Cyanobacteria Blooms Research Articles

Unusual Paralytic Shellfish Poisoning Toxins in Cayuga Lake, New York

Cyanobacteria blooms were detected in 2017 and 2018 in Cayuga Lake, New York, with paralytic shellfish poisoning toxins (PSPTs) the primary toxin detected. Analysis of these samples by HPLC with chemical oxidation, receptor binding assay, ELISA, and LC-MS/MS confirmed the presence of PSPTs but each method gave highly unusual results based on the theory establishing each method. The structures of the toxins could not be identified and may be ‘unusual’ or unelucidated PSPTs.

The Application of Aluminium- and Natural Clay- Based Compounds in the Treatment of Eutrophicated Waters in Semiarid Brazil

Objective: The presence of cyanobacteria in raw water can affect aquatic biota and human health, as some species are potentially toxic. In addition, these organisms can cause operational problems in water treatment plants, causing interference in the coagulation and flocculation processes, in addition to clogging the filters. The objective of this study was to test the efficiency of the application of poly aluminium chloride (PAC) and aluminium sulphate, with and without association with natural clay, in the removal of total phosphorus, chlorophyll a and cyanobacteria cells in eutrophic reservoir waters of the semi-arid region of Northeast Brazil. Theoretical Framework: The study is based on the application of materials (natural clays) with the capacity to adsorb and precipitate phosphorus from the aquatic environment, blocking its release after sedimentation. This application is efficient in removing sedimentation from cyanobacterial blooms with toxic potential from the aquatic environment Method: This is an experimental study, with tests carried out in Jar Test, with water from a eutrophic environment and with cyanobacteria blooms. Water samples were collected from the subsurface to analyze the parameters: pH, total phosphorus (PT), chlorophyll-a and quantity of cyanobacteria. PT pH and concentration were determined according to the techniques described in Standard Methods APHA (2012). Chlorophyll concentration was analyzed using the extraction technique with 96% ethanol (Jespersen; Christoffersen, 1987). For the qualitative and quantitative study of cyanobacteria, the analysis was carried out using an inverted microscope, according to the methodology of Utermöhl (1958), with sedimentation time in the counting chamber established according to the method of Margalef (1983). The density calculation was carried out according to Ross (1979), being expressed in number of individuals per milliliter (ind. mL-1). Results and Conclusion: The combined application of aluminium sulphate and PAC with natural clay (bentonite) functioned as an efficient technique to remove concentrations of total phosphorus and chlorophyll a, in addition to reducing the density of cyanobacteria. The reduction in the number of cyanobacterial cells with associated application of bentonite and coagulants was promising, with the removal of up to 100% of colonial species and 89% of filamentous species. Implications of the Researsh: The research highlights the relevance of applying low-cost techniques that optimize the quality of water offered for public supply. It should be noted that the presence of cyanobacteria in raw water can affect aquatic biota and human health, as some species have toxigenic potential. Furthermore, these organisms can cause operational problems in water treatment plants, interfering with the coagulation and flocculation processes, in addition to clogging filters. Originaly/Value: This study contributes to the understanding of the application of natural products (clays) as a phosphorus adsorbent and intact cyanobacteria cells. The research highlights that with additional studies, this approach could be a useful tool for removing cyanobacteria cells in water from eutrophic environments intended for public supply.

Spatial and Temporal Variability in the Bottom Sediment Characteristics of a Shallow Lake under Backwater Separation and Application of Effective Microorganisms

Lake Konin is a small and shallow lake under the influence of highly eutrophic riverine waters. Feeding the lake as a backwater during high water level periods, the River Obra had exerted a decisive impact on lake water quality, and thus a new dike with a closing device was created. Protective measures were followed by the application of Effective Microorganisms (EM), aiming at a reduction in nutrient concentrations and CyanoHABs. Positive changes in the ecosystem were initiated (increased phytoplankton diversity), but cyanobacteria blooms were still present due to high nutrient content. Some changes were observed in the lake sediments (phosphorus (P) and its fractions, P in pore waters, organic matter and experimental assessment of internal P loading) studied before and during treatment. A slight increase in P content in sediments was noted, as a result of an increase in the Res-P fraction. Simultaneously, a decrease in the most mobile fractions was observed. Summer internal P load was reduced from 5.4 kgP d−1 before the treatment to less than 1 kgP d−1 in the first year, but increased again in the second year to 4.5 kgP d−1. Similarly to lake water quality, positive changes were induced in the lake sediments; nevertheless, they still acted as an important source of nutrients for primary producers. Additional restoration methods shall be considered, as combined treatments used simultaneously are reported to be the most effective for water quality improvement.

