 318 was identified in sterile M. aeruginosa cultures. Our investigation focused on discerning correlations between AHL activity fluctuations and key parameters such as microcystin (MC-LR) production, algal density, photosynthesis, buoyancy, and aggregation. Furthermore, the AHL extract was introduced during the logarithmic stage of M. aeruginosa cultures to observe the response in physiological processes. The results revealed that AHL, functioning as an autoinducer (AI), positively influenced algal growth and photosynthesis, as evidenced by the upregulated photosynthetic conversion efficiency of PSI and chlorophyll synthesis gene (psbA). AI also played a crucial role in altering surface characteristics through the synthesis of polysaccharides and proteins in EPS, subsequently promoting cell aggregation. Concomitantly, AI upregulated mcyD, enhancing the synthesis of MC-LR. Notably, our investigation pinpointed the initiation of QS in Microcystis at a density of approximately 1.22 × 10^7 cells/mL. This groundbreaking evidence underscores the regulatory role of AI in governing the physiological processes of growth, aggregation, buoyancy, and MC-LR production by activating pertinent gene expressions. This study significantly expands the understanding of QS in AHL, providing crucial insights into the regulatory networks operating in blue-green algae.

Intensification of harmful cyanobacterial blooms in a eutrophic, temperate lake caused by nitrogen, temperature, and CO2

Warmer temperatures can significantly increase the intensity of cyanobacterial harmful algal blooms (CHABs) in eutrophic freshwater ecosystems. However, few studies have examined the effects of CO2 enrichment in tandem with elevated temperature and/or nutrients on cyanobacterial taxa in freshwater ecosystems. Here, we observed changes in the biomass of cyanobacteria, nutrients, pH, and carbonate chemistry over a two-year period in a shallow, eutrophic freshwater lake and performed experiments to examine the effects and co-effects of CO2, temperature, and nutrient enrichment on cyanobacterial and N2-fixing (diazotrophic) communities assessed via high throughput sequencing of the 16S rRNA and nifH genes, respectively. During both years, there were significant CHABs (50-500 μg cyanobacterial chlorophyll-a L-1) and lake CO2 levels were undersaturated (≤300 μatm pCO2). NH4+ significantly increased the net growth rates of cyanobacteria as well as the biomass of the diazotrophic cyanobacterial order Nostocales under elevated and ambient CO2 conditions. In a fall experiment, the N2 fixation rates of Nostocales were significantly higher when populations were enriched with CO2 and P, relative to CO2-enriched populations that were not amended with P. During a summer experiment, N2 fixation rates increased significantly under N and CO2 - enriched conditions relative to N-enriched and ambient CO2 conditions. Nostocales dominated the diazotrophic communities of both experiments, achieving the highest relative abundance under CO2-enriched conditions when N was added in the first experiment and when CO2 and temperature were elevated in the second experiment, when N2 fixation rates also increased significantly. Collectively, this study indicates that N promotes cyanobacterial blooms including those formed by Dolichospermum and that the biomass and N2 fixation rates of diazotrophic cyanobacterial taxa may benefit from enhanced CO2 levels in eutrophic lakes.

Long-term stability of the genome structure of the cyanobacterium, Dolichospermum in a deep German lake

Dolichospermum is a cyanobacterial genus commonly associated with toxic blooms in lakes and brackish water bodies worldwide, and is a long-term resident of Lake Stechlin, northeastern Germany. In recent decades, shifts in the phosphorus loading and phytoplankton species composition have seen increased biomass of Dolichospermum during summer blooms from 1998, peaking around 2005, and declining after 2020. Cyanobacteria are known to rapidly adapt to new environments, facilitated by genome adaptation. To investigate the changes in genomic features that may have occurred in Lake Stechlin Dolichospermum during this time of increased phosphorus loading and higher biomass, whole genome sequence analysis was performed on samples of ten akinetes isolated from ten, 1 cm segments of a sediment core, representing a ∼45-year period from 1970 to 2017. Comparison of these genomes with genomes of extant isolates revealed a clade of Dolichospermum that clustered with the ADA-6 genus complex, with remarkable genome stability, without gene gain or loss events in response to recent environmental changes. The genome characteristics indicate that this species is suited to a deep-chlorophyll maximum, including additional light-harvesting and phosphorus scavenging genes. Population SNP analysis revealed two sub-populations that shifted in dominance as the lake transitioned between oligotrophic and eutrophic conditions. Overall, the results show little change within the population, despite diversity between extant populations from different geographic locations and the in-lake changes in phosphorus concentrations.

Unveiling the link between Raphidiopsis raciborskii blooms and saxitoxin levels: Evaluating water quality in tropical reservoirs, Brazil

The proliferation of Raphidiopsis raciborskii blooms has sparked concerns regarding potential human exposure to heightened saxitoxins (STXs) levels. Thus, comprehending how environmental elements drive the proliferation of this STXs-producing species can aid in predicting human exposure risks. This study aimed to explore the link between cyanobacteria R. raciborskii, STXs cyanotoxins, and environmental factors in 37 public supply reservoirs in the tropical region and assess potential health hazards these toxins pose in the reservoir waters. A Structural Equation Model was used to assess the impact of environmental factors (water volume and physical and chemical variables) on R. raciborskii biomass and STXs levels. Furthermore, the potential risk of STXs exposure from consuming untreated reservoir water was evaluated. Lastly, the cumulative distribution function (CDF) of STXs across the reservoirs was computed. Our findings revealed a correlation between R. raciborskii biomass and STXs concentrations. Total phosphorus emerged as a critical environmental factor positively influencing species biomass and indirectly affecting STXs levels. pH significantly influenced STXs concentrations, indicating different factors influencing R. raciborskii biomass and STXs. Significantly, for the first time, the risk of STXs exposure was gauged using the risk quotient (HQ) for untreated water consumption from public supply reservoirs in Brazil's semi-arid region. Although the exposure risks were generally low to moderate, the CDF underscored the risk of chronic exposure due to low toxin concentrations in over 90% of samples. These outcomes emphasize the potential expansion of R. raciborskii in tropical settings due to increased phosphorus, amplifying waterborne STXs levels and associated intoxication risks. Thus, this study reinforces the importance of nutrient control, particularly phosphorus regulation, as a mitigation strategy against R. raciborskii blooms and reducing STXs intoxication hazards.

