Cyanobacterial Bloom Dynamics Research Articles

The occurrence of positive selection on BicA transporter of Microcystis aeruginosa

The rapid growth of cyanobacteria, particularly Microcystis aeruginosa, poses a significant threat to global water security. The proliferation of toxic Microcystis aeruginosa raises concerns due to its potential harm to human health and socioeconomic impacts. Dense blooms contribute to spatiotemporal inorganic carbon depletion, promoting interest in the roles of carbon-concentrating mechanisms (CCMs) for competitive carbon uptake. Despite the importance of HCO3− transporters, genetic evaluations and functional predictions in M. aeruginosa remain insufficient. In this study, we explored the diversity of HCO3− transporters in the genomes of 46 strains of M. aeruginosa, assessing positive selection for each. Intriguingly, although the Microcystis BicA transporter became a partial gene in 23 out of 46 genomic strains, we observed significant positive sites. Structural analyses, including predicted 2D and 3D models, confirmed the structural conservation of the Microcystis BicA transporter. Our findings suggest that the Microcystis BicA transport likely plays a crucial role in competitive carbon uptake, emphasizing its ecological significance. The ecological function of the Microcystis BicA transport in competitive growth during cyanobacterial blooms raises important questions. Future studies require experimental confirmation to better understand the role of the Microcysits BicA transporter in cyanobacterial blooms dynamics.

Predicting river phytoplankton blooms and community succession using ecological niche modeling

AbstractExcessive phytoplankton concentrations in rivers can result in the loss of plant and invertebrate communities, and threaten drinking water supplies. Whilst the physicochemical controls on algal blooms have been identified previously, how these factors combine to control the initiation, size, and cessation of blooms in rivers is not well understood. We applied flow cytometry to quantify diatom, chlorophyte, and cyanobacterial group abundances in the River Thames (UK) at weekly intervals from 2011 to 2022, alongside physicochemical data. A niche modeling approach was used to identify thresholds in water temperature, flow, solar radiation, and soluble reactive phosphorus (SRP) concentrations required to produce periods of phytoplankton growth, with blooms only occurring when all thresholds were met. The thresholds derived from the 2011 to 2018 dataset were applied to a test data set (2019–2022), which predicted the timing and duration of blooms at accuracies of > 80%. Diatoms and nano‐chlorophyte blooms were initiated by flow and water temperature, and usually terminated due to temperature and flow going out of the threshold range, or SRP and Si becoming limiting. Cyanobacterial bloom dynamics were primarily controlled by water temperature and solar radiation. This simple methodology provides a key understanding of phytoplankton community succession and inter‐annual variation and can be applied to any river with similar water quality and phytoplankton data. It provides early warnings of algal and cyanobacterial bloom timings, which support future catchment management decisions to safeguard water resources, and provides a basis for modeling changing phytoplankton bloom risk due to future climate change.

Monitoring of toxic cyanobacterial blooms in Lalla Takerkoust reservoir by satellite imagery and microcystin transfer to surrounding farms

Cyanobacterial harmful algal blooms (CyanoHABs) threaten public health and freshwater ecosystems worldwide. In this study, our main goal was to explore the dynamics of cyanobacterial blooms and how microcystins (MCs) move from the Lalla Takerkoust reservoir to the nearby farms. We used Landsat imagery, molecular analysis, collecting and analyzing physicochemical data, and assessing toxins using HPLC. Our investigation identified two cyanobacterial species responsible for the blooms: Microcystis sp. and Synechococcus sp. Our Microcystis strain produced three MC variants (MC-RR, MC-YR, and MC-LR), with MC-RR exhibiting the highest concentrations in dissolved and intracellular toxins. In contrast, our Synechococcus strain did not produce any detectable toxins. To validate our Normalized Difference Vegetation Index (NDVI) results, we utilized limnological data, including algal cell counts, and quantified MCs in freeze-dried Microcystis bloom samples collected from the reservoir. Our study revealed patterns and trends in cyanobacterial proliferation in the reservoir over 30 years and presented a historical map of the area of cyanobacterial infestation using the NDVI method. The study found that MC-LR accumulates near the water surface due to the buoyancy of Microcystis. The maximum concentration of MC-LR in the reservoir water was 160 µg L−1. In contrast, 4 km downstream of the reservoir, the concentration decreased by a factor of 5.39 to 29.63 µgL−1, indicating a decrease in MC-LR concentration with increasing distance from the bloom source. Similarly, the MC-YR concentration decreased by a factor of 2.98 for the same distance. Interestingly, the MC distribution varied with depth, with MC-LR dominating at the water surface and MC-YR at the reservoir outlet at a water depth of 10 m. Our findings highlight the impact of nutrient concentrations, environmental factors, and transfer processes on bloom dynamics and MC distribution. We emphasize the need for effective management strategies to minimize toxin transfer and ensure public health and safety.

