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Harmful algal blooms (HABs), mainly formed by dinoflagellates, have detrimental effects on marine ecosystems and public health. Therefore, detecting HABs is crucial for early warning and prevention of HABs as well as the mitigation of their adverse effects. Although various methods, such as light microscopy, electron microscopy, real-time PCR, andmicroarrays, have already been established for the detection of HABs, they are still cumbersome to be exploited in the field. Therefore, rapid nucleic detection methods such as recombinase polymerase amplification (RPA) and loop-mediated isothermal amplification (LAMP)-lateral flow dipstick (LFD) have been developed for monitoring bloom-forming algae. However, the CRISPR/Cas-based detection of HABs has yet to be applied to this field. In this study, we developed a method for detecting Karenia mikimotoi (K. mikimotoi), a typical ichthyotoxic dinoflagellate responsible for global blooms. Our method utilized Cas12a from Lachnospiraceae bacterium ND2006 (LbCas12a) to target and cleave the internal transcribed spacer (ITS) of K.mikimotoi, guided by RNA. We leveraged the target-activated non-specific single-stranded deoxyribonuclease cleavage activity of LbCas12a to generate signals that can be detected using fluorescence-read machines or LFDs. By combining RPA and LbCas12a with reporters, we significantly enhanced the sensitivity, enabling the detection of ITS-harboring plasmids at concentrations as low as 9.8 aM and genomic DNA of K. mikimotoi at levels as low as 3.6 × 10-5 ng/µl. Moreover, we simplified the genomic DNA extraction method using cellulose filter paper (CFP) by directly eluting the DNA into RPA reactions, reducing the extraction time to <30 s. The entire process, from genomic DNA extraction to result reporting, takes less than an hour, enabling the identification of nearly a single cell. In conclusion, our method provided an easy, specific, and sensitive approach for detecting K. mikimotoi, offering the potential for efficient monitoring and management of K. mikimotoi blooms. [ABSTRACT FROM AUTHOR]

Cyanobacterial harmful algal blooms in freshwater systems can produce cyanotoxins, such as microcystins (MCs) and nodularins (NODs), presenting serious threats to human health and ecosystems. Required routine monitoring of cyanotoxins in water samples, as posed by U.S. EPA drinking water contaminant candidate list 5 (CCL5), demands for cost-effective, reliable and sensitive MCs/NODs detection methods. We report the development of a colorimetric paper-based immunochip assisted by nanozyme catalysis with a smartphone readout system for rapid detection of cyanotoxins in water. We show that the introduction of biorthogonal click reaction enables in situ facile self-assembly of multi-layers of peroxidase-like nanozyme onto the anti-MCs/NODs monoclonal antibody. We can detect 13 variants of MCs/NODs even in the sub-microgram per liter range with detection limit of below 0.7 μg/L and satisfactory recovery percentages between 88 and 120% in different water matrices. Our technology shows a good correlation with the well-developed ELISA technology, demonstrating its great potential applications in resource-limited or less-developed regions for on-site and large-scale screening of cyanotoxins in water environment. [Display omitted] • A paper-based biochip with high sensitivity and throughput for cyanotoxins. • A layer-by-layer bioorthogonal click reaction for nanozyme amplification. • Limit of detection below 0.7 μg/L towards 13 variants of cyanotoxins. • Satisfactory recoveries in various water environments. • An entire detection cycle time of less than 60 min. [ABSTRACT FROM AUTHOR]

Timely and accurate observations of harmful algal blooms dynamics help to coordinate coastal protection and reduce the damage in advance. To date, predicting changes in the spatial distribution of algal blooms has been challenging due to the lack of suitable tools. The paper proposes that the development and disappearance of algal bloom can be monitored by satellite remote sensing in a large area from the diurnal variation of chlorophyll a. In this paper, 32 pairs of observed data in 2011–2020 showed that it was most appropriate to outline the areas where the diurnal variation (the standard deviation calculated from the daily chlorophyll a) in chlorophyll a was more than 2.2 mg/m3 . Among them, 30 pairs of data showed that the high chlorophyll a diurnal variation could predict the growth of the algal bloom in the next days. In these events, the median area difference between the two spatial distributions was -0.08%. When there was a high diurnal variation in chlorophyll a in the area adjacent to where algal bloom was occurred, a new algal bloom region was likely to spread in subsequent days. Continuous multiday time series showed that the diurnal variation in chlorophyll a can reflect the algal bloom’s overall growth condition. [ABSTRACT FROM AUTHOR]

In response to the challenges introduced by global warming and increased eutrophication, this paper presents an innovative modeling and simulation (M&S)-driven model for developing an automated inland water monitoring system. This system is grounded in a layered Internet of Things (IoT) architecture and seamlessly integrates cloud, fog, and edge computing to enable sophisticated, real-time environmental surveillance and prediction of harmful algal and cyanobacterial blooms (HACBs). Utilizing autonomous boats as mobile data collection units within the edge layer, the system efficiently tracks algae and cyanobacteria proliferation and relays critical data upward through the architecture. These data feed into advanced inference models within the cloud layer, which inform predictive algorithms in the fog layer, orchestrating subsequent data-gathering missions. This paper also details a complete development environment that facilitates the system lifecycle from concept to deployment. The modular design is powered by Discrete Event System Specification (DEVS) and offers unparalleled adaptability, allowing developers to simulate, validate, and deploy modules incrementally and cutting across traditional developmental phases. [ABSTRACT FROM AUTHOR]

The Limnology & Oceanography Bulletin has published a list of the top three accessed articles for each issue in the second quarter of 2023. The articles cover a range of topics including nitrogen patterns in a eutrophic lake during an algal bloom, prey selection in copepods, and the effects of ocean acidification on marine phytoplankton. Other articles explore the interactive effects of nitrogen and phosphorus on lake phytoplankton, the contribution of migrating copepods to the carbon pump, and the response of under-ice plankton communities to a snow removal experiment. The final set of articles investigate the unique carbon isotope fingerprints of microalgal taxonomic groups, the control of bottom hypoxia in alpine lakes, and the implications of sea-level rise on intertidal primary production. The authors are commended for their contributions to the journal. [Extracted from the article]

Most of the microscopic images of Harmful Algae Blooms (HABs) acquired in marine engineering are subject to blurred cell textures and poor overall clarity due to the effects of seawater impurities, unknown suspended particle deposits and high-speed cell motions. To solve the above problems, a microscopic image enhancement method based on the recursive-overlapped contrast limited adaptive histogram specification (CLAHS) and dual-image wavelet fusion (RO-CLAHS and DIWF) is proposed in this paper. It combines three main steps: homomorphic filtering, empirical modal feature map extraction, and dual-image wavelet fusion. This method firstly adopts homomorphic filtering to strengthen the illumination uniformity of the entire HABs image, and then obtains an empirical modal feature map of algal cells by an improved empirical modal decomposition method, which highlights the detailed features of algal cells due to histogram stretching, clip limit and grey-level mapping. Finally, this paper proposes a dual-image wavelet fusion method adapted for HAB microscopic images, which integrates the images processed by contrast limited adaptive histogram equalization (CLAHE) with an empirical modal feature map and then achieves the image enhancement effect. The comparison experimental results show that the enhanced microscopic images of HABs by this method presents the best texture clarity and global contrast and improves the accuracy of algae image edge detection significantly. [ABSTRACT FROM AUTHOR]