Development of an Algorithm for Semantic Segmentation of Earth Remote Sensing Data to Determine Phytoplankton Populations

Introduction. Computer vision is widely used for semantic segmentation of Earth remote sensing (ERS) data. The method allows monitoring ecosystems, including aquatic ones. Algorithms that maintain the quality of semantic segmentation of ERS images are in demand, specifically, to identify areas with phytoplankton, where water blooms— the cause of suffocation — are possible. The objective of the study is to create an algorithm that processes satellite data as input information for the formation and checking of mathematical models of hydrodynamics, which are used to monitor the state of water bodies. Various algorithms for semantic segmentation are described in the literature. New research focuses on enhancing the reliability of recognition — often using neural networks. This approach is modified in the presented work. To develop the direction, a new set of information from open sources and synthetic data are proposed. They are aimed at improving the generalization ability of the model. For the first time, the contour area of the phytoplankton population is compared to the database — and thus the boundary conditions are formed for the implementation of mathematical models and the construction of boundary-adaptive grids.Materials and Methods. The set of remote sensing images was supplemented with the author's augmentation algorithm in Python. Computer vision segmented areas of phytoplankton populations in the images. The U-Net convolutional neural network (CNN) was trained on the basis of NVIDIA Tesla T4 computing accelerators.Results. To automate the detection of phytoplankton distribution areas, a computer vision algorithm based on the U-Net CNN was developed. The model was evaluated by the calculated values of the main quality metrics related to segmentation tasks. The following metric values were obtained: Precision = 0.89, Recall = 0.88, F1 = 0.87, Dice = 0.87, and IoU = 0.79. Graphical visualization of the results of CNN learning on the training and validation sets showed good quality of model learning. This is evidenced by small changes in the loss function at the end of training. The segmentation performed by the model turned out to be close to manual marking, which indicated the high quality of the proposed solution. The area of the segmented region of the phytoplankton population was calculated by the area of one pixel. The result obtained for the original image was 51202.5 (based on information about the number of pixels related to the bloom of blue-green algae). The corresponding result of the modeling was 51312.Discussion and Conclusion. The study expands theoretical and practical knowledge on the use of convolutional neural networks for semantic segmentation of space imagery data. Given the results of the work, it is possible to assess the potential for automating the process of semantic segmentation of remote sensing data to determine the boundaries of phytoplankton populations using artificial intelligence. The use of the proposed computer vision model to obtain contours of water bloom due to phytoplankton will provide for the creation of databases — the basis for environmental monitoring of water resources and predictive modeling of hydrobiological processes.

Simultaneous removal of cyanobacteria and algal organic matter (AOM) by CaCO3 precipitation combined with Polyaluminum chloride (PACl) flocculation

Simultaneous removal of cyanobacteria and algal organic matter (AOM) is still a difficult task for drinking water treatment plants (DWTPs) during cyanobacteria blooms. CaCO3 precipitation, an environment-friendly drinking water treatment technique, has been recommended to removal cyanobacteria or AOM from drinking water. However, knowledge of simultaneous removal performance by CaCO3 precipitation is limited. Here, the simultaneous removal performance to cells and AOM of CaCO3 precipitation, combined with polyaluminum chloride (PACl) flocculation, was investigated, as well as the underlying mechanisms. The results showed that CaCO3 precipitation strategy significantly improved the simultaneous removal performance of PACl, with removal efficiency up to 98 % for cells and 48 % for AOM. CaCO3 precipitation exhibited reliable simultaneous removal effects at various initial cells densities and AOM concentrations. Scanning electron microscope (SEM), transmission electron microscope (TEM) and zeta potential results suggested that mutual flocculation between positively charged CaCO3 crystalline particles and negatively charged cells is the main responsible mechanism for cells removal. Despite that the adsorption of AOM on CaCO3 nuclei surface delays its precipitation, co-precipitation removal mechanism of AOM is realized during CaCO3 nucleation. Moreover, further AOM removal can be obtained by CaCO3 crystalline particles via chemisorption between organic molecules and the particles surface.