Моделирование способов управления динамикой цианобактериального цветения с применением воздушных и надводных робототехнических средств

The paper discusses the problem of water areas contaminated with cyanobacteria and ways to eliminate it through the use of robotic means. Laser radiation has the ability to significantly suppress the vital activity of both cyanobacteria and a number of studied pathogenic bacteria, fungal viruses and other microorganisms. The parameters of laser radiation were modeled with an assessment of the inhibitory effect on cyanobacteria in water bodies. Examples of created attachments with laser emitters, transport unmanned aerial vehicles and surface vehicles used in studies to control the dynamics of cyanobacterial blooms are presented.

Influence of Denitrification on Cyanobacterial Blooms Trends in Lake Taihu, China

Denitrification is a major process in aquatic ecosystems, and it competes with cyanobacterial growth for nitrogen. However, the effect of denitrification on cyanobacterial blooms under the background of climate change remains unclear. This study explored the interaction between lake denitrification and formation of cyanobacterial blooms, using the historical water quality monitoring data of North Lake Taihu over five years from 2017 to 2021 and via incubation experiments of cyanobacteria and sediment denitrification. The monitoring data showed that algal biomass (Chla as a proxy) primarily peaked during summer and autumn. The seasonal variations in total N concentration showed a completely opposite trend than that of algal biomass, which peaked in winter and spring. Nitrate was the major component of dissolved inorganic nitrogen, and the nitrate concentration was approximately zero in summer and autumn. The total phosphorus concentration varied in the same way as the Chla concentration. The experimental results showed that Cyanobacteria did not grow when the temperature was below 20℃. In comparison, denitrification showed a significant linear relationship with temperatures between 10-25℃ (R2=0.99) and reached the maximum value of (62.98±21.36) μmol·(kg·h)-1 in Lake Taihu at 25℃. Additionally, the nitrate concentration threshold at the maximum denitrification rate was 4 mg·L-1. Cyanobacteria assimilate nitrate for growth, thereby reducing the concentration of nitrate required for denitrification. This study indicated that the advance in lake temperature warming due to climate change may result in earlier growth of cyanobacteria, thereby leading to large amounts of N being assimilated by algae before denitrification, further affecting the dynamics of cyanobacterial blooms. The present results are scientifically important for explaining the mechanism of cyanobacterial bloom rebound in Lake Taihu under the background of recent climate changes.

Unraveling environmental influences on the spatial and temporal dynamics of cyanobacterial blooms in Lake Erhai during its early stage of eutrophication

ABSTRACT Lake Erhai, a lake in the early stage of eutrophication, has been threatened by algal blooms (particularly the overproliferation of blue-green algae), which can have an impact on drinking water safety and the lake’s ecosystem. Understanding the governing factors of cyanobacterial blooms is critical for taking timely and effective action during this key eutrophication-transition period. However, long-term records of cyanobacterial bloom and its key dominating factors remain unclear. It is, therefore, essential to understand the bloom dynamics and the driving forces before any control strategies can be determined. We investigated the cyanobacterial phycocyanin concentration variability based on satellite observations from 2003 to 2019, by using the empirical orthogonal function analysis. We observed a decrease in the coverage of the dominant mode of variability in phycocyanin magnitudes compared to the period 2003 to 2011, with variations primarily occurring in the northern bays. The largest variability was identified to be predominant in July, and an apparent timing shift in variability was observed in December 2016 and 2017. The 95% quantile regression model indicated a distinct upper boundary response in cyanobacteria proliferation to the joint Total Nitrogen (TN) and Total Phosphorus (TP) concentrations, which occurred in summer from 2003 to 2011. An apparent response of cyanobacterial bloom to TP was observed during the winters from 2016 to 2019. Additionally, water level and TN: TP ratio played a central role in summer from 2003 to 2011, while from 2016 to 2019, TN: TP ratio was found to dominate in the summer months. In winter, air temperature turned out to be a significant modulating factor compared to water level. Our results suggest that implementing a phosphorus reduction strategy, while controlling TN: TP ratio and suitable water level manipulation, should be considered to ensure the sustainability of Lake Erhai, especially under a consistent global warming scenario.