This document summarizes a collection of research papers on the effects of anthropogenic activities and climate change on harmful algal blooms (HABs) in marine and freshwater ecosystems. The papers discuss topics such as the discharge of nutrients into water systems, eutrophication, and the increase in frequency and severity of HABs worldwide. They also explore the diversity, growth, toxins, and toxicity of harmful algae, as well as mitigation strategies. The studies provide valuable insights into the impact of human activities on HAB-forming species and the need for further research and mitigation efforts. [Extracted from the article]

The phenomenon of algal bloom seriously affects the function of the aquatic ecosystems, damages the landscape of urban river and lakes, and threatens the safety of water use. The introduction of a multi-attribute decision-making method avoids the shortcomings of traditional algal bloom management that relies on manual experience. However, the weight-calculation part of this method still receives the artificial influence of human factors, which reduces the accuracy and scientific rigor of the decision. This paper presents a group decision-making method based on information self-learning which makes decision weights automatically clustered and assigned. A general framework of decision-making management is constructed for the algal bloom management process. In the decision-making process, an improved density-based clustering algorithm is used to automatically cluster and rank the decision data in the form of the three-parameter interval number, and ultimately obtain the optimal management method that meets the management objectives. Finally, the method was applied at the monitoring station of Sanjiadian Reservoir in Beijing, China. Based on the treatment objectives and water quality monitoring data of the station, relevant experts were invited to evaluate the management solutions, and the information self-organizing algorithm of this paper was used to automatically rank the decision-making methods, and finally obtain the most suitable management method for the station. Comparison with the water quality data and treatment inputs after the previous man-made selection of treatment options, and discussion among experts, show that the decision-making method is feasible and effective, and contributes to the sustainable treatment of algal blooms. [ABSTRACT FROM AUTHOR]

Harmful Algal and Cyanobacterial Bloom (HACB) threaten aquatic ecosystems, human health, and the economy. Many factors influence these dynamic events, which are often difficult to detect until the late stages of growth. The inclusion of an Early Warning System (EWS) can be instrumental in identifying hazards and preventing or at least minimizing their impact. Traditional monitoring approaches often fail to provide the real-time, high-resolution data needed for effective early warnings. The integration of Internet of Things (IoT) technologies offers a promising avenue to address these limitations by creating a network of interconnected sensors capable of continuously collecting and transmitting data from various aquatic environments. In this paper, we present DEVS-BLOOM-WebUI, an advanced web application that extends the capabilities of the DEVS-BLOOM framework, providing a user-friendly interface that supports different user roles. The application includes an interface to manage users and permissions, dashboards to inspect data (from sensors, Unmanned Surface Vehicles (USVs), weather stations, etc.), train AI models, explore their predictions, and facilitate decision-making through notification of early warnings. A key feature of DEVS-BLOOM-WebUI is the Scenario Configuration Editor (SCE). This interactive tool allows for users to design and configure the deployment of monitoring infrastructure within a water body, enhancing the system's adaptability to user-defined simulation scenarios. This paper also investigates the practical implementation of an IoT-based EWS, discussing design considerations, sensor technologies, and communication protocols essential for seamless data integration and effective operation of the EWS. [ABSTRACT FROM AUTHOR]

Biotoxins and harmful algal blooms (HABs) are damaging to aquaculture operations. Occurrences lead to disrupted operations, fish kills, and significant risks to human health. The conditions leading to blooms are driven by known, but complex processes. Heuristics exist about the drivers but the nonlinearity and opaqueness of relationships make it difficult to resolve using traditional rule-based mathematical models. An alternative approach leverages machine learning to uncover the conditions that lead to the closure of farms. This paper presents a comprehensive framework that combines semi-automated machine learning with ensemble classification approaches to predict site closures. Performance is evaluated on 7 years of site closure data from a shellfish farm in Southwest Portugal, together with publicly available environmental data. The model reports an accuracy of 83% across a challenging forecasting task. The proposed framework provides a pragmatic, scalable, site-specific decision tool to help aquaculture stakeholders mitigate the impacts of HABs. [ABSTRACT FROM AUTHOR]

The estimation of orchard blooming levels and the determination of peak blooming dates are very important because they determine the timing of orchard flower thinning and are essential for apple yield and quality. In this paper, we propose an orchard blooming level estimation method for global-level and block-level blooming level estimation of orchards. The method consists of a deep learning-based apple flower detector, a blooming level estimator, and a peak blooming day finding estimator. The YOLOv5s model is used as the apple flower detector, which is improved by adding a coordinate attention layer and a small object detection layer and by replacing the model neck with a bidirectional feature pyramid network (BiFPN) structure to improve the performance of the apple flower detector at different growth stages. The robustness of the apple flower detector under different light conditions and the generalization across years was tested using apple flower data collected in 2021–2022. The trained apple flower detector achieved a mean average precision of 77.5%. The blooming level estimator estimated the orchard blooming level based on the proportion of flowers detected at different growth stages. Statistical results show that the blooming level estimator follows the trend of orchard blooming levels. The peak blooming day finding estimator successfully positioned the peak blooming time and provided information for the flower thinning timing decision. The method described in this paper is able to provide orchardists with accurate information on apple flower growth status and is highly automated. [ABSTRACT FROM AUTHOR]

Frequent outbreaks of cyanobacterial blooms have become one of the most challenging water ecosystem issues and a critical concern in environmental protection. To overcome the poor stability of traditional detection algorithms, this paper proposes a method for detecting cyanobacterial blooms based on a deep-learning algorithm. An improved vegetation-index method based on a multispectral image taken by an Unmanned Aerial Vehicle (UAV) was adopted to extract inconspicuous spectral features of cyanobacterial blooms. To enhance the recognition accuracy of cyanobacterial blooms in complex scenes with noise such as reflections and shadows, an improved transformer model based on a feature-enhancement module and pixel-correction fusion was employed. The algorithm proposed in this paper was implemented in several rivers in China, achieving a detection accuracy of cyanobacterial blooms of more than 85%. The estimate of the proportion of the algae bloom contamination area and the severity of pollution were basically accurate. This paper can lay a foundation for ecological and environmental departments for the effective prevention and control of cyanobacterial blooms. [ABSTRACT FROM AUTHOR]