Physiology, microcystin production, and transcriptomic responses of Microcystis aeruginosa exposed to calcium and magnesium

Calcium ions (Ca2+) and magnesium ions (Mg2+) are pivotal in the community composition and stability of harmful cyanobacteria, yet the physiological and molecular responses remains poorly understood. This study aims to explore these responses in the high microcystin producer Microcystis aeruginosa (M. aeruginosa). Results indicate that the growth of M. aeruginosa is inhibited by Ca2+/Mg2+ exposure (0.5-10 mM), while Fv/Fm photosynthetic parameters and extracellular microcystin-leucine-arginine (MC-LR) concentrations increase. Additionally, MC-LR release is significantly elevated under exposure to Ca2+/Mg2+, posing potential aquatic environmental risks. Transcriptomic analysis reveals downregulation of genes related to cell architecture, membrane transport, and metabolism, while the genes linked to photosynthesis electron transmission and heavy metal-responsive transcriptional regulators are upregulated to adapt to environmental changes. Further analysis reveals that Ca2+ and Mg2+ primarily impact sulfur metabolism and transport of amino acids and mineral within cells. These findings provide insights into M. aeruginosa cells responses to Ca2+ and Mg2+ exposure.

Methane flux at the water-gas interface is influenced by complex interactions among phytoplankton, phosphorus inputs and methane-functional bacteria: A microcosm systems study

Phytoplankton affect carbon cycling and emissions in eutrophic reservoirs dramatically, but our knowledge about carbon emissions response to phytoplankton bloom and phosphorus enrichment is rather limited. Here we performed a microcosm experiment with five treatments to investigate how phytoplankton blooms and phosphorus addition will impact the carbon emissions and the methane-functional bacterial community. During the 43-day incubation, the CH4 and CO2 flux at the water-air interface in the five water columns fluctuated between 7.536 and 16.689 μmol and between 2788.501 and 4142.726 μmol, respectively. The flux of CH4 and CO2 during phytoplankton decay was 1.542 to 10.397 times and 4.203 to 8.622 times higher, respectively, compared to that during phytoplankton growth. Furthermore, exogenous phosphorus increases bloom biomass of phytoplankton and subsequent CH4 production, even with low nitrogen concentrations. The addition of 1 mg KH2PO4 resulted in a conservative increase of 0.0715 μmol in CH4 emission and 11.911 μmol in CO2 emission in the water column, respectively, compared to the in-situ water column. High throughput sequencing determined that hydrogenotrophic Methanoregula dominated methanogens (MPB) and Methylocystaceae dominated methanotrophs (MOB) in the sediment. Phosphorus inhibited the relative abundance of Methanoregula after incubation, resulting in a significant decrease. Real-time quantitative polymerase chain reaction indicated that the absolute abundance of MPB and MOB (i.e., the mcrA gene and the pmoA gene) in the sediments ranged from 5.1354E+06 to 6.3176E+07 copies·g-1 and 1.1656E+06 to 9.5056E+06 copies·g-1, respectively. The mcrA gene showed a preference for sediments with high organic carbon content. The effect of eutrophication on CH4 emissions is closely related to nutrient load and distinct niche of methane-functional bacteria.

Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach

Recent advances in remote sensing techniques provide a new horizon for monitoring the spatiotemporal variations of harmful algal blooms (HABs) using hyperspectral data in inland water. In this study, a hierarchical concatenated variational autoencoder (HCVAE) is proposed as an efficient and accurate deep learning (DL) based bio-optical model. To demonstrate its usefulness in retrieving algal pigments, the HCVAE is applied to bloom-prone regions in Daecheong Lake, South Korea. By abstracting the similarity between highly related features using layer-wise clique-based latent-feature extraction, HCVAE reduces the computational loads in deriving outputs while preventing performance degradation. Graph-based clique-detection uses information theory-based criteria to group the related reflectance spectra. Consequently, six latent features were extracted from 79 spectral bands to consist of a multilevel hierarchy of HCVAE that can simultaneously estimate concentrations of chlorophyll-a (Chl-a) and phycocyanin (PC). Despite the parsimonious model architecture, the Chl-a and PC concentrations estimated by HCVAE closely agree with the measured concentrations, with test R2 values of 0.76 and 0.82, respectively. In addition, spatial distribution maps of algal pigments obtained from HCVAE using drone-borne reflectance successfully capture the blooming spots. Based on its multilevel hierarchical architecture, HCVAE can provide the importance of latent features along with their individual wavelengths using Shapley additive explanations. The most important latent features covered the spectral regions associated with both Chl-a and PC. The lightweight neural network DNNsel, which uses only the spectral bands of highest importance in latent-feature extraction, performed comparably to HCVAE. The study results demonstrate the utility of the multilevel hierarchical architecture as a comprehensive assessment model for near-real-time drone-borne sensing of HABs. Moreover, HCVAE is applicable to a wide range of environmental big data, as it can handle numerous sets of features.

Damming exacerbates the discontinuities of phytoplankton in a subtropical river in China

Phytoplankton is sensitive to changes in river ecosystems. Increasing dams disrupt the continuity of river ecosystems. However, the spatial impacts of dams on phytoplankton have not been well documented. In this study, using multiple statistical analyses, the relationships between environmental drivers and phytoplankton community structures in natural background reaches, reservoirs, and corresponding post-dam reaches were explored in the Jiulong River with multiple cascaded dams, which encountered eutrophication and algal blooms in the past 15 years. Results illustrated that damming exacerbated longitudinal discontinuities of phytoplankton communities. The relative abundance of phytoplankton varied in three types of river sections. The average phytoplankton abundance in the reservoirs (1.62 × 105 cell·L-1) was higher than those in the natural background reaches (5.15 × 104 cell·L-1) and the corresponding downstream reaches (4.55 × 104 cell·L-1). The total β diversity ranged from 0.38 to 0.89 with an average of 0.64 and dominated by species replacement and least by species richness. The water environmental factors and hydraulic parameters rather than nutrients were more attributable to phytoplankton community variability in three river sections. These findings facilitate the management of rivers with multiple cascade dams by releasing environmental flows, jointly operating cascade hydropower stations, and developing nutrient reduction schemes to mitigate the negative impacts of damming in the river.