Characterization of water microbiota and their relationship with resident oysters during an oyster mortality event.

Microorganisms are vital for the health of marine invertebrates, and their assembly is driven by both deterministic and stochastic factors that regulate residents (innate to the host) and transients (from ambient water). However, the role of water microbiota and the significance of deterministic and stochastic processes in aquatic hosts facing mortality threats are largely unknown. This study examines the shifts in water microbiota during an oyster mortality event using amplicon sequencing and compared with those of resident oysters to disentangle the balance of the deterministic and stochastic factors involved. Water temperature and dissolved oxygen significantly shape the microbial community with a distinct monthly pattern, and Cyanobacteria blooms might exacerbate oyster mortality. The comparative analysis of microbial communities in oysters and water revealed that ≤ 21% of the genera were shared between oysters and water, implying that water microbiota cannot easily transfer into oysters. Furthermore, these shared genera had different functions, with oysters more involved in promoting host digestion and nutrient acquisition and water bacteria enriched more in functions promoting their own growth and survival. These findings illustrate that oysters may possess specific selection or barrier mechanisms that permit a small percentage of transients, controlled by stochastic factors and having a minimal effect on oyster mortality, to enter, whereas the majority of oyster microbiota are residents governed by deterministic factors. Consequently, oysters exhibit some plasticity in their symbiotic microbiota, enabling them to maintain microbial homeostasis and adapt to complex microbial surroundings. This may be a shared mechanism among marine invertebrates for survival in complex marine environments.IMPORTANCEPacific oysters are widely cultured and play vital ecological roles. However, the summer mortality hinders sustainable oyster farming. Untangling causative mechanisms of oyster mortality is a complex task due to the intricate "interactome" involving environmental factors, hosts, and pathogens. Interactions between hosts and microorganisms offer an ideal avenue for investigating the truth. We systematically investigated the microbial community in water and resident oysters during a summer mortality event and proposed that the assembly of oyster microbiota is primarily governed by deterministic processes independent of mortality. Pathogens mainly originate from resident members of the oyster microbiota, with a limited influence from the microbial community in the water. Additionally, environmental degraders, such as Cyanobacteria blooms, cannot be overlooked as a contributing factor of oyster mortality. This study evaluated the weight of deterministic and stochastic factors in microbial assembly during an oyster mortality event and greatly broadened our understanding of the "interactome" through the interaction between oysters and water in microbiota.

Combined measures in lake restoration – A powerful approach as exemplified from Lake Groote Melanen (the Netherlands)

Controlling lake eutrophication is a challenge. A case-specific diagnostics driven approach is recommended that will guide to a suite of measures most promising in restoration of eutrophic lakes as exemplified by the case of the shallow lake Groote Melanen, The Netherlands. A lake system analysis identified external and internal nutrient load as main reasons for poor water quality and reoccurring cyanobacterial blooms in the lake. Based on this analysis, a package of restoration measures was implemented between January 2015 and May 2016. These measures included fish removal, dredging, capping of peat rich sediment with sand and an active barrier (lanthanum-modified bentonite), diversion of two inlet streams, reconstruction of banks, and planting macrophytes. Dredging and sand capping caused temporarily elevated turbidity and suspended solids concentrations, while addition of the lanthanum-modified clay caused a temporary exceedance of the Dutch La standard for freshwaters. Diversion of inflow streams caused 35 % less water inflow and larger water level fluctuations, but the lake remained water transporting with strongly improved water quality as was revealed by comparing five years pre-intervention water quality data with five years’ post-intervention data. Total phosphorus concentration in the water column was reduced by 93 % from 0.47 mg P l-1 before the intervention to 0.03 mg P l-1 after the intervention, total nitrogen by 66 % from 1.27 to 0.21 mg N l-1, total chlorophyll-a by 75 % from 68 to 16 µg l-1, cyanobacteria chlorophyll-a by 88 % from 32 to 4 µg l-1. Turbidity had declined by 58 % from 23.5 FTU to on average 9.9 FTU. No cyanobacteria blooms were recorded over the entire post-intervention monitoring period (2016–2021). Submerged macrophytes increased from complete absence before intervention to around 10 %–15 % coverage after intervention. Repeated fish removal lowered the fish stock to below 100 kg ha-1 with 12 % of bream and carp remaining. Hence, the package of cohesive measures that was based on a thorough diagnosis resulted in rapidly, strongly and enduringly improved water quality. This case provides evidence for the power of combining measures in restoring eutrophic lakes.

Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Třeboň fishponds, Czech Republic

Cyanobacteria blooms in fishponds, driven by climate change and anthropogenic activities, have become a critical concern for aquatic ecosystems worldwide. The diversity in fishpond sizes and fish densities further complicates their monitoring. This study addresses the challenge of accurately predicting cyanobacteria concentrations in turbid waters via remote sensing, hindered by optical complexities and diminished light signals. A comprehensive dataset of 740 sampling points was compiled, encompassing water quality metrics (cyanobacteria levels, total chlorophyll, turbidity, total cell count) and spectral data obtained through AlgaeTorch, alongside Sentinel-2 reflectance data from three Třeboň fishponds (UNESCO Man and Biosphere Reserve) in the Czech Republic over 2022–2023. Partial Least Squares Regression (PLSR) and three machine learning algorithms, Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), were developed based on seasonal and annual data volumes. The SVM algorithm demonstrated commendable performance on the one-year data validation dataset from the Svět fishpond for the prediction of cyanobacteria, reflected by the key performance indicators: R2 = 0.88, RMSE = 15.07 μg Chl-a/L, and RPD = 2.82. Meanwhile, SVM displayed steady results in the unified one-year validation dataset from Naděje, Svět, and Vizír fishponds, with metrics showing R2 = 0.56, RMSE = 39.03 μg Chl-a/L, RPD = 1.50. Thus, Sentinel data proved viable for seasonal cyanobacteria monitoring across different fishponds. Overall, this study presents a novel approach for enhancing the precision of cyanobacteria predictions and long-term ecological monitoring in fishponds, contributing significantly to the water quality management strategies in the Třeboň region.

Microplastics enhanced the allelopathy of pyrogallol on toxic Microcystis with additional risks: Microcystins release and greenhouse gases emissions

Cyanobacteria blooms (CBs) caused by eutrophication pose a global concern, especially Microcystis aeruginosa (M. aeruginosa), which could release harmful microcystins (MCs). The impact of microplastics (MPs) on allelopathy in freshwater environments is not well understood. This study examined the joint effect of adding polystyrene (PS-MPs) as representative MPs and two concentrations (2 and 8 mg/L) of pyrogallol (PYR) on the allelopathy of M. aeruginosa. The results showed that the addition of PS-MPs intensified the inhibitory effect of 8 mg/L PYR on the growth and photosynthesis of M. aeruginosa. After a 7-day incubation period, the cell density decreased to 69.7 %, and the chl-a content decreased to 48 % compared to the condition without PS-MPs (p < 0.05). Although the growth and photosynthesis of toxic Microcystis decreased with the addition of PS-MPs, the addition of PS-MPs significantly resulted in a 3.49-fold increase in intracellular MCs and a 1.10-fold increase in extracellular MCs (p < 0.05). Additionally, the emission rates of greenhouse gases (GHGs) (carbon dioxide, nitrous oxide and methane) increased by 2.66, 2.23 and 2.17-fold, respectively (p < 0.05). In addition, transcriptomic analysis showed that the addition of PS-MPs led to the dysregulation of gene expression related to DNA synthesis, membrane function, enzyme activity, stimulus detection, MCs release and GHGs emissions in M. aeruginosa. PYR and PS-MPs triggered ROS-induced membrane damage and disrupted photosynthesis in algae, leading to increased MCs and GHG emissions. PS-MPs accumulation exacerbated this issue by impeding light absorption and membrane function, further heightening the release of MCs and GHGs emissions. Therefore, PS-MPs exhibited a synergistic effect with PYR in inhibiting the growth and photosynthesis of M. aeruginosa, resulting in additional risks such as MCs release and GHGs emissions. These results provide valuable insights for the ecological risk assessment and control of algae bloom in freshwater ecosystems.