Oil spillages on a sea's or an ocean's surface are a threat to marine and coastal ecosystems. They are mainly caused by ship accidents, illegal discharge of oil from ships during cleaning and oil seepage from natural reservoirs. Synthetic-Aperture Radar (SAR) has proved to be a useful tool for analyzing oil spills, because it operates in all-day, all-weather conditions. An oil spill can typically be seen as a dark stretch in SAR images and can often be detected through visual inspection. The major challenge is to differentiate oil spills from look-alikes, i.e., low-wind areas, algae blooms and grease ice, etc., that have a dark signature similar to that of an oil spill. It has been noted over time that oil spill events in Pakistan's territorial waters often remain undetected until the oil reaches the coastal regions or it is located by concerned authorities during patrolling. A formal remote sensing-based operational framework for oil spills detection in Pakistan's Exclusive Economic Zone (EEZ) in the Arabian Sea is urgently needed. In this paper, we report the use of an encoder–decoder-based convolutional neural network trained on an annotated dataset comprising selected oil spill events verified by the European Maritime Safety Agency (EMSA). The dataset encompasses multiple classes, viz., sea surface, oil spill, look-alikes, ships and land. We processed Sentinel-1 acquisitions over the EEZ from January 2017 to December 2023, and we thereby prepared a repository of SAR images for the aforementioned duration. This repository contained images that had been vetted by SAR experts, to trace and confirm oil spills. We tested the repository using the trained model, and, to our surprise, we detected 92 previously unreported oil spill events within those seven years. In 2020, our model detected 26 oil spills in the EEZ, which corresponds to the highest number of spills detected in a single year; whereas in 2023, our model detected 10 oil spill events. In terms of the total surface area covered by the spills, the worst year was 2021, with a cumulative 395 sq. km covered in oil or an oil-like substance. On the whole, these are alarming figures. [ABSTRACT FROM AUTHOR]

This study used GOCI-II data to systematically evaluate the feasibility of Rayleigh-corrected reflectance (Rrc) to detect algal blooms in the complex optical environment of the East China Sea (ECS). Based on long-term in situ remote sensing reflectance (Rrs), Rrc spectra demonstrated the similar capability of reflecting the water condition under various atmospheric conditions, and the baseline indices (BLIs) derived from Rrc and Rrs showed good consistency (R2 > 0.98). The effectiveness of five Rrc-based BLIs (SS490, CI, DI, FLH, and MCI) for algal bloom detection was assessed, among which SS490 and MCI showed better performances. A synthetic bloom detection algorithm based on the BLIs of Rrc was then developed to avoid the impact of turbid water. The validation of the BLI algorithm was carried out based on the in situ algal abundance data from 2021 to 2023. Specifically, SS490 showed the best bloom detection result (F-measure coefficient, FM = 0.97), followed by MCI (FM = 0.88). Since the 709 nm bands used in MCI were missing in many ocean color satellites, the SS490 algorithm was more useful in application. Compared to Rrs based bloom detection algorithms, synthetical Rrc BLI proposed in this paper provides more effective observation results and even better algal bloom detection performance. In conclusion, the study confirmed the feasibility of utilizing Rrc for algal bloom detection in the coastal areas of the ECS, and recognized the satisfactory performance of synthetical SS490 by comparing with the other BLIs. [ABSTRACT FROM AUTHOR]

Reconstructing the field of currents using remote sensing methods is a traditional task of oceanology. Satellite instruments such as altimeters, Doppler radars, and optical sensors are routinely used to solve oceanological problems for waters with large dimensions (open areas of the seas and oceans). The latter work well for reservoirs with significant water temperature gradients when applying the method of processing successive satellite images with varying time delays. Less commonly, areas of intense phytoplankton blooms, which are usual for productive waters, are used as markers for image matching. Such waters can be monitored with satellite ocean color sensors that provide high spatial resolution. The goal of the present paper is to investigate the possibility of reconstructing the flow field in the Gorki Reservoir, as an example of a medium-sized eutrophic reservoir, from sequent images of two different high-resolution ocean color sensors with a short time delay between images. This paper describes the field experiment under the satellite overpasses and presents the results of applying the maximum correlation method to two satellite images for the retrieval of the current field in comparison with shipboard data. It is shown that the proposed method has prospects for development. [ABSTRACT FROM AUTHOR]

This comprehensive review explores the escalating challenge of nutrient enrichment in aquatic ecosystems, spotlighting the dire ecological threats posed by harmful algal blooms (HABs) and excessive particulate organic matter (POM). Investigating recent advancements in water treatment technologies and management strategies, the study emphasizes the critical need for a multifaceted approach that incorporates physical, chemical, and biological methods to effectively address these issues. By conducting detailed comparative analyses across diverse aquatic environments, it highlights the complexities of mitigating HABs and underscores the importance of environment-specific strategies. The paper advocates for sustainable, innovative solutions and international cooperation to enhance global water quality and ecosystem health. It calls for ongoing advancement, regular monitoring, and comprehensive research to adapt to emerging challenges, thus ensuring the preservation of aquatic biodiversity and the protection of communities reliant on these vital resources. The necessity of integrating technological innovation, ecological understanding, and global cooperation to safeguard aquatic ecosystems for future generations is paramount. [ABSTRACT FROM AUTHOR]

The Global Navigation Satellite Systems (GNSS), including the US's GPS, China's BDS, the European Union's Galileo, and Russia's GLONASS, offer real-time, all-weather, any-time, anywhere and high precision observations by transmitting L band signals continuously, which have been widely used for positioning, navigation and timing. With the development of GNSS technology, it has been found that GNSS-reflected signals can be used to detect Earth's surface characteristics together with other signals of opportunity. In this paper, the current status and latest advances are presented on Global Navigation Satellite System-Reflectometry (GNSS-R) in theory, methods, techniques and observations. New developments and progresses in GNSS-R instruments, theoretical modeling, and signal processing, ground and space-/air-borne experiments, parameters retrieval (e.g. wind speed, sea surface height, soil moisture, ice thickness), sea surface altimetry and applications in the atmosphere, oceans, land, vegetation, and cryosphere are given and reviewed in details. Meanwhile, the challenges in the GNSS-R development of each field are also given. Finally, the future applications and prospects of GNSS-R are discussed, including multi-GNSS reflectometry, new GNSS-R receivers, GNSS-R missions, and emerging applications, such as mesoscale ocean eddies, ocean phytoplankton blooms, microplastics detection, target recognition, river flow, desert studies, natural hazards and landslides monitoring. [ABSTRACT FROM AUTHOR]