Current status and prognosis of Raphidiopsis raciborskii distribution in Bulgaria as part of the southeastern region of Europe

The cyanobacterial species Raphidiopsis raciborskii (Wołoszyńska) Aguilera et al. has a high invasiveness potential, which in less than a century leads to its cosmopolitan spread. In the temperate climate of Europe, R. raciborskii has been reported in many countries, but there is still a lack of detailed information about the current status of its distribution in lakes of Bulgaria, as a part of the southeastern range of its spread in Europe. We investigated the distribution of the species using data on the phytoplankton of 122 lakes surveyed during 13-years period (2009-2022). The species was found in 33 lakes (up to 324 m asl), and 14 new localities were registered during the studied period. The results reveal that the number of lakes with the presence of R. raciborskii (27 % of all research lakes) and its contribution to the total phytoplankton biomass, has increased significantly over the last decade. The species has successfully adapted and dominated the phytoplankton in 9 lakes, forming a bloom in 8 of them. The dominant position of R. raciborskii causes loss of species and functional diversity of phytoplankton and displaces the native bloom-forming cyanobacteria. Lakes with and without the species were compared based on the available data on bioclimatic and local environmental variables. Statistically significant differences were established with respect to water transparency, conductivity, maximum depth and maximum air temperature in the warmest month. Species distribution models (SDMs) were used to identify lakes in high risk of future invasion by R. raciborskii. The results of the SDMs implementation confirmed the high maximum air temperature and low water transparency to be important predictors of the occurrence of R. raciborskii in freshwater lakes in Bulgaria. In the areas with high summer temperatures the most suitable for R. raciborskii development were found to be shallow polymictic or medium deep lakes with small surface area and low water transparency. In areas with a suitable climate, the large, deep reservoirs with high transparency as well as macrophyte dominated lakes have a low probability of occurrence of R. raciborskii. Future colonization of lakes above 500 m asl (but most likely below 700 m asl) is also possible, especially in the conditions of global warming. SDMs account for climatic and biogeographic differences of lakes and could help in elucidating the underlying factors that control the occurrence and adaptation of R. raciborskii in a given area.

Eutrophication and loss of riparian shading influence food quality and trophic relation in stream food webs

Eutrophication induced by excessive inputs of nutrient is one of the main stressors in aquatic ecosystems. Deforestation in riparian zones alter riparian shading, which together with eutrophication is expected to exert a complex control over stream food webs. We manipulated two levels of riparian shading (open canopy vs. shading canopy) and nutrient supply (ambient vs. nutrient addition) in three headwater streams to investigate the individual and combined effects of eutrophication and loss of riparian shading on carbon sources and nutritional quality of biofilms, and the subsequent trophic effects on macroinvertebrate grazers. Nutrient enrichment increased the autochthonous carbon (i.e., algae especially diatoms) indicated by fatty acid (FA) biomarkers within biofilms and grazers. The nutritional quality indicated by eicosapentaenoic acid (EPA) content of biofilms was increased with nutrient enrichment and more so with the combined effect of an increase in riparian shading, consequently leading to an increase in the nutritional quality, density, and biomass of grazers. In particular, the trophic linkages between biofilms and grazers were mainly influenced by EPA concentration in the biofilms, and strengthened with the combined effects of riparian shading and additional nutrients. Our study emphasizes the nutritional significance of EPA for consumers at higher trophic levels and proposes its potential as an indicator for monitoring the health of aquatic ecosystems.

Phylogenetic analysis of Nostocales (Cyanobacteria) based on two novel molecular markers, implicated in the nitrogenase biosynthesis

The characterization of cyanobacteria communities remains challenging, as taxonomy of several cyanobacterial genera is still unresolved, especially within Nostocales taxa. Nostocales cyanobacteria are capable of nitrogen fixation; nitrogenase genes are grouped into operons and are located in the same genetic locus. Structural nitrogenase genes (nifH, nifK and nifD) as well as 16S rRNA have been shown to be adequate genetic markers for distinguishing cyanobacterial genera. However, there is no available information regarding the phylogeny of regulatory genes of the nitrogenase cluster. Aiming to provide a more accurate overview of the evolution of nitrogen fixation, this study analyzed for the first time nifE and nifN genes, which regulate the production of nitrogenase, alongside nifH. Specific primers were designed to amplify nifE and nifN genes, previously not available in literature and phylogenetic analysis was carried out in 13 and 14 TAU-MAC culture collection strains, respectively, of ten Nostocales genera along with other sequences retrieved from cyanobacteria genomes. Phylogenetic analysis showed that these genes seem to follow a common evolutionary pattern with nitrogenase structural genes and 16S rRNA. The classification of cyanobacteria based on these molecular markers seems to distinguish Nostocales strains with common morphological, ecological, and physiological characteristics.

A paleoecological investigation of recent cyanobacterial blooms and their drivers in two contrasting lakes

Cyanobacterial blooms are one of the most significant threats to global water security and freshwater biodiversity. Interactions among multiple stressors, including habitat degradation, species invasions, increased nutrient runoff, and climate change, are key drivers. However, assessing the role of anthropogenic activity on the onset of cyanobacterial blooms and exploring response variation amongst lakes of varying size and depth is usually limited by lack of historical records. In the present study we applied molecular, paleolimnological (trace metal, Itrax-µ-XRF and hyperspectral scanning, chronology), paleobotanical (pollen) and historical data to reconstruct cyanobacterial abundance and community composition and anthropogenic impacts in two dune lakes over a period of up to 1200 years. Metabarcoding and droplet digital PCR results showed very low levels of picocyanobacteria present in the lakes prior to about CE 1854 (1839-1870 CE) in the smaller shallow Lake Alice and CE 1970 (1963-1875 CE) in the larger deeper Lake Wiritoa. Hereafter bloom-forming cyanobacteria were detected and increased notably in abundance post CE 1984 (1982-1985 CE) in Lake Alice and CE 1997 (1990-2007 CE) in Lake Wiritoa. Currently, the magnitude of blooms is more pronounced in Lake Wiritoa, potentially attributable to hypoxia-induced release of phosphorus from sediment, introducing an additional source of nutrients. Generalized linear modelling was used to investigate the contribution of nutrients (proxy = bacterial functions), temperature, redox conditions (Mn:Fe), and erosion (Ti:Inc) in driving the abundance of cyanobacteria (ddPCR). In Lake Alice nutrients and erosion had a statistically significant effect, while in Lake Wiritoa nutrients and redox conditions were significant.