Cyanobacteria in the Anthropocene: Synanthropism forged in an era of global change.

The Anthropocene has driven a transformative era where human activities exert unprecedented influence on Earth's biosphere. Consequently, synanthropic organisms, adept at thriving in human-modified environments, have emerged. While well studied in terrestrial ecosystems, the presence and ecological importance of synanthropic species in aquatic ecosystems, specifically among cyanobacteria, are less understood. Cyanobacteria blooms, notorious for their detrimental effects on ecosystems and human health, are increasing in frequency and intensity globally. In this perspective, we explore the evidence supporting this rise of cyanobacteria blooms, emphasizing the roles of human-induced eutrophication and climate change on select cyanobacteria genera. Cyanobacteria are not a monolith, with certain genera showing an observable increase within anthropogenically modified environments. We propose the establishment of a new sub-branch of phycology that explicitly investigates the ecology and physiology of synanthropic cyanobacteria. Understanding the intricate interactions between synanthropic species and human populations is imperative for managing human-altered ecosystems and conserving freshwater resources, particularly in the face of increasing global water insecurity. PRACTITIONER POINTS: The rise in cyanobacteria blooms is driven by a small subset of human-adapted genera-synanthropic cyanobacteria. Research is needed to characterize synanthropic cyanobacteria, which will aid in developing tailored management approaches. A paradigm shift from domesticating to "rewilding" landscapes and modifying behaviors to facilitate cohabitation are solutions to reducing risks.

Stochastic dynamics of phycocyanin in years of contrasting phosphorus load

AbstractResilience, measured by the distribution of passage times between alternate states, indicates persistence of a state in stochastic dynamic systems such as blooms of cyanobacteria in lakes. We used high‐frequency datasets to compare the resilience of low and high states of phycocyanin, a pigment indicator of cyanobacteria, in Lake Mendota, Wisconsin, USA, for three growing seasons that ranged sevenfold in external phosphorus (P) load. Each year we observed 139–265 passage times across the unstable threshold that separated the low‐ from high‐phycocyanin states. Each sample of passage times is highly skewed with low median, larger mean, much larger SD, and wide tails extending to long lifetimes of a state. About 25% of events, whether low or high phycocyanin, lasted a day or more. Among these 3 years of contrasting external P load, there were no discernible differences in the resilience of either ecosystem state. We attribute this lack of contrast to the sustained recycling of P from sediments and the high stochasticity of phycocyanin in this lake.

A Förster Resonance Energy Transfer (FRET)-Based Immune Assay for the Detection of Microcystin-LR in Drinking Water.

Cyanobacteria bloom is the term used to describe an abnormal and rapid growth of cyanobacteria in aquatic ecosystems such as lakes, rivers, and oceans as a consequence of anthropic factors, ecosystem degradation, or climate change. Cyanobacteria belonging to the genera Microcystis, Anabaena, Planktothrix, and Nostoc produce and release toxins called microcystins (MCs) into the water. MCs can have severe effects on human and animal health following their ingestion and inhalation. The MC structure is composed of a constant region (composed of five amino acid residues) and a variable region (composed of two amino acid residues). When the MC variable region is composed of arginine and leucine, it is named MC-LR. The most-common methods used to detect the presence of MC-LR in water are chromatographic-based methods (HPLC, LC/MS, GC/MS) and immunological-based methods (ELISA). In this work, we developed a new competitive Förster resonance energy transfer (FRET) assay to detect the presence of traces of MC-LR in water. Monoclonal antibody anti-MC-LR and MC-LR conjugated with bovine serum albumin (BSA) were labeled with the near-infrared fluorophores CF568 and CF647, respectively. Steady-state fluorescence measurements were performed to investigate the energy transfer process between anti-MC-LR 568 and MC-LR BSA 647 upon their interaction. Since the presence of unlabeled MC-LR competes with the labeled one, a lower efficiency of FRET process can be observed in the presence of an increasing amount of unlabeled MC-LR. The limit of detection (LoD) of the FRET assay is found to be 0.245 nM (0.245 µg/L). This value is lower than the provisional limit established by the World Health Organization (WHO) for quantifying the presence of MC-LR in drinking water.