Algal blooms caused by eutrophication are a major global problem, and the monitoring and prediction of algal densities in lakes are important indicators of eutrophication management. However, the reliability of the commonly used chlorophyll-a (Chl-a) to characterize phytoplankton density in lake environments needs to be further investigated. In this paper, we sampled and analyzed 365 samples from nine plateau lakes in Yunnan Province during the dry and rainy seasons. The Chl-a data measured by the laboratory spectrophotometric method and the portable YSI multi-parameter water quality meter (YSI) directly used in the field were compared, and regression analysis and correlation analysis with phytoplankton density were performed. Most of the Chl-a values measured by the laboratory instrument were greater than those measured by the YSI, and the correlation between the two methods was weak (0.492, p < 0.001). The correlation between Chl-a and phytoplankton density measured by the YSI reached 0.67 (p < 0.001) in the dry season, while the laboratory methods used to measure Chl-a to characterize phytoplankton density may have led to an overestimation of phytoplankton density due to nonspecific sources of Chl-a. However, both methods are relatively inaccurate for characterizing phytoplankton density. For different trophic states of lakes, nutrient concentration changes affect the Chl-a concentration of phytoplankton. During different seasons, changes in the fluorescence intensity of phytoplankton in response to environmental conditions prevent the YSI results from reflecting the authentic phytoplankton density. Furthermore, high species diversity can lead to inconsistent changes in Chl-a and phytoplankton because the content of Chl-a in individual cells of different phytoplankton is different. The relationship between Chl-a and phytoplankton density was species specific. Therefore, when applying Chl-a to characterize phytoplankton density in lakes, it is necessary to consider environmental conditions, phytoplankton community structure and other practical conditions. In addition, laboratory analytical methods and instrumental techniques and instruments need to be improved. [ABSTRACT FROM AUTHOR]

Phytoplankton plays an essential role in the biogeochemical cycle because it is at the top of the food chain and is a source of oxygen. Eutrophication causes coastal areas to deteriorate as industrialization accelerates, leading to harmful algal blooms (HABs), severely affecting human and ecological health. The frequency and extent of HAB events potentially may increase due to climate change. HAB outbreaks have led to substantial losses for major coastal economies globally, and therefore have emerged as a critical research focus in environmental sciences. However, the lack of an overview of diverse factors influencing HABs complicates the cause identification and the effective countermeasure development for HAB occurrence, thereby impeding the formulation of targeted strategies for prediction and mitigation. Therefore, this review summarizes the influential factors affecting HABs in coastal areas, including water quality factors (nutrients, salinity, stratification, and biological factors) and climatological factors (temperature, pH and pCO2 , and irradiance and light). Recent work with several harmful algae species suggested that warmer temperatures combined with nutrient variation, stronger stratification, and ocean acidification may increase the growth of some toxic dinoflagellate species. Although the effects of factors vary for different species and locations, the intensification of anthropogenic activities and climate change likely will increase the frequency, outbreak scale, and severity of most coastal HABs. Because predicting HABs is crucial for understanding the factors and synergy affecting their growth and minimizing losses for decision makers and stakeholders, we reviewed models for predicting HABs, including process-based models, traditional statistical-empirical models, and data-driven machine learning models. Predicting HABs becomes more challenging as the spatial distribution of harmful algae is influenced by future climate patterns. This review paper presents a comprehensive overview of the various factors impacting HABs in coastal areas, serving as a valuable resource for decision makers and researchers to design targeted research and mitigation strategies. [ABSTRACT FROM AUTHOR]

This paper concerns a discrete-time phytoplankton–zooplankton model in which the effects of toxin produced by phytoplankton and refuges provided for phytoplankton on the interactions between phytoplankton and zooplankton are considered. We first discuss the existence and stability of fixed points. When two parameters change, it is shown that there exist some codimension-two bifurcations, including fold-flip bifurcation and strong resonance bifurcations. Moreover, we give the corresponding bifurcation diagrams, phase diagrams and maximum Lyapunov exponent diagrams. The results show that phytoplankton toxin and refuges play important roles in the occurrence and termination of algal blooms in freshwater lakes. [ABSTRACT FROM AUTHOR]

Algal bloom has been a persistent problem for both fresh and marine water, with no exception for a coastal reservoir (CR). Among the algal bloom mitigations for a CR, shape optimisation to reduce algal bloom occurrence has been frequently mentioned. However, there was no literature found on the actual shape optimisation study or process for CR. Thus, this research was done to bridge this gap, particularly for the second-generation CR. Hydrodynamic model of MIKE 21 has been used, with secondary data obtained from published papers and Google Earth. The secondary data of critical velocity corresponding to algal growth were only available for cyanobacteria, chlorella, filamentous algae and phytoplankton. Hence, only these algae species were considered in the algal mapping. All models were simulated for eight idealised cases of second-generation CR at the Yangtze Estuary. These different geometric shapes were analysed and compared, considering several factors including the average velocity in the reservoir, presence of stagnant water, percentage of occurrence for each algae species and so on. From the results, the reservoir model with the shape of "shorter piano key" ranked the highest among all the shapes in terms of proneness to algal bloom, based on the flow velocity within the reservoir. From the findings, further shape optimisation was done on second-generation CRs. From shape optimisation process, the optimised shape of the "little dinosaur" and "little pencil" showed excellent reduction in algal blooming. However, "little dinosaur" was preferred as its location for algal bloom is small and controllable due to the presence of "piano key" structure. Lastly, all the findings were applied to an existing CR at Qingcaosha to see if shape optimisation based on the analysis can reduce areas prone to algal blooming. The optimised model of Qingcaosha showed great reduction on area prone to algal blooming compared to its original shape but the addition of "piano key" structure did not have significant impact on the reduction of algal bloom occurrence since the shape of Qingcaosha is highly dependent on its natural topography. From the study, it was concluded that shape optimisation for topographic-dependent CR should be done on case-by-case basis, following the flow direction in the reservoir. As for second-generation CR without topographical constraints, the shape optimisation can be done by placing inlet perpendicular to the flow direction, minimising corners, implementing piano-key-like structure, optimising shape based on flow direction and refer "little dinosaur" or "little pencil" for the overall shape optimisation design. [ABSTRACT FROM AUTHOR]

"Red tide" is the popular name for a harmful algal bloom that occurs frequently in Florida waters and has significant impacts on the environment, the economy, and human and animal health. This paper addresses the limited understanding of public attitudes surrounding red tide and the potential for message framing to increase support for mitigation action. A sample of Florida residents (n = 498) was randomly shown a digital article framed around different red tide impacts (economic loss, human health risks, ecosystem damage, or harm to charismatic species) or a control article not framed around a specific red tide impact. Participants were then queried about their emotional responses, support for red tide mitigation policies, and intentions to change their behavior to mitigate impacts. Participants reported higher levels of negative emotions after viewing the harm to charismatic megafauna framing, indicating that messaging may play a significant role in eliciting environmental emotions. Message frames did not significantly impact other policy attitudes. Results demonstrate barriers to shifting support for mitigation where public support for action is already high. [ABSTRACT FROM AUTHOR]