Remote estimation of phycocyanin concentration in inland waters based on optical classification

In recent years, under the dual pressure of climate change and human activities, the cyanobacteria blooms in inland waters have become a threat to global aquatic ecosystems and the environment. Phycocyanin (PC), a diagnostic pigment of cyanobacteria, plays an essential role in the detection and early warning of cyanobacterial blooms. In this context, accurate estimation of PC concentration in turbid waters by remote sensing is challenging due to optical complexity and weak optical signal. In this study, we collected a comprehensive dataset of 640 pairs of in situ measured pigment concentration and the Ocean and Land Color Instrument (OLCI) reflectance from 25 lakes and reservoirs in China during 2020-2022. We then developed a framework consisting of the water optical classification algorithm and three candidate algorithms: baseline height, band ratio, and three-band algorithm. The optical classification method used remote sensing reflectance (Rrs) baseline height in three bands: Rrs(560), Rrs(647) and Rrs(709) to classify the samples into five types, each with a specific spectral shape and water quality character. The improvement of PC estimation accuracy for optically classified waters was shown by comparison with unclassified waters with RMSE = 72.6 μg L-1, MAPE = 80.4 %, especially for the samples with low PC concentration. The results show that the band ratio algorithm has a strong universality, which is suitable for medium turbid and clean water. In addition, the three-band algorithm is only suitable for medium turbid water, and the line height algorithm is only suitable for high PC content water. Furthermore, the five distinguished types with significant differences in the value of the PC/Chla ratio well indicated the risk rank assessment of cyanobacteria. In conclusion, the proposed framework in this paper solved the problem of PC estimation accuracy problem in optically complex waters and provided a new strategy for water quality inversion in inland waters.

Cascading climate effects in deep reservoirs: Full assessment of physical and biogeochemical dynamics under ensemble climate projections and ways towards adaptation

We coupled twenty-first century climate projections with a well-established water quality model to depict future ecological changes of Rappbode Reservoir, Germany. Our results document a chain of climate-driven effects propagating through the aquatic ecosystem and interfering with drinking water supply: intense climate warming (RCP8.5 scenario) will firstly trigger a strong increase in water temperatures, in turn leading to metalimnetic hypoxia, accelerating sediment nutrient release and finally boosting blooms of the cyanobacterium Planktothrix rubescens. Such adverse water quality developments will be suppressed under RCP2.6 and 6.0 indicating that mitigation of climate change is improving water security. Our results also suggested surface withdrawal can be an effective adaptation strategy to make the reservoir ecosystem more resilient to climate warming. The identified consequences from climate warming and adaptation strategies are relevant to many deep waters in the temperate zone, and the conclusion should provide important guidances for stakeholders to confront potential climate changes.

Spatiotemporal dynamics of phytoplankton biomass and community succession for driving factors in a meso-eutrophic lake

Effects of climate change and nutrient load caused by human activities on lake phytoplankton blooms have attracted much attention globally. However, their roles and synergistic effects on phytoplankton biomass and community historical succession are not well understood, especially for meso-eutrophic plateau lakes. In this study, a multi-year (1997-2022) monthly dataset including hydro-chemical and meteorological indicators of the meso-eutrophic plateau lake Erhai in China, was used to explore the contributions of climate change and nutrients on phytoplankton biomass variation and community succession. Phytoplankton biomass increased from 1997 to 2006, slowly decreased from 2006 to 2015, then increased again from 2015 to 2022, according to a generalised additive model (GAM). Alongside warming, nitrogen, phosphorus and organic matter are key drivers of long-term interannual variation in phytoplankton biomass and historical succession of the phytoplankton community. The extensive blooms in recent years were strongly associated with both organic matter accumulation and global warming. Phytoplankton biomass in northern and southern districts was greater than in central areas, with Cyanophyta and Pyrrophyta dominating in the north and Chlorophyta prevalent in the south. Since 2015, phytoplankton diversity has increased significantly, and biomass has declined in the southern district but increased markedly in the northern district. Spatial heterogeneity was caused by the spatial distribution of nutrients and the buoyancy regulation capacity of cyanobacteria. The results demonstrate that bloom mitigation responds strongly to nitrogen and phosphorus control in meso-eutrophic lakes, therefore preventing and controlling blooms through nitrogen and phosphorus reduction is still an effective measure. Given the accumulation of organic matter in recent years, synergistic control of organic matter and total nitrogen and phosphorus could effectively reduce the risk of cyanobacterial and dinoflagellate blooms.

Present and future potential role of toxin-producing Synechococcus in the tropical region

As anthropogenic induced temperature rises and nutrient loadings increase in fresh and brackish environments, the ecological function of the phytoplankton community is expected to favour the picocyanobacteria, of the genus Synechococcus. Synechococcus is already a ubiquitous cyanobacterium found in both freshwater and marine environments, notwithstanding that the toxigenic species still remains unexplored in many freshwaters. Their fast growth rate and their ability to produce toxins make Synechococcus a potential dominant player in harmful algal blooms under climate change scenarios. This study examines the responses of a novel toxin-producing Synechococcus (i.e., one belonging to a freshwater clade; the other belonging to a brackish clade) to environmental changes that reflect climate change effects. We conducted a series of controlled experiments under present and predicted future temperatures, as well as under various N and P nutrients loadings. Our findings highlight how Synechococcus can be altered by the differing reactions to increasing temperature and nutrients, which resulted in considerable variations in cell abundance, growth rate, death rate, cellular stoichiometry and toxin production. Synechococcus had the highest growth observed at 28 °C, and further increases in temperature resulted in a decline for both fresh and brackish waters. Cellular stoichiometry was also altered, where more nitrogen (N) per cell was required, and the plasticity of N:P was more severe for the brackish clade. However, Synechococcus become more toxic under future scenario. Anatoxin-a (ATX) saw the greatest spike when temperature was at 34 °C especially under P-enrichment conditions. In contrast, Cylindrospermopsin (CYN) was promoted at the lowest tested temperature (25 °C) and under N-limitation. Overall, both temperature and external nutrients are the dominant control over Synechococcus toxins production. A model was also created to assess Synechococcus toxicity to zooplankton grazing. Zooplankton grazing was reduced by two folds under nutrient limitation, but temperature accounted for very insignificant change.

