Cyanobacterial Blooms In Lakes Research Articles

Cycles of solar ultraviolet radiation favor periodic expansions of cyanobacterial blooms in global lakes

Global warming and eutrophication are known to increase the prevalence of cyanobacterial blooms, posing a severe threat to the ecological stability and sustainability of water bodies. The long-term (over an annual time frame) effect of UV radiation on cyanobacterial blooms in lakes are rarely discussed though the substantial effects of high-intensity UV radiation on the growth inhibition of marine phytoplankton were studied. Here, we employed the datasets on surface solar UV radiation, nitrogen and phosphorus concentrations, and the annual scales and frequencies of cyanobacterial blooms in lakes across long-term spatial scales to probe the relationship of UV radiation with cyanobacterial blooms. The results indicated that enhanced solar UV radiation may unintentionally stimulate cyanobacterial growth and favor the expansions of cyanobacterial blooms in lakes around the world. The fluctuating UV radiation significantly affects the annual scales of cyanobacterial blooms in both eutrophic and oligotrophic lakes. Solar UV radiation enhances the positive impact of rising phosphorus levels on cyanobacterial blooms because UV radiation prompts the synthesis of polyphosphate in cyanobacteria cells, which helps cyanobacteria to alleviate the stress of UV light. The scales of cyanobacterial blooms are significantly impacted by solar UV radiation intensities as opposed to the annual frequency of cyanobacterial blooms. Furthermore, solar UV radiation fluctuation with a 9-year period over a 14-year main cycles significantly affects the periodicities of cyanobacterial blooms in global lakes, which provides a basis for predicting the peak value of the scales of cyanobacterial blooms in lakes. These findings opened up new avenues of inquiry into the mechanism and management strategies of cyanobacterial blooms in lakes worldwide.

Harmful blooms across a longitudinal gradient in central Europe during heatwave: Cyanobacteria biomass, cyanotoxins, and nutrients

Climate change has increased the frequency, duration and intensity of heatwaves in Europe. These extreme events result in alterations of physical, chemical, and biological properties of lakes that may synergistically promote cyanobacterial dominance. In our study we focused on cyanobacterial blooms in lakes distributed over a longitudinal gradient in Central Europe during one of the “top ten European heat waves” in summer 2015. 92 lakes were included in the study, located across three climatic subregions: cool northern lakes, situated in Lithuania, temperate northern lakes in Poland, and warm northern lakes in Croatia. The objective of the study was to determine if cyanobacterial biomass, predominant species, and cyanotoxin concentration differed, across the south-north gradient, as a function of water temperature, total phosphorus, and total nitrogen. Statistical significance of observed patterns was tested using the Kruskal-Wallis rank sum test and the generalized linear model. We found the lowest average epilimnion temperature, but the highest average cyanobacterial biomass in the northern, ‘cool’ lakes while the highest average temperature with the lowest average cyanobacterial biomass in the southern, ‘warm’ lakes. The concentration of cyanotoxins was also the highest in the ‘cool’ lakes. Total phosphorus and total nitrogen correlated significantly with cyanobacterial biomass, cyanotoxins concentration and biomass of some cyanobacterial species (mainly Planktothrix agardhii), regardless of the latitude. Only in the ‘cool’ lakes concentration of cyanotoxins (microcystins and anatoxin-a) correlated significantly with cyanobacterial biomass and the biomass of some dominant cyanobacterial species (P. agardhii). Our results emphasized the differences of heat weaves impact on lakes of various latitudes, with the strongest increase in toxic cyanobacterial blooms in northern ‘cool’ lakes, situated in high latitudes. On the other hand, nutrients directly enhanced blooms across all the studied latitudes of Central Europe. The cyanobacteria species dominating in blooms might be recognized as ecological indicators of climate change, especially in the north-eastern part of Europe.

Predicting Imminent Cyanobacterial Blooms in Lakes Using Incomplete Timely Data

AbstractToxic cyanobacterial blooms (CBs) are becoming more frequent globally, posing a threat to freshwater ecosystems. While making long‐range forecasts is overly challenging, predicting imminent CBs is possible from precise monitoring data of the underlying covariates. It is, however, infeasibly costly to conduct precise monitoring on a large scale, leaving most lakes unmonitored or only partially monitored. The challenge is hence to build a predictive model that can use the incomplete, partially‐monitored data to make near‐future CB predictions. By using 30 years of monitoring data for 78 water bodies in Alberta, Canada, combined with data of watershed characteristics (including natural land cover and anthropogenic land use) and meteorological conditions, we train a Bayesian network that predicts future 2‐week CB with an area under the curve (AUC) of 0.83. The only monitoring data that the model needs to reach this level of accuracy are whether the cell count and Secchi depth are low, medium, or high, which can be estimated by advanced high‐resolution imaging technology or trained local citizens. The model is robust against missing values as in the absence of any single covariate, it performs with an AUC of at least 0.78. While taking a major step toward reduced‐cost, less data‐intensive CB forecasting, our results identify those key covariates that are worth the monitoring investment for highly accurate predictions.