High-Frequency Observations of Cyanobacterial Blooms in Lake Taihu (China) from FY-4B/AGRI

China’s FY-4B satellite, launched on 3 June 2021, is a new-generation geostationary meteorological satellite. The Advanced Geosynchronous Radiation Imager (AGRI) onboard FY-4B has 15 spectral channels, including 2 visible (470 and 650 nm), 1 near infrared (825 nm), and 3 shortwave infrared (1379, 1610, and 2225 nm) bands, which can be used to observe the Earth system with the highest spatial resolution of 500 m and 15 min temporal resolution. In this study, FY-4B/AGRI observations were applied for the first time to monitor cyanobacterial blooms in Lake Taihu, China. The AGRI reflectance at visible and near-infrared bands was first corrected to surface reflectance using the 6S radiative transfer model. Due to the similar spectral reflectance characteristics to those of land-based vegetation, the normalized difference vegetation index (NDVI) and some other remote sensing vegetation indices are usually used for the retrieval of cyanobacterial blooms. The fractional vegetation cover (FVC) of algae, defined as the fraction of green vegetation in the nadir view, was adopted to depict the status and trend of cyanobacterial blooms. NDVI and FVC, the two remote sensing indices developed for the retrieval of land vegetation, were used for the detection of cyanobacteria blooms in Lake Taihu. Finally, the FVC derived from AGRI measurements was compared with that obtained from the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite to validate the effectiveness of our method. It was found that atmospheric correction can substantially improve the determination of the normalized difference vegetation index (NDVI) values of cyanobacterial blooms in the lake. As a proof of the robustness of the algorithm, the NDVIs are both derived from both AGRI and AHI and their magnitudes are similar. In addition, the distribution of cyanobacterial blooms derived from AGRI FVC is highly consistent with that derived from FY-3D/MERSI and EOS/MODIS. While a lower spatial resolution of FY-4B/AGRI might restrict its capability in capturing some spatial details of cyanobacterial blooms, the high-frequency measurements can provide information for the timely and effective management of aquatic ecosystems and help researchers better quantify and understand the dynamics of cyanobacterial blooms. In particular, AGRI can provide greater details on the diurnal variation in the distribution of cyanobacterial blooms owing to the high temporal resolution.

The success of the bloom-forming cyanobacteria Planktothrix: Genotypes variability supports variable responses to light and temperature stress

Cyanobacterial blooms can modify the dynamic of aquatic ecosystems and have harmful consequences for human activities. Moreover, cyanobacteria can produce a variety of cyanotoxins, including microcystins, but little is known about the role of environmental factors on the prevalence of microcystin producers in the cyanobacterial bloom dynamics. This study aimed to better understand the success of Planktothrix in various environments by unveiling the variety of strategies governing cell responses to sudden changes in light intensity and temperature. The cellular responses (photosynthesis, photoprotection, heat shock response and metabolites synthesis) of four Planktothrix strains to high-light or high-temperature were studied, focusing on how distinct ecotypes (red- or green-pigmented) and microcystin production capability affect cyanobacteria's ability to cope with such abiotic stimuli. Our results showed that high-light and high-temperature impact different cellular processes and that Planktothrix responses are heterogeneous, specific to each strain and thus, to genotype. The ability of cyanobacteria to cope with sudden increase in light intensity and temperature was not related to red- or green-pigmented ecotype or microcystin production capability. According to our results, microcystin producers do not cope better to high-light or high-temperature and microcystin content does not increase in response to such stresses.