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.

Climate change amplifies the risk of potentially toxigenic cyanobacteria

Cyanobacterial blooms pose a significant threat to water security, with anthropogenic forcing being implicated as a key driver behind the recent upsurge and global expansion of cyanobacteria in modern times. The potential effects of land-use alterations and climate change can lead to complicated, less-predictable scenarios in cyanobacterial management, especially when forecasting cyanobacterial toxin risks. There is a growing need for further investigations into the specific stressors that stimulate cyanobacterial toxins, as well as resolving the uncertainty surrounding the historical or contemporary nature of cyanobacterial-associated risks. To address this gap, we employed a paleolimnological approach to reconstruct cyanobacterial abundance and microcystin-producing potential in temperate lakes situated along a human impact gradient. We identified breakpoints (i.e., points of abrupt change) in these time series and examined the impact of landscape and climatic properties on their occurrence. Our findings indicate that lakes subject to greater human influence exhibited an earlier onset of cyanobacterial biomass by 40 years compared to less-impacted lakes, with land-use change emerging as the dominant predictor. Moreover, microcystin-producing potential increased in both high- and low-impact lakes around the 1980s, with climate warming being the primary driver. Our findings chronicle the importance of climate change in increasing the risk of toxigenic cyanobacteria in freshwater resources.

Chemodiversity of Cyanobacterial Toxins Driven by Future Scenarios of Climate Warming and Eutrophication

Climate change and eutrophication are two environmental threats that can alter the structure of freshwater ecosystems and their service functions, but we know little about how ecosystem structure and function will evolve in future scenarios of climate warming. Therefore, we created different experimental climate scenarios, including present-day conditions, a 3.0 °C increase in mean temperature, and a "heatwaves" scenario (i.e., an increase in temperature variability) to assess the effects of climate change on phytoplankton communities under simultaneous stress from eutrophication and herbicides. We show that the effects of climate warming, particularly heatwaves, are associated with elevated cyanobacterial abundances and toxin production, driven by a change from mainly nontoxic to toxic Microcystis spp. The reason for higher cyanobacterial toxin concentrations is likely an increase in abundances because under the dual pressures of climate warming and eutrophication individual Microcystis toxin-producing ability decreased. Eutrophication and higher temperatures significantly increased the biomass of Microcystis, leading to an increase in the cyanobacterial toxin concentrations. In contrast, warming alone did not produce higher cyanobacterial abundances or cyanobacterial toxin concentrations likely due to the depletion of the available nutrient pool. Similarly, the herbicide glyphosate alone did not affect abundances of any phytoplankton taxa. In the case of nutrient enrichment, cyanobacterial toxin concentrations were much higher than under warming alone due to a strong boost in biomass of potential cyanobacterial toxin producers. From a broader perspective our study shows that in a future warmer climate, nutrient loading has to be reduced if toxic cyanobacterial dominance is to be controlled.

Global warming induces the succession of photosynthetic microbial communities in a glacial lake on the Tibetan Plateau

As an important freshwater resource in the Qinghai-Tibet Plateau, glacial lakes are being immensely affected by global warming. Due to the lack of long-term monitoring data, the processes and driving mechanisms of the water ecology of these glacial lakes in a rapidly changing climate are poorly understood. This study, for the first time, reconstructed changes in water temperature and photosynthetic microbial communities over the past 200 years in Lake Basomtso, a glacial lake on the southeastern Tibetan Plateau. Temperatures were reconstructed using a paleotemperature proxy based on branched glycerol dialkyl glycerol tetraethers (brGDGTs), the cell membrane lipids of some bacteria, and photosynthetic microbial communities were determined by high-throughput DNA sequencing. The reconstructed mean annual air temperature (MAAT) at Lake Basomtso varied between 6.9 and 8.3 °C over the past 200 years, with a rapid warming rate of 0.25 °C /10 yrs after 1950s. Carbon isotope of sediment and n-alkane analyses indicate that ≥95% of the organic matter in Lake Basomtso is derived from a mixture of terrestrial C3 plants and endogenous organic matter inputs, and the proportion of endogenous organic matter in the sediments has gradually increased since the 1960s. The sedimentary DNA analyses of the sediment core reveal that Chloracea is the most dominant prokaryotic photosynthetic microbial group (84.5%) over the past 200 years. However, the relative abundance of Cyanobacteria has increased from ≤6.8% before the 1960s to 15.5% nowadays, suggesting that warmer temperatures favor the growth of Cyanobacteria in glacial lakes. Among eukaryotic photosynthetic microorganisms, the Chlorophyceae have been gradually replaced by Dinoflagellata and Diatomacae since the 1980s, although the Chlorophyceae still had the highest average relative abundance overall (30-40%). The Pb isotopic composition, together with the total phosphorous concentration, implies that human activity exerted a minimal impact on Lake Basomtso over the past 200 yrs. However, the synchronous fluctuations of total organic carbon (TOC), total nitrogen (TN), and metal elements in sediments suggest that temperature appears to have a strong influence on nutrient input to Lake Basomtso by controlling glacial erosion. Global warming and the concurrent increase in glacial meltwater are two main factors driving changes in nutrient inputs from terrestrial sources which, in turn, increases the lake productivity, and changes microbial community composition. Our findings demonstrate the sensitive response of glacial lake ecology to global warming. It is necessary to strengthen the monitoring and research of glacial lake ecology on the Tibetan plateau, so as to more scientifically and accurately understand the response process and mechanism of the glacial lake ecosystem under global warming.