Adopt a Lake: Successfully Tracking Harmful Cyanobacterial Blooms in Canadian Surface Waters Through Citizen Science

The proliferation of harmful waterborne cyanobacterial algal blooms, some of which can produce potent toxins, poses severe risks to environmental and human health. Academic and governmental monitoring efforts may be constrained by budget, time, and staff, and thus miss otherwise significant pollution events. Here, we report on the implementation of a citizen science project to track harmful cyanobacterial blooms in lakes and waterways across Canada. Through both crowdsourcing and crowdfunding, the Adopt a Lake (Adopt a Lake 2022) campaign aimed to document the potential presence of cyanobacteria and toxins with the assistance of participants, thus improving public awareness of the issue of water quality preservation. Using social media, participants were encouraged to participate in the initiative by collecting samples during a bloom from a nearby pond or by making a financial contribution to support the initiative. Adopt a Lake benefitted from the analytical platform of Algal Blooms Treatment, Risk Assessment, Predictions, and Prevention (ATRAPP), a research project focused on the prediction and management of harmful cyanobacterial blooms. The presence of cyanotoxins, which can confirm whether a lake has a toxic bloom, was determined through high-resolution mass spectrometry analyses. This paper presents an overview of the implementation of the Adopt a Lake initiative, the campaign’s status, and the lessons learned, and it argues the importance of continual monitoring of cyanobacterial blooms.

Assessment of cyanotoxins in water and fish in an African freshwater lagoon (Lagoon Aghien, Ivory Coast) and the application of WHO guidelines.

In comparison with northern countries, limited data are available on the occurrence and potential toxicity of cyanobacterial blooms in lakes and ponds in sub-Saharan countries. With the aim of enhancing our knowledge on cyanobacteria and their toxins in Africa, we performed a 17-month monitoring of a freshwater ecosystem, Lagoon Aghien (Ivory Coast), which is used for multiple practices by riverine populations and for drinking water production in Abidjan city. The richness and diversity of the cyanobacterial community were high and displayed few variations during the entire survey. The monthly average abundances ranged from 4.1 × 104 to 1.8 × 105 cell mL-1, with higher abundances recorded during the dry seasons. Among the five cyanotoxin families analyzed (anatoxin-a, cylindrospermopsin, homoanatoxin, microcystins, saxitoxin), only microcystins (MC) were detected with concentrations ranging from 0 to 0.364 μg L-1 in phytoplankton cells, from 32 to 1092 μg fresh weight (FW) kg-1 in fish intestines, and from 33 to 383 μg FW kg-1 in fish livers. Even if the MC concentrations in water and fish are low, usually below the thresholds defined in WHO guidelines, these data raise the issue of the relevance of these WHO guidelines for sub-Saharan Africa, where local populations are exposed throughout the year to these toxins in multiple ways.

Characterizing carotenoids in cyanobacterial cultures – Opportunities and implications for paleolimnological studies

Cyanobacterial blooms are increasing in frequency and intensity globally, impacting lake ecosystem health and posing a risk to human and animal health due to the toxins they can produce. Cyanobacterial pigments preserved in lake sediments provide a useful means of understanding the changes that have led to cyanobacterial blooms in lakes. However, there is some uncertainty as to whether specific carotenoids are unique to certain genera or types of cyanobacteria. To fill this knowledge gap, we analyzed pigments in 34 cyanobacteria cultures and applied the findings to sediments from three New Zealand lakes. The cyanobacterial carotenoids canthaxanthin, echinenone and zeaxanthin were detected in all cultures, whereas myxoxanthophyll was only detected in ten cultures (Microcoleus, Planktothrix and the picocyanobacteria cultures; Synechococcaceae). The sum of the individual carotenoid concentrations provided the strongest relationship with cyanobacterial biomass (R2 = 0.58) and could be used in paleolimnology studies to evaluate general cyanobacterial abundance. Ratios of canthaxanthin, zeaxanthin and myxoxanthophyll relative to echinenone indicated that carotenoid ratios could be used to differentiate picocyanobacteria and bloom-forming cyanobacteria, to some degree. High zeaxanthin/echinenone ratios were measured in picocyanobacteria and low zeaxanthin/echinenone ratios were measured in bloom-forming cyanobacteria. The zeaxanthin/echinenone ratio was applied to sediment core samples where the cyanobacterial community was also evaluated by 16S rRNA gene metabarcoding, with the zeaxanthin/echinenone ratios showing similar patterns to those observed in the cultures. The preliminary assessment described here suggests that zeaxanthin/echinenone ratios could provide a valuable paleoecological proxy for evaluating historical shifts in cyanobacterial communities and warrants further exploration.