Investigating the sub-daily dynamics of cyanobacterial blooms by coupling high-frequency time-series remote sensing with hydro-ecological modelling

Cyanobacterial Harmful Algal Blooms (CyanoHABs) are a health-threatening and increasingly prevalent environmental issue at both regional and global levels. An improved understanding of the short-term dynamics of CyanoHABs is required to better capture their spatial pattern and temporal evolution. However, the heterogeneous and dynamic nature of CyanoHABs, and the interacting factors and processes that drive them, make interpreting and predicting the blooms a very challenging task. In this paper, we used an integrative approach that combines high-frequency time-series remote sensing with hydro-ecological modelling, to reproduce and investigate the sub-daily dynamics of CyanoHABs in Taihu Lake. Results show that the distribution of CyanoHABs is highly patchy and dynamic without intensive wind-induced circulation and turbulence, which suggests that the dynamic pattern may be largely caused by the migratory behavior of cyanobacteria. The hydro-ecological model well reproduced the observed pattern and trend, and the average of Root Mean Square Error (RMSE) and coefficient of determination (R2) were 9.82 μg/L and 0.52, respectively. Results from sensitivity analysis suggest that photosynthesis rate and respiration rate are two most influential model parameters. Conclusively, there is a lack of adequate representation of physiological processes in currently used modelling framework, thereby suggesting the need for microscale modelling for future modelling exercises of CyanoHABs.

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.

High-resolution temporal detection of cyanobacterial blooms in a deep and oligotrophic lake by high-frequency buoy data

Cyanobacterial blooms are increasing in magnitude, frequency, and duration worldwide. However, our knowledge of cyanobacterial blooms dynamics and driving mechanisms is still limited due to their high spatiotemporal variability. To determine the potential driving mechanisms of cyanobacterial blooms in oligotrophic lakes, we collected a high-frequency depth profile of chlorophyll fluorescence (ChlF) and synchronous water quality, hydrometeorological data in early spring 2016 in oligotrophic Lake Qiandaohu. The vertical distribution of ChlF exhibited two patterns, “aggregated” and “discrete”, using Morisita's index, and the aggregated ChlF presented subsurface chlorophyll maxima during the thermal stratification period. The ChlF concentration was positively correlated with water temperature and negatively correlated with turbidity. Significantly linear relationships were observed between ChlF vertical structure parameters (e.g., Morisita's index, subsurface chlorophyll maxima depth and thickness) and thermal stratification parameters (e.g., mixing layer depth and relative water column stability). After rainstorm floods, the ChlF pattern suddenly change from “aggregated” to “discrete” and a ChlF concentration <1 μg/L was observed for 7–11 days with a significant increase in the mixing depth layer and turbidity. The results suggest that cyanobacterial blooms are robustly associated with thermal stratification and rainstorm floods in the deep and oligotrophic lake. Thermal stratification boosts surface phytoplankton accumulation by increasing water temperature, enhancing light availability and restricting phytoplankton vertical distribution. Rainstorm floods interrupt the accumulation by disrupting thermal stratification and decreasing the available light. Furthermore, wind speed and air temperature both regulate the phytoplankton dynamics by affecting thermal stratification. Our research quantifies the cyanobacterial bloom dynamics and their relationship between environmental factors, improving our knowledge of the driving mechanisms of cyanobacterial bloom for the protection of drinking water safety and aquatic organism health in lakes.

Quantifying Scales of Spatial Variability of Cyanobacteria in a Large, Eutrophic Lake Using Multiplatform Remote Sensing Tools

Harmful algal blooms of cyanobacteria are increasing in magnitude and frequency globally, degrading inland and coastal aquatic ecosystems and adversely affecting public health. Efforts to understand the structure and natural variability of these blooms range from point sampling methods to a wide array of remote sensing tools. This study aims to provide a comprehensive view of cyanobacterial blooms in Clear Lake, California — a shallow, polymictic, naturally eutrophic lake with a long record of episodic cyanobacteria blooms. To understand the spatial heterogeneity and temporal dynamics of cyanobacterial blooms, we evaluated a satellite remote sensing tool for estimating coarse cyanobacteria distribution with coincident, in situ measurements at varying scales and resolutions. The Cyanobacteria Index (CI) remote sensing algorithm was used to estimate cyanobacterial abundance in the top portion of the water column from data acquired from the Ocean and Land Color Instrument (OLCI) sensor on the Sentinel-3a satellite. We collected hyperspectral data from a handheld spectroradiometer; discrete 1 m integrated surface samples for chlorophyll-a and phycocyanin; multispectral imagery from small Unmanned Aerial System (sUAS) flights (∼12 cm resolution); Autonomous Underwater Vehicle (AUV) measurements of chlorophyll-a, turbidity, and colored dissolved organic matter (∼10 cm horizontal spacing, 1 m below the water surface); and meteorological forcing and lake temperature data to provide context to our cyanobacteria measurements. A semivariogram analysis of the high resolution AUV and sUAS data found the Critical Scale of Variability for cyanobacterial blooms to range from 70 to 175 m, which is finer than what is resolvable by the satellite data. We thus observed high spatial variability within each 300 m satellite pixel. Finally, we used the field spectroscopy data to evaluate the accuracy of both the original and revised CI algorithm. We found the revised CI algorithm was not effective in estimating cyanobacterial abundance for our study site. Satellite-based remote sensing tools are vital to researchers and water managers as they provide consistent, high-coverage data at a low cost and sampling effort. The findings of this research support continued development and refinement of remote sensing tools, which are essential for satellite monitoring of harmful algal blooms in lakes and reservoirs.