Water exchange in lake basins is a very important process in regulating the health of the aquatic environment, e.g., by shaping algal blooms. Thus, knowledge of the process is also required to develop management strategies. The paper presents a dynamic of water renewal time in the Uściwierz chain of lakes, in which the natural hydrological connectivity of the catchment areas has been altered due to human impact. Calculations of water renewal were limited to the part of the lake basin corresponding to the active (dynamic) retention layer. A comparative analysis of the rate of potential water renewal, based on the structure difference index, was used as an indicator of the degree of anthropogenic transformation of water distribution in the lake catchments. The smallest differences in the structure of the water renewal rate between the neighboring lakes in the chain system were observed in the cold period, and the largest differences were observed in the warm period. The results showed that the shorter the timescale (5-day period), the higher the similarity in the structure of the water renewal rate between the lakes. Very large differences between the structure of the potential water renewal rate in Lakes Uściwierz and Bikcze indicated a significant transformation of the water cycle down the lake chain. The water renewal rate proved to be a good indicator of the degree of anthropogenic transformation in the catchments located in close proximity. [ABSTRACT FROM AUTHOR]

The occurrence of harmful algal blooms (HABs) in coastal and inland waters has a significant impact on societies. This complex biogeophysical phenomenon becomes further complicated due to the impact of climate change. This review summarizes the research performed in recent years in the direction of climate change on three lake parameters, viz. lake temperature, precipitation, runoff, and lake ice, which impacts the lake ecology and, in turn, impacts the HABs. The present paper also reviews the research work related to the relationship between climate change and HABs. The purpose of this study is to provide the researchers with the opportunity to understand the current research in the direction of climate change and HABs so they can contribute effectively to one of the most important phenomena that will severely impact water quality in the future warmer climate, in coastal as well as inland water bodies. Furthermore, this work aims to discuss how HABs will change in the future warmer climate. [ABSTRACT FROM AUTHOR]

Management of water resources in the Murray-Darling Basin has historically focussed on water security and the allocation of water for users with competing needs. This focus was reflected in the seminal paper on multiple risks to shared water across the basin by the Commonwealth Scientific and Industrial Research Organisation 15 years ago. That paper captured key concerns that were at the forefront for decision-makers, managers and policy-makers who were, at that time, experiencing the early impacts of the Millennium Drought. Water quality, then, was secondary to the issues of water security. Across the following years, new water quality risks have emerged along with a more nuanced understanding of the complex interplay between climate, floodplain/catchment vegetation, hydrology, and water quality. Critically, this improved understanding applies to the systemic shocks of extreme events, such as the 2020 bushfires and hypoxic blackwater events, as well as the variability, duration and volumes of natural and regulated river flows. In this paper, we explore the key water quality issues that currently face the Basin, and reframe water quality as an integral rather than incidental component of the risks to shared water in the Basin, with the associated implications for policy development that this implies. [ABSTRACT FROM AUTHOR]

Globally, observations on marine species during marine heatwaves (MHWs) help outline the scope of the MHW's possible biological effects. In line with this effort, this paper presents a 2020 MHW that coincided with a reported "tomato jellyfish" (Crambione mastigophora Maas, 1903) bloom on 23 March 2020 in the Corong-Corong Bay of Palawan, Philippines. Detecting a moderate MHW from 21 March to 04 April 2020, the analysis of sea surface temperatures revealed that most areas surrounding the bloom site attained their peak positive anomalies on the same day as the reported bloom. Certain physical mechanisms present in the first quarter of 2020 may have played a role in the occurrence of both events: the presence of cyclonic eddies and parallel monsoonal winds alongshore can induce upwelling which promotes biological productivity in surface waters, while the observed weakening of winds have been associated with anomalous warming of the sea surface. Further studies are still highly recommended to determine the exact causes of the jellyfish bloom and what conditions make it more likely to happen during MHWs. However, if the C. mastigophora is hypothetically able to continually bloom amidst warming temperatures, the increasing trend of MHW frequency and intensity in the West Philippine Sea (where the reported bloom site is situated) may consequently yield more future co-occurrences. This paper aims to hopefully contribute to the existing knowledge of possible biological impacts associated with extreme marine events, especially in the Philippine context where both jellyfish blooms and MHWs are understudied. [ABSTRACT FROM AUTHOR]

The Sulejów reservoir is one of the largest reservoirs in Poland and is exposed to a large flux of nutrients from both point and diffuse sources, which leads to an excessive amount of eutrophication and cyanobacteria bloom. The underlying inspiration for this paper was to use a 1D HEC-RAS hydrodynamic model to improve the knowledge of sedimentation conditions and the chemistry of bottom sediments in the context of reservoir eutrophication and algae bloom. Field sampling was performed, and chemical concentrations of Total Organic Carbon, Total Phosphorus, and Cadmium were measured in samples from bottom sediments. The deepest parts of the reservoir and the presence of sediment traps coincide with the highest concentrations of organic carbon, nutrients, and heavy metals. The paper has shown that reservoir hydrodynamic modelling and precise bathymetry maps provide very valuable information that can be used for the interpretation of bottom sediment chemistry patterns and for understanding the conditions of sedimentation. [ABSTRACT FROM AUTHOR]

Using a three-dimensional coupled physical–biological model, this paper explores the effect that short-lived wind events lasting a few days in duration have on the creation of phytoplankton blooms in island wakes. Findings show that wind-induced coastal upwelling creates initial nutrient enrichment and phytoplankton growth near the island, whereas an oscillating flow, typical of island wakes, expels patches of upwelled water, including its nutrient and phytoplankton loads, into the ambient ocean. Dependent on the wind direction, a short-lived wind event can create one or more plankton patches with diameters of the order of the island diameter. Phytoplankton continues to grow within floating patches, each forming an individual marine ecosystem. While the ecological features of island wakes are well documented, this study is the first that describes the significance of short-lived, transient wind-driven upwelling in the process. [ABSTRACT FROM AUTHOR]

Harmful algae and cyanobacteria blooms are increasing in frequency and intensity in freshwater systems due to anthropogenic impacts such as nutrient loading in watersheds and engineered alterations of natural waterways. There are multiple physical factors that affect the conditions in a freshwater system that contribute to optimal habitats for harmful algae and toxin-producing cyanobacteria. A growing body of research shows that climate change stressors also are impacting water-body conditions that favor harmful algae and cyanobacteria species over other phytoplankton. The overgrowth of these organisms, or a "bloom," increases the opportunity for exposure to toxins by humans, companion animals, livestock, and wildlife. As waters warm and precipitation patterns change over time, exposure to these blooms is projected to increase. Hence, it is important that states and tribes develop monitoring and reporting strategies as well as align governmental policies to protect their citizens and ecosystems within their jurisdiction. Currently, the policies and approaches taken to monitor and report on harmful algae and cyanobacteria blooms vary widely among states, and it is undetermined if any tribes have specific policies on harmful algae blooms. This paper synthesizes research on algal blooms in inland freshwater systems of the United States. This review examines how climate change contributes to trends in bloom frequency or severity and outlines approaches that states and tribes may use to monitor, report, and respond to harmful algae and cyanobacteria blooms. Significance Statement: Inland bodies of freshwater supply drinking water for humans and animals, water for irrigating crops, habitats for aquatic species, places of cultural significance for Indigenous peoples, and other important functions. Many of these bodies of water have been polluted with runoff from industry, including agriculture, and already support harmful algal blooms during warm conditions. Hot extremes associated with climate change are expected to increase the occurrence and duration of harmful algal blooms, and in some places, initiate blooms where none have been recorded previously. These toxic blooms are harmful to people, companion animals, livestock, and wildlife. It is important to review the interconnections among biological, climate, and water systems to monitor blooms and alert the public about their toxin production. [ABSTRACT FROM AUTHOR]