Improving lake chlorophyll-a interpreting accuracy by combining spectral and texture features of remote sensing.

Cyanobacterial blooms in lakes fueled by increasing eutrophication have garnered global attention, and high-precision remote sensing retrieval of chlorophyll-a (Chla) is essential for monitoring eutrophication. Previous studies have focused on the spectral features extracted from remote sensing images and their relationship with chlorophyll-a concentrations in water bodies, ignoring the texture features in remote sensing images which is beneficial to improve interpreting accuracy. This study explores the texture features in remote-sensing images. It proposes a retrieval method for estimating lake Chla concentration by combining spectral and texture features of remote sensing images. Remote sensing images from Landsat 5 TM and 8 OLI were used to extract spectral bands combination. The gray-level co-occurrence matrix (GLCM) of remote sensing images was used to obtain a total of 8 texture features; then, three texture indices were calculated using texture features. Finally, a random forest regression was used to establish a retrieval model of in situ Chla concentration from texture and spectral index. Results showed that texture features are significantly correlated with lake Chla concentration, and they can reflect the temporal and spatial distribution change of Chla. The retrieval model combining spectral and texture indices performs better (MAE = 15.22μg·L-1, bias = 9.69%, MAPE = 47.09%) than the model without texture features (MAE = 15.76μg·L-1, bias = 13.58%, MAPE = 49.44%). The proposed model performance varies in different Chla concentration ranges and is excellent in predicting higher concentrations. This study evaluates the potential of incorporating texture features of remote sensing images in lake water quality estimation and provides a novel remote sensing method to better estimate lake Chla concentration.

Analysis of Influencing Factors of Chlorophyll-a in Lake Taihu Based on Bayesian Network

Global warming has aggravated the problem of lake eutrophication. As a typical large, eutrophic, shallow lake in China, the issue of cyanobacterial harmful algal blooms (cyanoHABs) was particularly prominent in Lake Taihu. We took Lake Taihu as the study area, using the meteorological (temperature, wind speed, rainfall, and sunshine hours), water quality (total nitrogen, total phosphorus, conductivity, pH, and chemical oxygen demand), and biological (chlorophyll-a in phytoplankton) monitoring data from 1992 to 2020. We built a simulation model of chlorophyll-a based on the Bayesian network model with continuous variables to study the chlorophyll-a level of Lake Taihu under different meteorological and water quality conditions. The 75th percentile of chlorophyll-a concentration was used as the threshold to judge the risk of cyanobacterial bloom. When the probability of chlorophyll-a concentration below this threshold was greater than 75%, it was regarded as "low risk" of cyanobacterial bloom outbreak. The results showed that the average level of "temperature wind ratio" (ratio of air temperature to wind speed) in spring was 6.67℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.130 mg·L-1. The average "temperature wind ratio" level in summer was 10.52℃·s·m-1, and the probability of high chlorophyll-a was less than 75% when the total phosphorus concentration was less than 0.257 mg·L-1. The average level of total phosphorus concentration in autumn was 0.154 mg·L-1, and the probability of high chlorophyll-a was less than 75% when the "temperature wind ratio" was less than 6.30℃·s·m-1. Based on the above research, the chlorophyll-a model constructed by the Bayesian network model with continuous variables was further used to simulate the nutrient control objectives under different climate change backgrounds. In order to control chlorophyll-a in Lake Taihu at the:"low risk" level of cyanoHABs, the target concentration thresholds of total phosphorus needed to be controlled under the climate level background from 1992 to 2000, 2001 to 2010, and 2011 to 2020 were given. From 1992 to 2000, the threshold value of total phosphorus concentration was 0.135 mg·L-1 in spring, 0.174 mg·L-1 in summer, and 0.171 mg·L-1 in autumn. From 2001 to 2010, the threshold value of total phosphorus concentration was 0.115 mg·L-1 in spring, 0.164 mg·L-1 in summer, and 0.162 mg·L-1 in autumn. From 2011 to 2020, the threshold value of total phosphorus concentration was 0.059 mg·L-1 in spring, 0.145 mg·L-1 in summer, and 0.145 mg·L-1 in autumn. The results showed that the control of cyanoHABs in eutrophic lakes required more stringent nutrient control strategies with global warming. It provided a reference for preventing and controlling cyanoHABs and eutrophication in Lake Taihu. Previous studies have used multiple regression models, hydrodynamic numerical models, and other methods to predict chlorophyll-a concentrations or cyanobacterial blooms in lakes. However, there has been no study on the prediction of cyanoHABs in lakes based on the Bayesian network model with continuous variables and the "dynamic" evaluation of nutrient thresholds. Therefore, based on the seasonal meteorological, water quality, and biological monitoring data of Lake Taihu from 1992 to 2020, the chlorophyll-a model of Lake Taihu was constructed for the first time based on the Bayesian network model with continuous variables to simulate the chlorophyll-a concentration of Lake Taihu under different climate indicators and total phosphorus concentrations. The weight of its influencing factors was also analyzed, and the nutrient control objectives under different climate scenarios were "dynamically" evaluated.