Genotoxicity detected during cyanobacteria bloom in a water supply reservoir

The aquatic ecosystems are susceptible to cyanobacterial blooms due to the eutrophication of water bodies caused by human activities. In this study, phytoplankton and cyanotoxins analysis, as well as cellular and genetic biomarkers of toxicity (Allium cepa test - higher plant test system), were evaluated in water samples of Alagados Reservoir during a cyanobacterial bloom in South Brazil. The water samples were collected during the wet season at two sites in the Reservoir. Paralytic shellfish toxins (PSTs) were detected in both samples (sites 1 and 2); however, the levels of PSTs were higher in site 1. Gonyautoxin 2 was the major cyanotoxin found in the Reservoir. Both samples were able to induce cytotoxic effects (reduced Mitotic Index) and damage the genetic material (i.e., increased frequencies of chromosome aberration and micronuclei) of meristematic cells of A. cepa. The cellular and genetic damages were higher in the sample site 1, wherein high levels of PSTs were verified. Thus, our findings suggested that cyanotoxins-contaminated waters may damage the genetic material of living organisms, and therefore this group of contaminants should be assessed for their potential genotoxicity.

Adverse effects of Microcystis aeruginosa exudates on the filtration, digestion, and reproduction organs of benthic bivalve Corbicula fluminea

Cyanobacteria bloom and the secondary metabolites released by the microorganism are extremely harmful to aquatic animals, yet study on their adverse effects in zoobenthos is rare. Corbicula fluminea widely distributed in freshwater environment with algal blooms. It is a typical filter feeding zoobenthos that may be affected by the secondary metabolites of cyanobacteria due to its high filtering rate. In this study, C. fluminea was exposed to Microcystis aeruginosa exudates (MaE) for 96 h, which was obtained from 5 × 105 cells/mL and 2.5 × 106 cells/mL exponential stage M. aeruginosa culture solution that represented cyanobacteria cell density needs environmental risk precaution control and emergent control, respectively. The responses of C. fluminea critical organs to MaE were analyzed and evaluated based on histopathological sections, antitoxicity biomarkers, and organ function biomarkers. The results showed that all the organs underwent structural disorders, cell vacuolization, apoptosis, and necrosis, and the damage levels increased as MaE concentration increased. The detoxification and antioxidant defense systems biomarkers in each organ response to MaE exposure differently and the level of reaction improved when MaE concentration increased. The siphon rate and acetylcholinesterase activity showed that the filtration function decreased significantly as the MaE concentration increased. Increased activity of glutathione S-transferase and amylase in the digestive gland indicate that it is the major detoxification organ of C. fluminea. Increased vitellogenin concentration and enlarged oocytes in the gonad indicate that MaE may have an estrogenic effect on C. fluminea. This study demonstrates that cyanobacteria threat benthic bivalves by inducing oxidative stress, inhibiting filtering feeding system, and disturbing digestion system and reproduction potential of C. fluminea.