Unsaturated diacylglycerols are a class of antioxidant compounds with the potential to positively impact human health. Their ability to combat oxidative stress through radical scavenger activity underscores their significance in the context of preventive and therapeutic strategies. In this paper we highlight the role of Anabaena flos-aquae as a producer of unsaturated mono and diacylglycerols, and then demonstrate the antioxidant activity of its methanolic extract, which has as its main components a variety of acylglycerol analogues. This finding was revealed using a sustainable strategy in which the One Strain Many Compounds (OSMAC) cultivation in microscale was coupled with a bioinformatic approach to analyze a large dataset of mass spectrometry data using the molecular networking analyses. This strategy reduces time and costs, avoiding long and expensive steps of purification and obtaining informative data on the metabolic composition of the extracts. This study highlights the role of Anabaena as a sustainable and green source of novel bioactive compounds. [ABSTRACT FROM AUTHOR]

Populations are generally censused daily, weekly, monthly or annually. In this paper, we introduce a discrete-time nutrients-phytoplankton-oysters (NPO) model that describes the interactions of nutrients, phytoplankton and oysters in a bay ecosystem. We compute the threshold parameter $ \mathcal {R}_N $ R N for persistence of phytoplankton with or without oysters. When $ \mathcal {R}_{N} \lt 1 $ R N < 1 , then both phytoplankton and oysters populations go extinct. However, when $ \mathcal {R}_N \gt 1 $ R N > 1 , we show that the model may exhibit two scenarios: (1) a locally asymptotically stable equilibrium with positive values of nutrients and phytoplankton with oysters missing, and (2) a locally asymptotically stable interior equilibrium with positive values of nutrients, phytoplankton and oysters. We use sensitivity analysis to study the impact of human and environmental factors on the model. We use examples to illustrate that some human activities and environmental factors can force the interior equilibrium to undergo a Neimark–Sacker bifurcation which generates phytoplankton blooms with oscillations in oysters population and nutrients level. [ABSTRACT FROM AUTHOR]

Lake Diefenbaker Irrigation Canals in Canada are crucial in providing water for irrigation, preventing droughts and floods, and supporting the Saskatchewan agriculture industry and economy. Unfortunately, filamentous algal blooms occur every summer in Lake Diefenbaker Irrigation Canals. These algae are not toxic but a nuisance. They block farmers' pumps and reduce irrigation water flow rates. Currently, the Water Security Agency periodically adds the algaecide Magnacide H. to control the algal blooms, which is costly (i.e., one million dollars per year for the Lake Diefenbaker M1 Irrigation Canal only) and requires effort to dewater the canal to protect fish. Therefore, algae removal before the canal water enters farmer's pumps might be a cost-effective alternative, especially the removal of microalgae during the initial stages of growth in June of each year. This paper has summarized and evaluated algae removal technologies, considering their advantages, disadvantages, and potential solutions for addressing the challenges and limitations associated with these technologies. Five algae removal technologies were identified as promising, which are suspended air flotation (SAF), dissolved air flotation (DAF), hydrodynamic cavitation, spiral blade centrifuge, and coagulation. Among them, SAF seems the most suitable option, while DAF and hydrodynamic cavitation offer eco-friendly advantages. Further research and pilot testing are needed to determine the costeffective and feasible algae removal technology for Lake Diefenbaker Irrigation Canals. [ABSTRACT FROM AUTHOR]

Blooms of various types of seaweeds have been reported worldwide, with recent expansions in surface waters. While most of the expansions have been attributed to eutrophication due mainly to human activities, any potential role of climate change is unclear. Here we show that, in the East China Sea and Yellow Sea, increased biomass of Sargassum horneri (S. horneri, brown seaweed) from 2000 to 2021 appears to be caused primarily by ocean warming, as S. horneri prefers a certain temperature range to grow. In contrast, while increases of Ulva prolifera (U. prolifera, green seaweed) in the same regions might also be related to ocean warming, during the same period, human activities such as coastal aquaculture or seaweed mitigation may muddle such effects. With the projected ocean warming in the next decades, we hypothesize that S. horneri blooms may occur earlier during the year and may continue to expand in the future. Plain Language Summary: Seaweed macroalgae blooms have been reported around the world in the last two decades, yet the exact reasons are often unclear. This paper attempts to solve this puzzle for the Sargassum and Ulva seaweeds in the East China Sea and Yellow Sea using long‐term observations and laboratory‐based seaweed physiology measurements. The paper shows not only how seaweeds have expanded in the two marginal seas in the past four decades, but also how a warming ocean (due to climate variability) and nutrient enrichment (due mainly to human activities) controlled such expansions. Among 63 large marine ecosystems (LMEs) in the world, the East China Sea (where seaweeds expanded) is one of the three LMEs that experienced "super‐fast" warming. Given the IPCC‐projected seawater temperature rise of 1.6°C by 2050, will these seaweeds continue to expand? Key Points: Multi‐sensor satellite data show significant and near‐synchronized expansions of Sargassum horneri and Ulva prolifera in the past 38 yearsOcean warming appears to be a main factor behind the recent expansions of S. horneri because of its physiological requirementOcean warming may also play a role in U. prolifera expansions, but the effect appears confounded by human mitigation efforts [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) pose a significant threat to aquatic ecosystems and human health due to the production of toxins. The identification and quantification of these toxins are crucial for water quality management decisions. This study used DNA analysis (PCR techniques) to identify toxin-producing strains and liquid-chromatography-tandem mass spectrometry (LC-MS/MS) to quantify microcystins in samples from Mindu and Nyumba ya Mungu Dams in Tanzania. The results showed that HABs were detected in both dams. The BLAST results revealed that the 16S gene sequences of uncultured samples were very similar to an Antarctic cyanobacterium, Leptolyngbya sp, Anabaena sp, and Microcystis aeruginosa. Sequences of the cultured samples were most similar to Nodularia spumigena, Amazoninema brasiliense, Anabaena sp, and Microcystis aeruginosa. Further analyses showed that the nucleotide sequence similarity of uncultured isolates from this study and those from the GenBank ranged from 85 to 100%. For cultured isolates from this study and others from the GenBank, nucleotide identity ranged from 81 to 100%. The molecular identification of Microcystis aeruginosa confirmed the presence of HABs in both Mindu and Nyumba ya Mungu Dams in Tanzania. At Mindu Dam, the mean concentrations (± standard deviation) of microcystin-LR, -RR, and -YR were 1.08 ± 0.749 ppm, 0.120 ± 0.0211 ppm, and 1.37 ± 0.862 ppm, respectively. Similarly, at Nyumba ya Mungu Dam, the concentrations of microcystin-LR, -RR, and -YR were 1.07 ± 0.499 ppm, 0.124 ± 0.0224 ppm, and 0.961 ± 0.408 ppm, respectively. This paper represents the first application of PCR and LC-MS/MS to study microcystins in small freshwater reservoirs in Tanzania. This study confirms the presence of toxin-producing strains of Microcystis aeruginosa in both dams and also provides evidence of the occurrence of microcystins from these strains. These findings contribute in improving the monitoring of HABs contamination and their potential impact on water quality in Tanzanian reservoirs. [ABSTRACT FROM AUTHOR]