Temporal continuous monitoring of cyanobacterial blooms in Lake Taihu at an hourly scale using machine learning.

Cyanobacterial blooms in most lakes exhibit extraordinary changes in time and space. Herein, a cyanobacterial prediction model was designed for Lake Taihu based on a machine learning method. This method can generate temporally continuous (24 moments throughout the day) cyanobacterial data at a fine spatial scale of 9 km. The hourly meteorological data for 24 moments of the day were obtained from ERA5-Land data. Areal coverage of cyanobacterial blooms was derived from the hourly Geostationary Ocean Color Imager reflectance data observed only eight times a day (from ~8:00 to ~15:00, UTC+8). The cyanobacterial and meteorological data of eight moments in Lake Taihu from 2011 to 2020 were used to design the prediction model. The results were compared and validated employing nine training strategies to determine the best cyanobacterial prediction model for Lake Taihu (R = 0.42; root mean square error = 0.10). With the best-fitted model utilizing meteorological data (2011-2020), the area coverage of cyanobacterial blooms at the other 16 moments during a day were estimated. Based on this, the regional and temporal characteristics of diurnal bloom variation were evaluated at an hourly scale. The results indicated that the hourly variations in the areal coverage of cyanobacterial blooms at 24 moments of the day had similar patterns in each subregion of Lake Taihu with minor seasonal variations. The six meteorological variables adopted to construct the model had similar diurnal changes but with diverse value ranges among the seasons. Further analysis revealed that three meteorological variables (temperature, surface pressure, and evaporation) were positively related to diurnal bloom variations at an hourly scale. Overall, these results illustrate that meteorological conditions can affect the occurrence of cyanobacterial blooms at multiple time scales (e.g., hourly, daily, or monthly). The developed cyanobacterial prediction model can provide cyanobacterial data when cyanobacterial data is unavailable for the target waterbody.

Metabolic mechanism and function of cyanobacterial polyphosphate in lakes

大规模蓝藻水华暴发对湖泊水生态系统健康和饮用水安全产生巨大危害，而湖泊水体磷是影响蓝藻水华暴发程度的重要生源要素。应对水体不同磷酸盐浓度，蓝藻高效运行磷酸盐转运系统和磷酸盐特殊转运系统，并合成多聚磷酸盐（聚磷）。蓝藻胞内存在颗粒态、胶体态和可溶态3种形态的聚磷，且不同形态的聚磷分布位置不同。不同蓝藻合成聚磷颗粒的大小、数量和合成期均有所差异。多聚磷酸盐激酶、多聚磷酸盐外切酶、多聚磷酸盐内切酶和P-AMP-磷酸转移酶分别催化聚磷的合成与分解。多聚磷酸盐是二价阳离子的螯合剂，也是磷酸盐及高能磷酸键的储藏库，为细胞生存提供阳离子、磷酸盐和能量，满足蓝藻生命活动过程中生理生化活动所需，具有抵御高温、高pH、紫外线和营养盐缺乏等环境胁迫的生理功能，提升其在不利环境中的生存能力。同时，在蓝藻水华持续暴发、湖泊藻型生境稳态和磷生物地球化学循环过程中聚磷发挥重要的生态功能。因此，蓝藻合成聚磷的分子生物学机制及生态功能研究能够阐明聚磷的存在如何改变湖泊水体-沉积物磷分配、食物网中磷传递等。而开展调控聚磷合成的技术研究，通过控制蓝藻合成聚磷来减轻蓝藻水华暴发规模，将为湖泊水体良性生态系统的重构提供新方法。;Cyanobacterial blooms pose a huge harm to lake aquatic ecosystems health and drinking water safety, and the high phosphorus concentration of lake water bodies is an important inducement for the frequent outbreak of cyanobacterial blooms in lakes. The efficient operation of cyanobacterial intracellular inorganic phosphate transport system and the phosphate special transport system and polyphosphate (polyP) synthesis in cyanobacteria ensures the absorption of phosphate and its survival in phosphorus fluctuating environment. Three forms of polyP including granular, colloidal and soluble polyP, appear in cyanbacterial cells. The subcellular locations of different polyP forms are varied. The size, quantity and the growth period of polyP synthesized are different in different cyanobacterial species. The synthesis and decomposition of polyP are catalyzed by polyphosphate kinase, polyphosphate exonuclease, polyphosphate endonuclease and P-AMP-phosphate transferase, respectively. PolyP is also a chelating agent of divalent cations and a reservoir of phosphate and high-energy phosphate bonds, providing cations, phosphate and energy for cell survival. Cyanobacterial synthesizing polyP is a response to environmental stresses such as high temperature, peroxidation, and nutrient salt deficiency, which improves the viability of cyanobacteria. Therefore, the synthesis of polyP is required for physiological and biochemical activities in the life activities of cyanobacteria. In addition, the synthesis of polyP plays an important ecological function in the continuous outbreak of cyanobacterial blooms and the maintenance of the homeostasis of algal eco-environments. Therefore, it should strengthen the research on the molecular biological mechanism and the ecological function of cyanobacterial polyP synthesis. How the presence of polyphosphorus changes the phosphorus distribution in lake water-sediment and phosphorus transfer in food webs should also be elucidated. The techniques to control large-scale outbreaks of cyanobacterial blooms by controlling the synthesis of polyP in cyanobacteria may provide new methods to reconstruct benign ecosystems in lake waters.