Contributions of external nutrient loading and internal cycling to cyanobacterial bloom dynamics in Lake Taihu, China: Implications for nutrient management

AbstractHarmful cyanobacterial blooms (CyanoHABs) are linked to increasing anthropogenic nitrogen (N) and phosphorus (P) inputs. However, CyanoHABs in many large lakes continue despite extensive abatement efforts, mostly focused on external P loading. Internal nutrient cycling can modify nutrient availability and limitation; thus, understanding the relative importance of external vs. internal nutrient loading is essential for developing effective mitigation strategies for CyanoHABs. We estimated long‐term nutrient budgets for Lake Taihu, China, from mass balance models using extensive monitoring of input and output nutrient data from 2005 to 2018 to quantify contributions from internal nutrient loading. The nutrient mass balance showed that 9% and 63% of annual external N and P inputs, respectively, were retained in the lake. Denitrification removed 54% of external N loading and can thus help explain rapid decreases in lake N concentrations and summer N limitation. Water columnregeneration can help sustain CyanoHABs over the short term and contributed 38–58% of potentialdemand for summer‐fall,Microcystis‐dominated blooms. Internal P release contributed 23–90% of CyanoHABs P demand, although Taihu was a net P sink on an annual scale. Our results show that internal nutrient cycling helps sustain CyanoHABs in Taihu, despite reductions in external nutrient inputs. Furthermore, N is leaving the lake faster than P, thereby creating persistent N limitation. Therefore, parallel reductions in external N loading, along with P, will be most effective in reducing CyanoHABs and accelerate the recovery process in this and other large, shallow lakes.

Contributions of external nutrient loading and internal cycling to cyanobacterial bloom dynamics in Lake Taihu, China: Implications for nutrient management

Contributions of external nutrient loading and internal cycling to cyanobacterial bloom dynamics in Lake Taihu, China: Implications for nutrient management

Deciphering the key factors determining spatio-temporal heterogeneity of cyanobacterial bloom dynamics in the Nakdong River with consecutive large weirs

Following the construction of eight large weirs in a 200-km section of the Nakdong River, which is a major water source for the region, harmful cyanobacterial blooms have been occurring annually, causing severe problems with water quality. The present study investigated the community structure of harmful cyanobacteria and identified temporal and spatial patterns in harmful cyanobacterial blooms and their dynamic relationships with physicochemical, hydrological, and meteorological variables in the eight weir sections for 6 years from 2013 to 2018. The dominant harmful cyanobacteria in the eight weir sections were Aphanizomenon and Microcystis spp. There was a successional phenomenon wherein Aphanizomenon spp. first bloomed in spring, and then Microcystis spp. bloomed as water temperatures increased. Additionally, the initiation and duration of the blooms of both genera were affected by the timing and volume of heavy rainfall that caused flushing of cyanobacterial biomass, resulting in direct reduction of cyanobacterial growth in all sections. The harmful cyanobacteria of upstream weirs did not affect the biomass of downstream weirs in terms of either growth initiation or time taken to reach peak biomass, despite being physically connected. Owing to the long retention time during the dry season, similar to what occurs in separate reservoirs, the water quality of each weir section, particularly regarding nutrient characteristics and retention time, were the major factors determining the harmful cyanobacterial abundance, resulting in heterogeneous spatial distribution of harmful cyanobacterial blooms in the Nakdong River.