Harmful algal and cyanobacterial blooms (HABs), occurring in inland and maritime waters, pose threats to natural environments by producing toxins that affect human and animal health. In the past, HABs have been assessed mainly by the manual collection and subsequent analysis of water samples and occasionally by automatic instruments that acquire information from fixed locations. These procedures do not provide data with the desirable spatial and temporal resolution to anticipate the formation of HABs. Hence, new tools and technologies are needed to efficiently detect, characterize and respond to HABs that threaten water quality. It is essential nowadays when the world's water supply is under tremendous pressure because of climate change, overexploitation, and pollution. This paper introduces Discrete Event System Specification-BLOOM, a novel framework for real-time monitoring and management of HABs. Its purpose is to support high-performance hazard detection with model-based system engineering and cyber-physical systems infrastructure for dynamic environments. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real‐time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll‐a concentrations (chl‐a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real‐time monitoring of HABs. Landsat‐8 and Sentinel‐2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl‐a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R2 values of 0.75, 0.82, and 0.79 for chl‐a, turbidity, and phycocyanin, while multiple regression had R2 values of 0.29, 0.51, and 0.46 and SVR had R2 values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open‐source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality. [ABSTRACT FROM AUTHOR]

Vibrio vulnificus (Vv) and Vibrio parahaemolyticus (Vp) are water- and foodborne bacteria that can cause several distinct human diseases, collectively called vibriosis. The success of oyster aquaculture is negatively impacted by high Vibrio abundances. Myriad environmental factors affect the distribution of pathogenic Vibrio, including temperature, salinity, eutrophication, extreme weather events, and plankton loads, including harmful algal blooms. In this paper, we synthesize the current understanding of ecological drivers of Vv and Vp and provide a summary of various tools used to enumerate Vv and Vp in a variety of environments and environmental samples. We also highlight the limitations and benefits of each of the measurement tools and propose example alternative tools for more specific enumeration of pathogenic Vv and Vp. Improvement of molecular methods can tighten better predictive models that are potentially important for mitigation in more controlled environments such as aquaculture. [ABSTRACT FROM AUTHOR]

Aquaculture is an industry that has developed rapidly over the past decades. Despite several hazards in the operations, emergency preparedness is not at the same level as in the rest of the maritime industry. This paper highlights some possibilities to increase the aquaculture industry’s coastal emergency preparedness. This paper is the result of the innovation project “Coastal Emergency Preparedness” funded by the Norwegian Research Council and industry partners. The aquaculture industry must establish its own emergency preparedness. In this paper, the innovation of a fleet of emergency preparedness vessels along the coastline, which could fill the gaps in emergency preparedness, is presented. The vessels would be of varied sizes, with different equipment and response times, and could assist the aquaculture industry during local incidents or large‐scale ones, such as algae blooms or winter storms, that affect many sites at the same time. Each production zone would need its own dedicated fleet due to biosecurity regulations. The emergency preparedness vessel fleet would be led by an on‐scene commander. The fleet would deal with oil spills and tasks such as emergency towing, firefighting, rescue of people, recapturing of fish, silage making, algae detection, and diving missions. With such a vessel fleet, small and large aquaculture companies could increase their emergency preparedness with a common strategy and shared resources. [ABSTRACT FROM AUTHOR]

The majestic River Ganga is a sacred environment which nurtures more than 650 million people in her large watershed. The Ganga has proved resilient despite the multiple, enormous, environmental stressors placed on her. The Laurentian Great Lakes have also faced severe environmental degradation and the lessons learned there over the past 50 years can provide guidance for the remediation and restoration of the Ganga. One of the more important lessons is defining Beneficial Use Impairments to focus remediation efforts in degraded Areas of Concern. This paper provides a case study of one such impairment, Eutrophication or Undesirable Algae, and shows how it can be applied as part of a broader Ecosystem Approach towards the identification and selection of Ganga Areas of Concern. The 10 proposed Ganga Areas of Concern are intended to provide guidance to all stakeholders on how and where to focus remediation efforts on the Ganga, and similar ecosystems throughout the world. [ABSTRACT FROM AUTHOR]

With the acceleration of industrialization and urbanization, most lakes and reservoirs have been in eutrophication state. Eutrophication of water body will produce a series of environmental problems, among which cyanobacteria bloom is one of the most studied and seriously polluted problems. It is of great significance to effectively control the occurrence of cyanobacteria blooms by predicting and simulating the outbreak process of cyanobacteria blooms and accurately forecasting the relevant governance departments. However, there are two problems in the existing analysis of algal blooms: on the one hand, it is difficult to consider the impact of other factors on cyanobacteria blooms by taking chlorophyll concentration as the main influencing factor, and it is also unable to determine the relationship between various factors. On the other hand, only based on the field monitoring data research, lack of comprehensive analysis of the whole water area. The remote sensing image can reflect the change of the whole water area, but the traditional analysis method is difficult to deal with the massive remote sensing data effectively. In this study, eutrophication level was used as characterization index of cyanobacteria bloom, and the remote sensing image and its inversion map were taken as the main research data, and a new method of cyanobacteria bloom prediction based on four-dimensional (4D) fractal CNN was proposed. The prediction model uses 4D fractal CNN to extract the features of multi factor remote sensing images, capture the temporal and spatial characteristics and the interaction between multiple factors, and predict the eutrophication level of water body. In this study, a total of 216 remote sensing images of Taihu Lake Basin were selected from 29 groups with fine weather from 2009 to 2010 obtained by MODIS satellite. The simulation results show that the method proposed in this paper has excellent prediction performance, and the accuracy rate of 85.71% is better than that of common 3D CNN and 4D CNN models. [ABSTRACT FROM AUTHOR]

Humans have always lived with and around algae. At times, algae enable life, and at others, render life difficult. This article examines two sites suffering from atypical—and potentially harmful—algae blooms: Lake Erie in Ohio (USA) and the Riviera Maya (Mexico). Referring to ethnographic fieldwork, as well as to newspaper articles, policy papers, and online fora, we demonstrate how the narratives around algae have changed over time and shed light on how changes in these narratives opened the discussion of wetland repair and coastal integrity. We argue that conceptualizing algae as the "unwanted" unifies people, brings them together, and makes the treatment of lake eutrophication and coastal protection actionable. [ABSTRACT FROM AUTHOR]