Occurrence, Distribution and Toxins of Benthic Cyanobacteria in German Lakes

Cyanobacteria are favored by climate change and global warming; however, to date, most research and monitoring programs have focused on planktic cyanobacteria. Benthic cyanobacteria blooms also increase and pose a risk to animal and human health; however, there is limited knowledge of their occurrence, distribution and the toxins involved, especially in relation to their planktic conspecifics. Therefore, we analyzed the benthic and planktic life forms of cyanobacterial communities in 34 lakes in Germany, including a monitoring of cyanotoxins. Community analyses were based on microscopic examination and Illumina sequencing of the 16S rRNA gene. The analyses of cyanotoxins were carried out using LC-MS/MS and ELISA. Observed benthic mats containing cyanobacteria consisted mainly of Nostocales and Oscillatoriales, being present in 35% of the lakes. Anatoxin was the most abundant cyanotoxin in the benthic samples, reaching maximum concentrations of 45,000 µg/L, whereas microcystin was the predominate cyanotoxin in the open-water samples, reaching concentrations of up to 18,000 µg/L. Based on the results, specific lakes at risk of toxic cyanobacteria could be identified. Our findings suggest that monitoring of benthic cyanobacteria and their toxins should receive greater attention, ideally complementing existing open-water sampling programs with little additional effort.

Predicting water quality variability in a Mediterranean hypereutrophic monomictic reservoir using Sentinel 2 MSI: the importance of considering model functional form

Anthropogenic eutrophication is a global environmental problem threatening the ecological functions of many inland freshwaters and diminishing their abilities to meet their designated uses. Water authorities worldwide are being pressed to improve their abilities to monitor, predict, and manage the incidence of harmful algal blooms (HABs). While most water quality management decisions are still based on conventional monitoring programs that lack the needed spatio-temporal resolution for effective lake/reservoir management, recent advances in remote sensing are providing new opportunities towards better understanding water quality variability in these important freshwater systems. This study assessed the potential of using the Sentinel 2 Multispectral Instrument to predict and assess the spatio-temporal variability in the water quality of the Qaraoun Reservoir, a poorly monitored Mediterranean hypereutrophic monomictic reservoir that is subject to extensive periods of HABs. The work first evaluated the ability to transfer and recalibrate previously developed reservoir-specific Landsat 7 and 8 water quality models when used with Sentinel 2 data. The results showed poor transferability between Landsat and Sentinel 2, with most models experiencing a significant drop in their predictive skill even after recalibration. Sentinel 2 models were then developed for the reservoir based on 153 water quality samples collected over 2 years. The models explored different functional forms, including multiple linear regressions (MLR), multivariate adaptive regression splines (MARS), random forests (RF), and support vector regressions (SVR). The results showed that the RF models outperformed their MLR, MARS, and SVR counterparts with regard to predicting chlorophyll-a, total suspended solids, Secchi disk depth, and phycocyanin. The coefficient of determination (R2) for the RF models varied between 85% for TSS up to 95% for SDD. Moreover, the study explored the potential of quantifying cyanotoxin concentrations indirectly from the Sentinel 2 MSI imagery by benefiting from the strong relationship between cyanotoxin levels and chlorophyll-a concentrations.

Algal biomass mapping of eutrophic lakes using a machine learning approach with MODIS images

Algal blooms are a widespread issue in eutrophic lakes. Compared with the satellite-derived surface algal bloom area and chlorophyll-a (Chla) concentration, algae biomass is a more stable way to reflect water quality. Although satellite data have been adopted to observe the water column integrated algal biomass, the previous methods mostly are empirical algorithms, which are not stable enough for widespread use. This paper proposed a machine learning algorithm based on Moderate Resolution Imaging Spectrometer (MODIS) data to estimate the algal biomass, which was successfully applied to a eutrophic lake in China, Lake Taihu. This algorithm was developed by linking Rayleigh-corrected reflectance to in situ algae biomass data in Lake Taihu (n = 140), and the different mainstream machine learning (ML) methods were compared and validated. The partial least squares regression (PLSR) (R² = 0.67, mean absolute percentage error (MAPE) = 38.88 %) and support vector machines (SVM) (R² = 0.46, MAPE = 52.02 %) performed poor satisfactory. In contrast, random forest (RF) and extremely gradient boosting tree (XGBoost) algorithms had higher accuracy (RF: R² = 0.85, MAPE = 22.68 %; XGBoost: R² = 0.83, MAPE = 24.06 %), demonstrating greater application potential in algal biomass estimation. Field biomass data were further used to estimate the RF algorithm, which showed acceptable precision (R² = 0.86, MAPE < 7 mg Chla). Subsequently, sensitivity analysis showed that the RF algorithm was not sensitive to high suspension and thickness of aerosols (rate of change <2 %), and inter-day and consecutive days verification showed stability (rate of change <5 %). The algorithm was also extended to Lake Chaohu (R² = 0.93, MAPE = 18.42 %), demonstrating its potential in other eutrophic lakes. This study for algae biomass estimation provides technical means with higher accuracy and greater universality for the management of eutrophic lakes.

Effects of water movement and temperature on Rhizophydium infection of Planktothrix in a shallow hypereutrophic lake

Grand Lake St. Marys (GLSM) is a popular recreational lake located in western Ohio, United States, generating nearly $150 million in annual revenue. However, recurring algal blooms dominated by Planktothrix agardhii, which can produce harmful microcystin toxins, have raised concerns about water safety and negatively impacted the local economy. Planktothrix agardhii is host to a number of parasites and pathogens, including an obligate fungal parasite in the Chytridiomycota (chytrids). In this study, we investigated the potential of these chytrid (Rhizophydium sp.) to infect P. agardhii blooms in the environment by modifying certain environmental conditions thought to limit infection prevalence in the wild. With a focus on temperature and water mixing, mesocosms were designed to either increase or decrease water flow compared to the control (water outside the mesocosm). In the control and water circulation mesocosms, infections were found infrequently and were found on less than 0.75% of the Planktothrix population. On the other hand, by decreasing the water flow to stagnation, chytrid infections were more frequent (found in nearly 3x as many samples) and more prevalent, reaching a maximum infection rate of 4.12%. In addition, qPCR coupled with 16S-18S sequencing was utilized to confirm the genetic presence of both host and parasite, as well as to better understand the effect of water circulation on the community composition. Statistical analysis of the data confirmed that chytrid infection was dependent on water temperature, with infections predominantly occurring between 19°C and 23°C. Additionally, water turbulence can significantly reduce the infectivity of chytrids, as infections were mostly found in stagnant mesocosms. Further, decreasing the water circulation promoted the growth of the cyanobacterial population, while increasing water agitation promoted the growth of green algae (Chlorophyta). This study starts to explore the environmental factors that affect chytrid pathogenesis which can provide valuable insights into controlling measures to reduce the prevalence of harmful algal blooms and improve water quality in GLSM and similarly affected waterbodies.