Hydrogen peroxide measurements in subtropical aquatic systems and their implications for cyanobacterial blooms

Hydrogen peroxide is widely recognized as the most stable of the reactive oxygen species (ROS) produced by both biotic and abiotic pathways in natural waters. Its high reactivity in mediating redox transformations may, directly or indirectly, affect aquatic ecosystem functions, including primary productivity. However, environmental interactions between photoautotrophs, particularly cyanobacteria, and hydrogen peroxide are poorly understood. To gain a better understanding of hydrogen peroxide and cyanobacterial interactions, we determined the hydrogen peroxide concentrations in the presence and absence of cyanobacterial blooms in southwest Florida. Hydrogen peroxide concentrations were determined using a fast response amperometric hydrogen peroxide microelectrode. Our measurements ranged from 0 to 5.3 µM in freshwater bodies (ponds, lakes and the Caloosahatchee River) and 0 to 92.9 µM in rainwater. In general, hydrogen peroxide levels were highly associated with cyanobacterial bloom conditions, indicating the potential role of cyanobacteria in hydrogen peroxide production in freshwater. To determine the potential biodegradation of hydrogen peroxide during sample transportation in the dark condition, water samples were passed through 0.2 µm pore size filters immediately after sampling and compared with unfiltered water samples in the laboratory. We found that filtered water samples retained higher concentrations of hydrogen peroxide than unfiltered samples with a mean biodegradation rate of 44 ± 10.6 nmol/h. Out of a total of 26 samples, only one unfiltered sample showed a higher hydrogen peroxide concentration than the filtered samples. Overall, our study found the microelectrode technique could accurately measure hydrogen peroxide concentrations in the samples from various freshwater bodies. This measurement method revealed that hydrogen peroxide concentrations vary with temporal and spatial dynamics of cyanobacterial blooms.

Increasing Outbreak of Cyanobacterial Blooms in Large Lakes and Reservoirs under Pressures from Climate Change and Anthropogenic Interferences in the Middle–Lower Yangtze River Basin

In recent decades, the increasing frequency and severity of cyanobacterial blooms in recreational lakes and water supply reservoirs have become a great concern to public health and a significant threat to the environment. Cyanobacterial bloom monitoring is the basis of early warning and treatment. Previous research efforts have always focused on monitoring blooms in a few specific lakes in China using moderate resolution imaging spectroradiometer (MODIS) images, which are available for the years 2000 onward. However, the lack of overall information on long-term cyanobacterial blooms in the lakes and reservoirs in the middle–lower Yangtze River (MLYR) basin is an obstacle to better understanding the dynamics of cyanobacterial blooms at a watershed scale. In this study, we extracted the yearly coverage area and frequency of cyanobacterial blooms that occurred from 1990 to 2016 in 30 large lakes and 10 reservoirs (inundation area &gt;50 km2) by using time series Landsat satellite images from Google Earth Engine (GEE). Then, we calculated the cyanobacterial bloom area percentage (CAP) and the cyanobacterial bloom frequency index (CFI) and analyzed their inter-annual variation and trends. We also investigated the main driving forces of changes in the CAP and CFI in each lake and reservoir. We found that all reservoirs and more than 60% of lakes exhibited an increasing frequency and coverage area of cyanobacterial blooms under the pressures of climate change and anthropogenic interferences. Reservoirs were more prone to be affected by fertilizer consumption from their regional surroundings than lakes. High temperatures increased blooms of cyanobacteria, while precipitation in the lake and reservoir regions somewhat alleviated blooms. This study completes the data records of cyanobacterial blooms in large lakes and reservoirs located in hotspots of the MLYR basin and provides more baseline information before 2000, which will present references for water resource management and freshwater conservation.