Investigation of cellular structure and metabolic activity of Microcystis cells treated by chlorination

Abstract Frequent outbreaks of cyanobacterial blooms in lakes and reservoirs can result in the deterioration of drinking water quality. Chlorine has been used as an oxidant or algicide to treat cyanobacteria-laden source waters, but influences of chlorination on the cellular structure and metabolic activity of cyanobacterial cells were not well understood. In this study, after chlorination with various initial dosages (0.5–8.0 mg L−1), the cellular size, cellular surface, and cellular structure of Microcystis cells were investigated, and both photosynthetic and respiratory activity of Microcystis cells were also analyzed. Results showed that chlorination of 1–8 mg L−1 could effectively decrease the metabolic activity of Microcystis cells and their cellular structures were severely destroyed (e.g., cell wall, cell membrane, and photosynthetic lamellar). Meanwhile, Microcystis aggregates induced an increase of their particle size distribution of 10–100 μm (1.2–1.9%) in these treatments. In contrast, low-level chlorination of 0.5 mg L−1 did not change the particle size distribution of 2–10 μm along with a slight destruction of cellular structures. Interestingly, this treatment could induce an increase of photosynthetic activity of Microcystis cells (19.0%), implying that insufficient chlorination may not be a proper algicide to control cyanobacterial blooms in lakes or reservoirs.

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

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

Sensitivity of phytoplankton, zooplankton and macroinvertebrates to hydrogen peroxide treatments of cyanobacterial blooms

Addition of hydrogen peroxide (H2O2) is a promising method to acutely suppress cyanobacterial blooms in lakes. However, a reliable H2O2 risk assessment to identify potential effects on non-target species is currently hampered by a lack of appropriate ecotoxicity data. The aim of the present study was therefore to quantify the responses of a wide diversity of freshwater phytoplankton, zooplankton and macroinvertebrates to H2O2 treatments of cyanobacterial blooms. To this end, we applied a multifaceted approach. First, we investigated the 24-h toxicity of H2O2 to three cyanobacteria (Planktothrix agardhii, Microcystis aeruginosa, Anabaena sp.) and 23 non-target species (six green algae, eight zooplankton and nine macroinvertebrate taxa), using EC50 values based on photosynthetic yield for phytoplankton and LC50 values based on mortality for the other organisms. The most sensitive species included all three cyanobacterial taxa, but also the rotifer Brachionus calyciflores and the cladocerans Ceriodaphnia dubia and Daphnia pulex. Next, the EC50 and LC50 values obtained from the laboratory toxicity tests were used to construct a species sensitivity distribution (SSD) for H2O2. Finally, the species predicted to be at risk by the SSD were compared with the responses of phytoplankton, zooplankton and macroinvertebrates to two whole-lake treatments with H2O2. The predictions of the laboratory-based SSD matched well with the responses of the different taxa to H2O2 in the lake. The first lake treatment, with a relatively low H2O2 concentration and short residence time, successfully suppressed cyanobacteria without major effects on non-target species. The second lake treatment had a higher H2O2 concentration with a longer residence time, which resulted in partial suppression of cyanobacteria, but also in a major collapse of rotifers and decreased abundance of small cladocerans. Our results thus revealed a trade-off between the successful suppression of cyanobacteria at the expense of adverse effects on part of the zooplankton community. This delicate balance strongly depends on the applied H2O2 dosage and may affect the decision whether to treat a lake or not.