Application of floating wetlands for the improvement of degraded urban waters: Findings from three multi-year pilot-scale installations

Floating Treatment Wetlands (FTWs) are an emerging ecological engineering technology being applied the restoration of eutrophic urban water bodies. Documented water-quality benefits of FTW include nutrient removal, transformation of pollutants, and reduction in bacterial contamination. However, translating findings from short-duration lab and mesocosm scale experiments, into sizing criteria that might be applied to field installations is not straightforward. This study presents the results of three well established (>3 years) pilot-scale (40-280 m²) FTW installations in Baltimore, Boston, and Chicago. We quantify annual phosphorus removal through harvesting of above-ground vegetation and find an average removal rate of 2 g-P m^-2_. In our own study and in a review of literature, we find limited evidence of enhanced sedimentation as a pathway for phosphorus removal. In addition to water-quality benefits, FTW planted with native species, provide valuable wetland habitat; and theoretically improve ecological function. We document efforts to quantify the local effect of FTW installations on benthic and sessile macroinvertebrates, zooplankton, bloom-forming cyanobacteria, and fish. Data from these three projects suggest that, even on a small scale, FTW produce localized changes in biotic structure that reflect improving environmental quality. This study provides a simple and defensible method for sizing FTW for nutrient removal in eutrophic waterbodies. We propose several key research pathways which would advance our understanding of the effects FTW have on the ecosystem they are deployed in.

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.

Characterization of lacustrine harmful algal blooms using multiple biomarkers: Historical processes, driving synergy, and ecological shifts

Harmful algal blooms (HABs) producing toxic metabolites are increasingly threatening environmental and human health worldwide. Unfortunately, long-term process and mechanism triggering HABs remain largely unclear due to the scarcity of temporal monitoring. Retrospective analysis of sedimentary biomarkers using up-to-date chromatography and mass spectrometry techniques provide a potential means to reconstruct the past occurrence of HABs. By combining aliphatic hydrocarbons, photosynthetic pigments, and cyanotoxins, we quantified herein century-long changes in abundance, composition, and variability of phototrophs, particularly toxigenic algal blooms, in China's third largest freshwater Lake Taihu. Our multi-proxy limnological reconstruction revealed an abrupt ecological shift in the 1980s characterized by elevated primary production, Microcystis-dominated cyanobacterial blooms, and exponential microcystin production, in response to nutrient enrichment, climate change, and trophic cascades. The empirical results from ordination analysis and generalized additive models support climate warming and eutrophication synergy through nutrient recycling and their feedback through buoyant cyanobacterial proliferation, which sustain bloom-forming potential and further promote the occurrence of increasingly-toxic cyanotoxins (e.g., microcystin-LR) in Lake Taihu. Moreover, temporal variability of the lake ecosystem quantified using variance and rate of change metrics rose continuously after state change, indicating increased ecological vulnerability and declined resilience following blooms and warming. With the persistent legacy effects of lake eutrophication, nutrient reduction efforts mitigating toxic HABs probably be overwhelmed by climate change effects, emphasizing the need for more aggressive and integrated environmental strategies.

Comparative assessment of algaecide performance on freshwater phytoplankton: Understanding differential sensitivities to frame cyanobacteria management

Cyanobacterial bloom represent a growing threat to global water security. With fast proliferation, they raise great concern due to potential health and socioeconomic concerns. Algaecides are commonly employed as a mitigative measure to suppress and manage cyanobacteria. However, recent research on algaecides has a limited phycological focus, concentrated predominately on cyanobacteria and chlorophytes. Without considering phycological diversity, generalizations crafted from these algaecide comparisons present a biased perpective. To limit the collateral impacts of algaecide interventions on phytoplankton communities it is critical to understand differential phycological sensitivities for establishing optimal dosage and tolerance thresholds. This research attempts to fill this knowledge gap and provide effective guidelines to frame cyanobacterial management. We investigate the effect of two common algaecides, copper sulfate (CuSO₄) and hydrogen peroxide (H₂O₂), on four major phycological divisions (chlorophytes, cyanobacteria, diatoms, and mixotrophs). All phycological divisions exhibited greater sensitivity to copper sulfate, except chlorophytes. Mixotrophs and cyanobacteria displayed the highest sensitivity to both algaecides with the highest to lowest sensitivity being observed as follows: mixotrophs, cyanobacteria, diatoms, and chlorophytes. Our results suggest that H₂O₂ represents a comparable alternative to CuSO₄ for cyanobacterial control. However, some eukaryotic divisions such as mixotrophs and diatoms mirrored cyanobacteria sensitivity, challenging the assumption that H₂O₂ is a selective cyanocide. Our findings suggest that optimizing algaecide treatments to suppress cyanobacteria while minimizing potential adverse effects on other phycological members is unattainable. An apparent trade-off between effective cyanobacterial management and conserving non-targeted phycological divisions is expected and should be a prime consideration of lake management.