Analysis of Meteorological Drivers of Taihu Lake Algal Blooms over the Past Two Decades and Development of a VOCs Emission Inventory for Algal Bloom

Cyanobacterial blooms represent a common environmental issue in aquatic systems, and these blooms bring forth numerous hazards, with the generation of volatile organic compounds (VOCs) being one of them. Global climate change has led to alterations in various climatic factors affecting algal growth, indirectly impacting the quantity of VOCs released by algae. With advancements in remote sensing technology, exploration of the spatiotemporal distributions of algae in large water bodies has become feasible. This study focuses on Taihu Lake, characterized by frequent occurrences of cyanobacterial blooms. Utilizing MODIS satellite imagery from 2001 to 2020, we analyzed the spatiotemporal characteristics of cyanobacterial blooms in Taihu Lake and its subregions. Employing the LightGBM machine learning model and the (SHapley Additive exPlanations) SHAP values, we quantitatively analyzed the major meteorological drivers influencing cyanobacterial blooms in each region. VOC-related source spectra and emission intensities from cyanobacteria in Taihu Lake are collected based on the literature review and are used to compile the first inventory of VOC emissions from blue-green algae blooms in Taihu Lake. The results indicate that since the 21st century, the situation of cyanobacterial blooms in Taihu Lake has continued to deteriorate with increasing variability. The relative impact of meteorological factors varies across different regions, but temperature consistently shows the highest sensitivity in all areas. The VOCs released from the algal blooms increase with the proliferation of the blooms, posing a continuous threat to the atmospheric environment of the surrounding cities. This study aims to provide a scientific basis for further improvement of air quality in urban areas adjacent to large lakes.

Metabolic activity of Planktothrix rubescens and its consequences on oxygen dynamics in laboratory experiment: A stable isotope study.

Fluctuations in dissolved oxygen (DO) contents in natural waters can become intense during cyanobacteria blooms. In a reconnaissance study, we investigated DO concentrations and stable isotope dynamics during a laboratory experiment with the cyanobacterium Planktothrix rubescens in order to obtain insights into primary production under specific conditions. This observation was extended to sub-daily timescales with alternating light and dark phases. Dissolved oxygen concentrations and its isotopes (δ18ODO) ranged from 0.02 to 0.06 mmol · L-1 and from +9.6‰ to +23.4‰. The δ18ODO proved to be more sensitive than concentration measurements in response to metabolic variation and registered earlier shifts to dominance by respiration. Oxygen (O2) contents in the headspace and its isotopes (δ18OO2) ranged from 2.62 to 3.20 mmol · L-1 and from +9.8‰ to +21.9‰. Headspace samples showed less fluctuations in concentration and isotope trends because aquatic processes were hardly able to alter signals once the gas had reached the headspace. Headspace δ18OO2 values were corrected for gas-water equilibration and were determinedto be higher than the mean δ18OH2O of -8.7‰. This finding suggests that counteracting respiration was important even during the highest photosynthetic activity. Additionally, headspace analyses led to the definition of a fractionation factor for respiration (αR) of this cyanobacterium with a value of 0.980. This value confirms the one commonly used for cyanobacteria. Our findings may become important for the management of water bodies where decreases in DO are caused by cyanobacteria.

Real-time water quality forecasting in rivers using satellite data and dynamic models: an online system for operational management, control and citizen science

Increasingly scarce water resources and growing global populations have exacerbated the problems of water quality in river systems and freshwaters in general. New monitoring methodologies and tools to democratize access to water quality information are needed if we are to reach ambitious societal objectives such as the UN Sustainable Development Goals and the European Green Deal. Here we present a cloud-based system for producing publicly accessible real time water quality forecasts coupled to novel biosensor technology. Short term forecasts of water quality impairments, e.g., as cyanobacteria blooms, sediment plumes and toxic pollution incidents are increasingly relevant both to citizens and stakeholders. Here, we present a new cloud based system that utilizes satellite data to produce real time forecasts of flow and water quality using a chain of dynamic catchment-scale models at multiple locations in a river network. We demonstrate this new system using two case studies: the River Thames and the Essex Colne River (United Kingdom). These rivers are key water supply sources for London and South-East England, respectively and are of high interest to recreational water users. We show how the new system can predict and forecast water quality, estimate toxicity and connect to citizen science observations using an App (www.aquascope.com) for information synthesis and delivery.

Changes in physiology, antioxidant system, and gene expression in Microcystis aeruginosa under fenoxaprop-p-ethyl stress.