Compounds to mitigate cyanobacterial blooms affect growth and toxicity of Microcystis aeruginosa

Numerous products and techniques are used to combat harmful cyanobacterial blooms in lakes. In this study, we tested nine products, the phosphate binders Phoslock® and Aqual-PTM, the coagulant chitosan, the phosphorus binder and coagulant aluminum salts (aluminum sulphate and sodium aluminate), the copper-based algicides SeClear, Captain® XTR and CuSO4·5H2O, the antibiotic Streptomycin and the oxidant hydrogen peroxide (H2O2) on their efficiency to manage the cyanobacterium Microcystis aeruginosa (M. aeruginosa). To this end, 7 days of laboratory experiments were conducted and effects were determined on chlorophyll-a, photosystem II efficiency (PSII), soluble reactive phosphorus (SRP) and intracellular and extracellular microcystin (MC) concentrations. The algicides, chitosan and H2O2 were the most powerful in reducing cyanobacteria biomass. Biomass reductions compared to the controls yielded: Chitosan (99.8%) > Hydrogen peroxide (99.6%) > Captain XTR (98.2%) > SeClear (98.1%) > CuSO4·5H2O (97.8%) > Streptomycin (86.6%) > Phoslock® (42.6%) > Aqual-PTM (28.4%) > alum (5.5%). Compounds that caused the largest reductions in biomass also strongly lowered photosystem II efficiency, while the other compounds (Phoslock®, Aqual-PTM, aluminum salts) had no effect on PSII, but strongly reduced SRP. Intracellular MC concentration followed the biomass patterns, extracellular MC was generally lower at higher doses of algicides, chitosan and H2O2 after one week. Recovery of PSII was observed in most algicides and chitosan, but not at the highest doses of SeClear and in all streptomycin treatments. Our results revealed that M. aeruginosa can be killed rapidly using several compounds, that in some treatments already signs of recovery occurred within one week. P fixatives are efficient in reducing SRP, and thus acting via resource suppression, which potentially may provide an addition to fast-acting algicides that kill most of the cells, but allow rapid regrowth as sufficient nutrients remain.

Effects of terrestrial dissolved organic matter on a bloom of the toxic cyanobacteria, Raphidiopsis raciborskii

The concentration of coloured terrestrial dissolved organic matter (tDOM) from vegetation appears to be increasing in lakes in some regions of the world, leading to the term brownification. The light attenuating effect of coloured tDOM on phytoplankton growth has been a major focus of attention, but the phytotoxic effects of tDOM, particularly on cyanobacterial blooms, are less well understood. This mesocosm study tested whether coloured tDOM, leached from the leaves of a Eucalyptus tree species, inhibited a naturally occurring bloom of the toxic cyanobacterium, Raphidiopsis raciborskii, in a reservoir over a 10 day period. The study found that tDOM leachate, measured as dissolved organic carbon (DOC), inhibited photosynthesis and growth of both R. raciborskii, as well as species present at lower densities, i.e. other cyanobacteria and diatoms. However, the effect was greater at higher tDOM input loads. The photosynthetic yield (Fv/Fm) of cyanobacteria decreased rapidly in treatments with 5.9 and 25 mg L−1 DOC addition, compared to the control (reservoir water with background DOC concentration of 6.85 ± 1.09 mg L−1). tDOM had no measurable effect in the 2 and 3.3 mg L−1 DOC addition treatments. By day 5, cell densities of cyanobacteria, including R. raciborskii, and diatoms, in treatments with 5.9 and 25 mg L−1 DOC addition were significantly lower than the control with no tDOM addition, and this effect continued throughout the experiment. This is despite the leachate addition increasing phosphate concentrations which counteracted the low background concentrations of phosphate. Light attenuation and dissolved oxygen (DO) levels were also affected by the tDOM addition, but were only significantly lower in the 25 mg L−1 DOC treatment compared with the control. DOC, dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP) concentrations all decreased in the tDOM addition treatments over the first 3 days, as the microbial cell densities increased. The components of the tDOM that decreased over time were determined by 1H NMR spectroscopy in the 25 mg L−1 DOC treatment. After 5 d, the relative concentrations of fatty acids, sugars and gallic acid decreased by around 60%, while concentrations of flavonoids and myo-inositol decreased by 45 and 35% respectively. This study suggests that phytotoxic compounds in tDOM can suppress cyanobacterial blooms, despite the increased nutrient inputs. This has implications for predicting the future likelihood of cyanobacterial blooms in lakes and reservoirs with climate-change driven changes in flow events, and other changes in the amount and types of vegetation cover. Revegetation of riparian zones, resulting in increased tDOM into waterways, may also be beneficial in reducing cyanobacterial blooms.