Phosphorous is considered as an essential nutrient for life. Its availability in the water dictates the primary productivity, including macroalgae. In this paper, peer-reviewed articles reporting the effects of phosphorous on macroalgae for the past decades and up to the present were reviewed and recapitulated. The literature revealed that while phosphorous is one of the limiting nutrients in an open ocean, eutrophication in some coastal areas, which is fueled by anthropogenic activities, contributes to the excess phosphorous resulting in the occurrence of green tides. The general influences of phosphorous availability to many macroalgae were enhanced growth and biomass, especially with the interaction effect with nitrogen. However, some studies reported that the high concentration of phosphorous has deleterious effects on macroalgae. Hence, future studies are needed to fully understand the role of phosphorous availability in macroalgae. [ABSTRACT FROM AUTHOR]

The biogeochemistry of waters is an essential regulator of phytoplankton dynamics, determining the level of species bloom and the change in dominants. This paper investigated the seasonal dynamics of phytoplankton and the nutrient concentrations and their ratios in the northeastern Black Sea in 2017–2021. Two taxonomic groups, diatoms and coccolithophores, determine the seasonal dynamics and significantly contribute to the total phytoplankton biomass. Coccolithophores formed blooms in early June annually, except in 2020. Large diatoms dominated in summer with a biomass exceeding 1000 mg m−3 annually, except in 2019. During the blooms of these taxonomic groups, their contribution to the total phytoplankton biomass exceeded 90%. Each group has characteristic biogeochemical niches in the nitrogen and phosphorus concentration coordinates. The position of the seasonal thermocline regulates the biogeochemistry of the water. With a high-lying and sharp gradient thermocline (the average for five years is 6.87 m), low nitrogen concentrations and a nitrogen-to-phosphorus ratio below the Redfield ratio are created in the upper mixed layer. These conditions are optimal for the dominance of coccolithophores. When the thermocline is deepened (the average for five years is 17.96 m), the phosphorus concentration decreases significantly and the ratio of nitrogen to phosphorus is significantly higher than the Redfield ratio, and these conditions lead to the dominance of large diatoms. The results of experimental studies with nitrogen and phosphorus additives in the natural phytoplankton population confirm the above statements. The addition of phosphorus leads to the increased role of coccolithophores in the total phytoplankton biomass, the addition of nitrogen alone contributes to the growth of large diatoms, and the combined addition of phosphorus and nitrogen in a ratio close to the Redfield ratio leads to the dominance of small diatoms. [ABSTRACT FROM AUTHOR]

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Phytoplanktons are drifting plants in an aquatic system. They provide food for marine animals and are compared to terrestrial plants in that having chlorophyll and carrying out photosynthesis. Zooplanktons are drifting animals found inside the aquatic bodies. For stable aquatic ecosystem, the growth of both Zooplankton and Phytoplankton should be in steady state but in previous eras, there has been a universal explosion in destructive Plankton or algal blooms. Many investigators used various mathematical methodologies to try to explain the bloom phenomenon. So, in this paper, a discretized two-dimensional Phytoplankton–Zooplankton model is investigated. The results for the existence and uniqueness, and conditions for local stability with topological classifications of the equilibrium solutions are determined. It is also exhibited that at trivial and semitrivial equilibrium solutions, discrete model does not undergo flip bifurcation, but it undergoes Neimark–Sacker bifurcation at interior equilibrium solution under certain conditions. Further, state feedback method is deployed to control the chaos in the under consideration system. The extensive numerical simulations are provided to demonstrate theoretical results. [ABSTRACT FROM AUTHOR]

Https://www.epa.gov/cyanohabs This site from the U.S. Environmental Protection Agency deals with cyanobacterial algal blooms, the toxic products made, monitoring efforts and research into the topic. Climate change and algal blooms https://pubs.acs.org/doi/10.1021/acs.est.7b01498 This paper presents a modeling framework that predicts the effect of climate change on cyanobacterial blooms in water bodies in and surrounding the United States. Blooms: Tastes and odors https://www.usgs.gov/centers/kansas-water-science-center/science/cyanobacterial-blue-green-algal-blooms-tastes-odors-and This site deals with some of the chemicals involved in toxic algal blooms and gives information about specific geographic locations that have been studied. [Extracted from the article]

As freshwater harmful algal blooms continue to rise in frequency and severity, increasing focus is made on the effects of mixed pollutants and the dominant cyanobacterial species Microcystis aeruginosa (M. aeruginosa). However, few studies have investigated whether M. aeruginosa has a synergistic relationship with two common pollutants, namely, organophosphate flame retardants (OPFRs) and fluoroquinolone antibiotics (FQs). In this paper, three FQs and three OPFRs commonly detected in freshwaters were selected to construct a ternary mixture of FQs, a ternary mixture of OPFRs, and a six-component mixture of OPFRs and FQs. The effects of single substance and mixture on the growth of M. aeruginosa were determined at 24, 48, 72, and 96 h, and the toxicities of the mixture were evaluated by concentration addition model and independent action model. The results showed that the mixture of FQs and the mixture of OPFRs do not show toxicological interaction. However, partial mixtures of OPFRs and FQs showed antagonism or synergism at different concentrations and times. This indicated that combined toxicities of OPFRs and FQs on M. aeruginosa were mixture ratio dependent, concentration dependent and time dependent. This study improves our understanding of the role of OPFRs and FQs in cyanobacterial outbreaks of Microcystis. [ABSTRACT FROM AUTHOR]

An assessment framework for Tampa Bay Water's Hydrobiological Monitoring Program (HBMP) has been established based on the relationship between freshwater flow and primary environmental indicators monitored under the HBMP. The underlying paradigm is based on the understanding that reduced flows can result in water quality conditions adverse to biological populations if these conditions exceed a specific magnitude and/or are beyond a certain duration. HBMP water quality parameters identified as primary indicators include salinity (due to osmotic pressure controlling distribution of fish, benthos, and vegetation among other ecological effects), dissolved oxygen (due to the aerobic stress to fish and benthos that can occur due to depressed dissolved oxygen concentrations), and chlorophyll-a (due to excessive phytoplankton blooms that may increase biological oxygen demand and can result in depressed dissolved oxygen concentrations). These primary indicators were identified because they specifically relate to linkages in the HBMP conceptual model as well as State of Florida water quality standards and a great deal of effort has been allocated to understanding these relationships. To this end, special studies have been implemented to further scientific information related to the effects of flows and withdrawals on the magnitude, duration, and distribution of phytoplankton as one aspect of the larger HBMP assessment framework. In this paper, we provide a summary of recent special studies completed in the lower Alafia River, focused on in situ fluorometer chlorophyll-a measurement, interpretation, and predictive capability. We share lessons learned and our steps for moving forward in efforts to relate flow (and withdrawal-related effects) on phytoplankton in the lower Alafia River. [ABSTRACT FROM AUTHOR]