Fenoxaprop-p-ethyl (FE) is one of the typical aryloxyphenoxypropionate herbicides. FE has been widely applied in agriculture in recent years. Human health and aquatic ecosystems are threatened by the cyanobacteria blooms caused by Microcystis aeruginosa, which is one of the most common cyanobacteria responsible for freshwater blooming. Few studies have been reported on the physiological effects of FE on M. aeruginosa. This study analyzed the growth curves, the contents of chlorophyll a and protein, the oxidative stress, and the microcystin-LR (MC-LR) levels of M. aeruginosa exposed to various FE concentrations (i.e., 0, 0.5, 1, 2, and 5mg/L). FE was observed to stimulate the cell density, chlorophyll a content, and protein content of M. aeruginosa at 0.5- and 1-mg/L FE concentrations but inhibit them at 2 and 5mg/L FE concentrations. The superoxide dismutase and catalase activities were enhanced and the malondialdehyde concentration was increased by FE. The intracellular (intra-) and extracellular (extra-) MC-LR contents were also affected by FE. The expression levels of photosynthesis-related genes psbD1, psaB, and rbcL varied in response to FE exposure. Moreover, the expressions of microcystin synthase-related genes mcyA and mcyD and microcystin transportation-related gene mcyH were significantly inhibited by the treatment with 2 and 5mg/L FE concentrations. These results might be helpful in evaluating the ecotoxicity of FE and guiding the rational application of herbicides in modern agriculture.

Founder populations of Stuckenia pectinata in restored ponds originate from genetically diverse propagule pool: A case study of urban ponds in Brussels, Belgium

Eutrophication and cyanobacteria blooms are considered major problems for the biodiversity and water quality of urban ponds. While biomanipulation techniques such as drawdown with fish removal have great potential to restore turbid ponds to a clearwater status, it remains difficult to predict if and how macrophytes will recover naturally. Here, we used individual genotyping and population genetics based on 20 nuclear microsatellite loci to investigate the recruitment and recolonization strategies of the submerged macrophyte Stuckenia pectinata (L.) Börner. More specifically, we compared the founder genetic diversity of recovering populations just after biomanipulation to the genetic diversity of spontaneous, contiguous populations that settled over an extended period of time and were within the same catchment. Our results showed that turbid ponds may contain a persistent propagule bank that allows for an immediate re-establishment of genetically diverse populations of S. pectinata once a desired clearwater state is restored. Therefore, biomanipulation without sediment removal proved to be successful for founding populations to become immediately integrated with their established populations, thus maintaining the overall diversity of this species within local areas. Additionally, our results demonstrated an excess of heterozygotes in established populations that may be caused by substantial drift in albeit small effective population sizes of this predominantly outbreeding species.

Earth Observation-Based Cyanobacterial Bloom Index Testing for Ecological Status Assessment in the Open, Coastal and Transitional Waters of the Baltic and Black Seas

The use of Earth Observation (EO) for water quality monitoring has substantially raised in the recent decade; however, harmonisation of EO-based indicators across the seas to support environmental policies is in great demand. EO-based Cyanobacterial Bloom Index (CyaBI) originally developed for open waters, was tested for transitional and coastal waters of the Lithuanian Baltic Sea and the Ukrainian Black Sea during 2006–2019. Among three tested neural network-based processors (FUB-CSIRO, C2RCC, standard Level-2 data), the FUB-CSIRO applied to Sentinel-3 OLCI images was the most appropriate for the retrieval of chlorophyll-a in both seas (R2 = 0.81). Based on 147 combined MERIS and OLCI synoptic satellite images for the Baltic Sea and 234 for the Black Sea, it was shown that the CyaBI corresponds to the eutrophication patterns and trends over the open, coastal and transitional waters. In the Baltic Sea, the cyanobacteria blooms mostly originated from the central part and the outflow of the Curonian Lagoon. In the Black Sea, they occurred in the coastal region and shelf zone. The recent decrease in bloom presence and its severity were revealed in the areas with riverine influence and coastal waters. Intensive blooms significantly enhanced the short-term increase in sea surface temperature (mean ≤ 0.7 °C and max ≤ 7.0 °C) compared to surrounding waters, suggesting that EO data originating from thermal infrared sensors could also be integrated for the ecological status assessment.