Classifying diurnal changes of cyanobacterial blooms in Lake Taihu to identify hot patterns, seasons and hotspots based on hourly GOCI observations

Occurrence of cyanobacterial blooms in most lakes has dramatic changes in time and space. However, most current studies only focused on daily or seasonal scales to obtain a relatively coarse resolution result. To explore the possibility of fine changes occurring within a day in Lake Taihu (China), the area coverage of surface cyanobacterial blooms was quantified from the hourly Geostationary Ocean Color Imager (GOCI) data using a GOCI-derived cyanobacterial index. Based on that, diurnal change characteristics were explored at two scales, and the environmental impacts were investigated. For that, an classification method was first designed to identify the types of diurnal change patterns of cyanobacterial blooms automatically. This method classified the patterns into four types, including the decreasing (Type1), decreasing first and then increasing (Type2), increasing (Type3), increasing first and then decreasing (Type4). Based on that, the types of diurnal change patterns of blooms in Lake Taihu (from April 1, 2011 to October 31, 2020) were identified at pixel (500 m) and synoptic scales. Results indicated that Type1 and Type3 were two hot diurnal change patterns of blooms, and lakeshore was the hotspot occurring severe diurnal changes, and autumn was the hot season occurring frequent diurnal changes. Specifically, hotspot of Type1 was lakeshore, while hotspot of Type3 was Central Regions. Environmental impacts were analyzed at two scales. At pixel scale (500 m), diurnal variation of temperature affected the regional occurence of each type ofdiurnal changes patterns of blooms, and the afternoon temperature played the most critical role (p < 0.001, N = 8316). The occurrence frequency of Type1 was positively (R = 0.41) related with the afternoon temperature, and the occurrence frequency of Type3 was negatively (R = -0.37) related with it. Diurnal variation of wind speed was another key factor impacting the occurrence of obvious diurnal blooms changes, and the wind impacts should be distinguished when the wind speed was over or below 3.5 m/s. At synoptic scale, the interaction of multi environmental factors influenced the diurnal change degree of blooms area, and the environmental contributions were 71%.Comparing with the existing manual classifying workat synoptic scale, the designed classification method can identify the types of diurnal change patterns of blooms at a higher spatial resolution (500 m). These explorations on diurnal dynamics of cyanobacterial blooms in Lake Taihu provide a new insight for advanced cyanobacteria dynamics studies and regional water management.

Effects of temperature and oxygen on cyanobacterial DNA preservation in sediments: A comparison study of major taxa

AbstractThe analysis of sediment DNA has emerged as a promising alternative to classical paleolimnological proxies, which typically rely on hard fossils to reconstruct environmental change. In recent studies, the timing and causes of apparent increases in toxic cyanobacterial blooms in lakes around the world have been identified by high‐throughput sequencing of cyanobacterial 16S rRNA genes from decadal‐ and centennial‐scale sediment records. However, the reconstruction of ecological time series can be influenced by DNA degradation processes interfering with taxonomic resolution and quantification of target genes. To determine whether some cyanobacterial taxa degrade more rapidly than others, a one‐year incubation experiment was performed to estimate degradation rates in sediments under contrasting environmental conditions of temperature (4°C vs. 25°C) and sediment redox (oxic vs. anoxic). Using sediments collected from an oligotrophic lake, serum bottles were inoculated with either Microcystis aeruginosa, Synechococcus sp., or Trichormus variabilis. These cyanobacteria were chosen because they are widespread yet exhibit contrasting morphologies. The absolute concentrations of the target genes were measured over time through droplet digital PCR. The three taxa exhibited log‐linear declines with different rates of decay. Based on first‐order linear decay models, Microcystis exhibited faster decay under oxic conditions, whereas Synechococcus sp. and Trichormus were both temperature and anoxic dependent. Overall, cyanobacterial decay rates were lowest under 4°C anoxic conditions, corresponding to conditions in deep temperate lakes. Under 4°C, Synechococcus exhibited the lowest degradation rates followed by Trichormus, then Microcystis. These findings will be useful in the interpretation of population and community structure data based on sediment DNA and advances our current understanding of cyanobacterial preservation in sediment.