Beyond Eutrophication: Vancouver Lake, WA, USA as a Model System for Assessing Multiple, Interacting Biotic and Abiotic Drivers of Harmful Cyanobacterial Blooms

Eutrophication of lakes and reservoirs has contributed to an increase in the magnitude and frequency of harmful cyanobacterial blooms; however, the interactive effects of nutrient availability (eutrophication) and other abiotic and biotic drivers have rarely been comprehensively studied in the field. We undertook an eight-year (2005–2013) research program that assessed the interaction of multiple factors driving cyanobacterial blooms in Vancouver Lake, a large, shallow eutrophic lake in Washington, USA. Our program consisted of nearly continuous monthly or weekly monitoring of water quality and plankton community composition over eight years, as well as multiple zooplankton grazing experiments over three years. We found a relatively consistent seasonal succession of phytoplankton and zooplankton assemblages, and a pattern of interacting factors influencing cyanobacterial bloom dynamics. Typically, a combined effect of decreased dissolved inorganic nitrogen (N), a sudden increase of dissolved inorganic phosphorus (P), and a cascading effect of zooplankton grazing created a ‘perfect storm’ of conditions that promoted the rapid proliferation of cyanobacteria over the two to three weeks before a bloom. At the blooms’ peaks, cyanobacterial carbon biomass reached as high as 20 µg L−1, with total [chl a] often exceeding 750 µg L−1. In the weeks following the blooms’ peaks, [PO4-P] and [NH4-N] dropped and copepod feeding rates fell to near zero, whereas microzooplankton grazing rates reached their maxima. Microzooplankton grazing impact, combined with low nutrient availability, then drove down cyanobacteria abundance. Vancouver Lake serves as a model for understanding multiple, interacting drivers of cyanobacterial bloom dynamics in shallow, temperate lakes, and is therefore an important system in which to investigate new questions related to the science and management of harmful algal blooms.

Temporal Dynamics of the Microbial Community Composition with a Focus on Toxic Cyanobacteria and Toxin Presence during Harmful Algal Blooms in Two South German Lakes.

Bacterioplankton plays an essential role in aquatic ecosystems, and cyanobacteria are an influential part of the microbiome in many water bodies. In freshwaters used for recreational activities or drinking water, toxic cyanobacteria cause concerns due to the risk of intoxication with cyanotoxins, such as microcystins. In this study, we aimed to unmask relationships between toxicity, cyanobacterial community composition, and environmental factors. At the same time, we assessed the correlation of a genetic marker with microcystin concentration and aimed to identify the main microcystin producer. We used Illumina MiSeq sequencing to study the bacterioplankton in two recreational lakes in South Germany. We quantified a microcystin biosynthesis gene (mcyB) using qPCR and linked this information with microcystin concentration to assess toxicity. Microcystin biosynthesis gene (mcyE)-clone libraries were used to determine the origin of microcystin biosynthesis genes. Bloom toxicity did not alter the bacterial community composition, which was highly dynamic at the lowest taxonomic level for some phyla such as Cyanobacteria. At the OTU level, we found distinctly different degrees of temporal variation between major bacteria phyla. Cyanobacteria and Bacteroidetes showed drastic temporal changes in their community compositions, while the composition of Actinobacteria remained rather stable in both lakes. The bacterial community composition of Alpha- and Beta-proteobacteria remained stable over time in Lake Klostersee, but it showed temporal variations in Lake Bergknappweiher. The presence of potential microcystin degraders and potential algicidal bacteria amongst prevalent Bacteroidetes and Alphaproteobacteria implied a role of those co-occurring heterotrophic bacteria in cyanobacterial bloom dynamics. Comparison of both lakes studied revealed a large shared microbiome, which was shaped toward the lake specific community composition by environmental factors. Microcystin variants detected were microcystin-LR, -RR, and -YR. The maximum microcystin concentrations measured was 6.7 μg/L, a value still acceptable for recreational waters but not drinking water. Microcystin concentration correlated positively with total phosphorus and mcyB copy number. We identified low abundant Microcystis sp. as the only microcystin producer in both lakes. Therefore, risk assessment efforts need to take into account the fact that non-dominant species may cause toxicity of the blooms observed.

The effect of algal blooms on fish in their inshore nursery grounds in the Gulf of Gdańsk

Studies of cyanobacterial bloom dynamics show that the highest biomass accumulation of Nodularia spumigena is observed in the shallowest area of the Gulf of Gdańsk in summer. In the same region and time, the highest fish abundance is observed. Mostly young individuals of gobies, small sandeel, flounder, three-spine stickleback and young herring occur. In this work we compare how toxic blooms of cyanobacteria influence the number and structure of fish communities in a coastal zone. The results obtained in our study were rather unexpected. More fish species were caught and the biomass of fish was higher during a bloom than in a month following the sampling (no bloom).