Combined effects of microplastics and warming enhance algal carbon and nitrogen storage

Algae dominate primary production in groundwater and oceans and play a critical role in global carbon dioxide fixation and climate change but are threatened by ongoing global warming events (such as heatwaves) and increasing microplastic (MP) pollution. However, whether and how ecologically important phytoplankton respond to the combined effects of warming and MPs remain poorly understood. We thus investigated the combined effects of these factors on carbon and nitrogen storage and the mechanisms underlying the alterations in the physiological performance of a model diatom, Phaeodactylum tricornutum, exposed to a warming stressor (25 °C compared with 21 °C) and polystyrene MP acclimation. Although warmer conditions decreased the cell viability, the diatoms subjected to the synergistic effects of MPs and warming showed significant increases in the growth rate (1.10-fold) and nitrogen uptake rate (1.26-fold). Metabolomics and transcriptomic analyses revealed that MPs and warming mainly promoted fatty acid metabolism, the urea cycle, glutamine and glutamate production, and the tricarboxylic acid (TCA) cycle due to an increased level of 2-oxoglutarate, which is the hub of carbon and nitrogen metabolism and accounts for the acquisition and utilization of carbon and nitrogen. Our findings emphasize the nonnegligible effects of MPs and HWs on the algal carbon and nitrogen cycles in waters.

The pace of shifting seasons in lakes

Lake ecosystems are vulnerable to seasonal thermal cues, with subtle alterations in the timing of seasonal temperatures having a dramatic influence on aquatic species. Here, a measure of seasonal change in temperature is used to describe the pace of shifting seasons in lakes. Since 1980 spring and summer temperatures in Northern Hemisphere lakes have arrived earlier (2.0- and 4.3-days decade^-1, respectively), whilst the arrival of autumn has been delayed (1.5-days decade^-1) and the summer season lengthened (5.6-days decade^-1). This century, under a high-greenhouse-gas-emission scenario, current spring and summer temperatures will arrive even earlier (3.3- and 8.3-days decade^-1, respectively), autumn temperatures will arrive later (3.1-days decade^-1), and the summer season will lengthen further (12.1-days decade^-1). These seasonal alterations will be much slower under a low-greenhouse-gas-emission scenario. Changes in seasonal temperatures will benefit some species, by prolonging the growing season, but negatively impact others, by leading to phenological mismatches in critical activities.

Laboratory growth capacity of an invasive cyanobacterium (Microcystis aeruginosa) on organic substrates from surface waters of permafrost peatlands

Within a global warming trend, invasive cyanobacteria, abundant in tropical and temperate regions, can migrate northward and colonize thermokarst lakes in permafrost-affected territories. For a better understanding of the cyanobacterial proliferation mechanism in those lakes, we performed laboratory growth of typical invasive cyanobacteria, Microcystis aeruginosa, onto various organic-rich solutions representative of permafrost peatlands. Aqueous leachates of lichen, moss and peat were the most favorable substrates for massive growth. The growth in the presence of all organic substrates produced an increase in solution pH by two units and a sizable (30-50%) decrease in the concentration of dissolved organic carbon. The observed increase in the dissolved organic carbon aromaticity degree likely reflected preferential cyanobacterial uptake of aliphatic, optically transparent organic substances. Cyanobacterial growth over a bloom period can create a carbon sink (uptake of 2.5 and 8.3 g C-CO₂ m^-2 d^-1) that can offset the net heterotrophic status of thermokarst lakes in permafrost peatlands, thus switching the lake status from a C source to a C sink. Therefore, predictions of future carbon exchanges with the atmosphere in surface waters of permafrost peatlands require explicit accounting for the possibility of invasive cyanobacterial growth.

Reducing the water residence time is inadequate to limit the algal proliferation in eutrophic lakes

The eutrophication problem now threatens many lakes and reservoirs. To avoid the occurrence of algal blooms, some cities try to increase the flow rate or directly choose lakes or reservoirs with a short water residence time (WRT) as drinking water sources. However, up to now, whether such a strategy can achieve its goal is still unclear. In this study, a newly restored lake with a WRT of approximately 3 days was chosen to investigate algal growth potential as well as its responses to external nitrogen (N) and phosphorus (P) inputs. The results suggested that although the water quality of the lake could generally meet the environmental quality standards for surface water, dissolved inorganic nitrogen reached a high level with an average value of 1.58 mg/L. Meanwhile, a considerable increase in Chl-a concentration was observed across the flow direction. Especially, in July, Chl-a concentration at the site near the outlet was 8.1 times higher than that at the inlet, and cyanobacteria became the dominant species accounting for 83% of the total cell density. Nutrient enrichment experiments showed that algae could grow rapidly within 3 days with average specific growth rates (μ) of 0.36-0.42 d^-1. The addition of N and P furtherly promoted the algal growth, and μ values of the treatments with P addition were the highest at 0.67-0.83 d^-1. These results indicated that even if the WRT was reduced to 3 days, the risk of the occurrence of algal blooms still exists, and this undesirable trend would be enhanced by the short-term external nutrient input. Our findings indicated that the hydrodynamic control measures may not be entirely successful in protecting the drinking water source from algal blooms, especially when its influent has already been under eutrophication.

Synergistic Effects of Warming and Internal Nutrient Loading Interfere with the Long-Term Stability of Lake Restoration and Induce Sudden Re-eutrophication

Phosphorus (P) precipitation is among the most effective treatments to mitigate lake eutrophication. However, after a period of high effectiveness, studies have shown possible re-eutrophication and the return of harmful algal blooms. While such abrupt ecological changes were attributed to the internal P loading, the role of lake warming and its potential synergistic effects with internal loading, thus far, has been understudied. Here, in a eutrophic lake in central Germany, we quantified the driving mechanisms of the abrupt re-eutrophication and cyanobacterial blooms in 2016 (30 years after the first P precipitation). A process-based lake ecosystem model (GOTM-WET) was established using a high-frequency monitoring data set covering contrasting trophic states. Model analyses suggested that the internal P release accounted for 68% of the cyanobacterial biomass proliferation, while lake warming contributed to 32%, including direct effects via promoting growth (18%) and synergistic effects via intensifying internal P loading (14%). The model further showed that the synergy was attributed to prolonged lake hypolimnion warming and oxygen depletion. Our study unravels the substantial role of lake warming in promoting cyanobacterial blooms in re-eutrophicated lakes. The warming effects on cyanobacteria via promoting internal loading need more attention in lake management, particularly for urban lakes.