Real-time monitoring of cyanobacterial blooms dynamics around Lake Chaohu based on video surveillance images

蓝藻的防控与治理是湖泊水环境、水生态管理的重要内容，实时获取蓝藻的空间分布信息对于降低蓝藻灾害风险具有重要意义.针对地面调查费时费力、卫星遥感监测粒度较粗且时效性不强等问题，本文提出了一种基于视频监控网络的湖泊蓝藻实时监测技术.基于环巢湖视频监控网络的33个功能摄像机，研究如何从视频图像中实时、准确提取蓝藻的分布信息.为克服不同摄像头的观测角度不一致、光照强度和背景条件不一致等诸多挑战，在视频图像蓝藻表征分析的基础上，通过多尺度深度网络进行图像粗粒度分类，区分蓝藻与浑浊、阴影水体；基于随机森林进行蓝藻精细化识别，克服蓝藻的强异质性.最后以渔政站沿岸水域的日均蓝藻覆盖率和月均蓝藻覆盖率为统计单位，开展了巢湖沿岸蓝藻的动态监测.研究成果可为科学制定蓝藻治理方案提供技术支撑.;The prevention and management of cyanobacterial blooms is an important part of lake environment and water ecological management. Real-time acquisition of spatial distribution of cyanobacterial blooms is of great significance for timely salvage and disaster reduction. Aiming at the problems of time-consuming and laborious ground surveys, satellite remote sensing monitoring with a low spatial and temporal resolution, a new method for real-time monitoring of cyanobacterial blooms in lakes using video surveillance network (VSN) was proposed. Based on the 33 cameras of VSN around Lake Chaohu, the study focuses on the real-time and accurate extraction of cyanobacteria distribution information from video images. First, in order to overcome the challenges of different observation angles from different cameras, light intensities and background conditions, the representation of cyanobacterial blooms in video images was analyzed. Then, a multi-scale depth network was used for coarse-grained image classification to distinguish cyanobacteria from turbid and shadowed water; Random forest method was used to finely recognize cyanobacterial blooms to overcome the strong heterogeneity of cyanobacteria. Finally, the distribution information of cyanobacterial blooms was acquired. Based on the average daily and monthly cyanobacteria coverage of the coastal waters of the fishery administration station, monitoring of cyanobacterial blooms dynamics along the Lake Chaohu coast was completed, which can provide technical support for the management of cyanobacterial blooms.

Monitoring Cyanobacteria Bloom in Dianchi Lake Based on Ground-Based Multispectral Remote-Sensing Imaging: Preliminary Results

Some lakes in China have undergone serious eutrophication, with cyanobacterial blooms occurring frequently. Dynamic monitoring of cyanobacterial blooms is important. At present, the traditional lake-survey-based cyanobacterial bloom monitoring is spatiotemporally limited and requires considerable human and material resources. Although satellite remote sensing can rapidly monitor large-scale cyanobacterial blooms, clouds and other factors often mean that effective images cannot be obtained. It is also difficult to use this method to dynamically monitor and manage aquatic environments and provide early warnings of cyanobacterial blooms in lakes and reservoirs. In contrast, ground-based remote sensing can operate under cloud cover and thus act as a new technical method to dynamically monitor cyanobacterial blooms. In this study, ground-based remote-sensing technology was applied to multitemporal, multidirectional, and multiscene monitoring of cyanobacterial blooms in Dianchi Lake via an area array multispectral camera mounted on a rotatable cloud platform at a fixed station. Results indicate that ground-based imaging remote sensing can accurately reflect the spatiotemporal distribution characteristics of cyanobacterial blooms and provide timely and accurate data for salvage treatment and early warnings. Thus, ground-based multispectral remote-sensing data can operationalize the dynamic monitoring of cyanobacterial blooms. The methods and results from this study can provide references for monitoring such blooms in other lakes.

Quantitative screening for cyanotoxins in soil and groundwater of agricultural watersheds in Quebec, Canada

Cyanotoxins, as secondary metabolites of cyanobacteria, are highly toxic to humans, animals and plants. Cyanobacterial blooms are ‘hot spots’ for cyanotoxin production, but we hypothesized that cyanotoxins will be present in multiple ecological compartments of agricultural watersheds. We detected cyanotoxins in the vadose zone (soil and drainage water from the soil profile) and in groundwater used as a drinking water source from agricultural watersheds. Cyanotoxins detection was confirmed with enzyme-linked immunosorbent assay kits and ultra-high liquid chromatography with tandem mass spectrometry. This work confirms that cyanotoxins exist outside of freshwater lakes, based on detection of microcystins in the vadose zone and in drinking water sourced from groundwater in agricultural watersheds. This suggests that cyanotoxins may be transferred from cyanobacterial blooms in lakes to groundwater through normal hydrologic processes. Public health authorities should be alerted to cyanotoxins in drinking water supplies and proper monitoring and treatment protocols should be implemented to protect citizens from this potential health hazard.