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Abstract Climate change is leading to an increase in severity, frequency, and distribution of harmful algal blooms across the globe. For many harmful algae species in eutrophic lakes, the formation of such blooms is controlled by three factors: the lake hydrodynamics, the vertical motility of the algae organisms, and the ability of the organisms to form colonies. Here, using the common cyanobacterium Microcystis aeruginosa as an example, we develop a model that accounts for both vertical transport and colony dynamics. At the core of this treatment is a model for aggregation. For this, we used Smoluchowski dynamics containing parameters related to Brownian motion, turbulent shear, differential setting, and cell‐to‐cell adhesion. To arrive at a complete description of bloom formation, we place the Smoluchowski treatment as a reaction term in a set of one‐dimensional advection‐diffusion equations, which account for the vertical motion of the algal cells through molecular and turbulent diffusion and self‐regulating buoyant motion. Results indicate that Smoluchowski aggregation qualitatively describes the colony dynamics of M. aeruginosa. Further, the model demonstrates wind‐induced mixing is the dominant aggregation process, and the rate of aggregation is inversely proportional to algal concentration. Because blooms of Microcystis typically consist of large colonies, both of these findings have direct consequences to harmful algal bloom formation. While the theoretical framework outlined in this manuscript was derived for M. aeruginosa, both motility and colony formation are common among bloom‐forming algae. As such, this coupling of vertical transport and colony dynamics is a useful step for improving forecasts of surface harmful algal blooms.

Myriophyllum aquaticum has shown potential allelopathic effects for the biocontrol of cyanobacteria and cyanotoxins. However, the composition of allelochemicals and their biological effects may be influenced by seasonal changes. In this study, we investigated the impact of aqueous extracts of M. aquaticum collected in different seasons on the growth of Microcystis aeruginosa and the concentration of microcystin-LR. Plant samples were extracted using ultrasound cycles in aqueous solutions, and extracts at varying concentrations (0.1, 10, and 100 mg/L) and a control treatment were inoculated with M. aeruginosa, and cell growth was analyzed using a Neubauer chamber. Photosynthetic pigment quantification was used to measure physiological effects and liquid chromatography was used to evaluate the microcystin-LR concentrations. The extracts of plants collected during autumn and winter exhibited higher inhibition of M. aeruginosa growth and a reduction in photosynthetic pigments compared to those collected during spring and summer. These results can be explained by the higher presence of phenolic compounds in the composition of extracts from autumn and winter. Microcystin-LR concentrations were decreased at 10 and 100 mg/L, with the highest efficiency observed in autumn, while spring showed lower efficiency. Our findings suggest that M. aquaticum extracts have inhibitory potential on M. aeruginosa, particularly during the autumn season, making them a promising nature-based solution for the biocontrol of harmful algal blooms.

Efforts to identify in situ the mechanisms underpinning the response of harmful algae to climate change demand frequent observations in dynamic and often difficult to access marine and freshwater environments. Increasingly, resource managers and researchers are looking to fill this data gap using unmanned systems. In this study we integrated the Environmental Sample Processor (ESP) into an autonomous platform to provide near real-time surveillance of harmful algae and the toxin domoic acid on the Washington State continental shelf over a three-year period (2016–2018). The ESP mooring design accommodated the necessary subsystems to sustain ESP operations, supporting deployment durations of up to 7.5 weeks. The combination of ESP observations and a suite of contextual measurements from the ESP mooring and a nearby surface buoy permitted an investigation into toxic Pseudo-nitzschia spp. bloom dynamics. Preliminary findings suggest a connection between bloom formation and nutrient availability that is modulated by wind-forced coastal-trapped waves. In addition, high concentrations of Pseudo-nitzschia spp. and elevated levels of domoic acid observed at the ESP mooring location were not necessarily associated with the advection of water from known bloom initiation sites. Such insights, made possible by this autonomous technology, enable the formulation of testable hypotheses on climate-driven changes in HAB dynamics that can be investigated during future deployments.

Eutrophic estuaries have suffered from a proliferation of harmful algal blooms (HABs) and acceleration of ocean acidification (OA) over the past few decades. Despite laboratory experiments indicating pH effects on algal growth, little is understood about how acidification affects HABs in estuaries that typically feature strong horizontal and vertical gradients in pH and other carbonate chemistry parameters. Here, coupled hydrodynamic–carbonate chemistry–HAB models were developed to gain a better understanding of OA effects on a high biomass HAB in a eutrophic estuary and to project how the global anthropogenic CO2 increase might affect these HABs in the future climate. Prorocentrum minimum in Chesapeake bay, USA, one of the most common HAB species in estuarine waters, was used as an example for studying the OA effects on HABs. Laboratory data on P. minimum grown under different pH conditions were applied in the development of an empirical formula relating growth rate to pH. Hindcast simulation using the coupled hydrodynamic-carbonate chemistry–HAB models showed that the P. minimum blooms were enhanced in the upper bay where pH was low. On the other hand, pH effects on P. minimum growth in the mid and lower bay with higher pH were minimal, but model simulations show surface seaward estuarine flow exported the higher biomass in the upper bay downstream. Future model projections with higher atmospheric pCO2 show that the bay-wide averaged P. minimum concentration during the bloom periods increases by 2.9% in 2050 and 6.2% in 2100 as pH decreases and 0.2 or 0.4, respectively. Overall the model results suggest OA will cause a moderate amplification of P. minimum blooms in Chesapeake bay. The coupled modeling framework developed here can be applied to study the effects of OA on other HAB species in estuarine and coastal environments.

An unprecedented large-scale outbreak of harmful algae, including Karenia selliformis and Karenia mikimotoi, was reported in mid-September 2021 in the northwest Pacific Ocean off southeastern Hokkaido, Japan. It inflicted catastrophic damage on coastal fisheries in the ensuing months. To understand the spatiotemporal distribution of Karenia spp. abundance, we conducted extensive ship-based surveys across several water masses during 4–14 October, 2021 and analyzed in-situ data in combination with Sentinel-3-derived ocean color imagery with a horizontal resolution of 300 m. High chlorophyll-a concentrations (exceeding 10 mg m–3) were identified mainly in coastal shelf–slope waters of 103 cells mL–1) of Karenia spp. on the shelf were characterized by submesoscale (i.e., 1–10 km) patch- or streak-like distributions, or both. Within a roughly 24-h period from 12 to 13 October, Karenia-spp. abundances averaged over the shelf abruptly increased more than doubled; these abundance spikes were associated with the combined effects of physical advection and algal growth. The obtained maps and features of Karenia spp. abundance will provide basic estimates needed to understand the processes and mechanisms by which algal blooms can inflict damage on regional fisheries.

Freshwater cyanobacterial harmful algae blooms (cHABs) are a major threat to human and environmental health and are increasing globally in frequency and severity. To manage this threat in a timely manner, science must focus on increasing our ability to predict the growth and toxigenicity of specific taxa of cyanobacteria.Recent molecular research has revealed striking genomic and metabolic diversity among the many morphologically indistinguishable sub‐species and strains of cyanobacteria. Assemblage‐level molecular metabolic capability surveys promise to improve our ability to predict cyanobacterial responses to environmental forcing, but many of these cutting‐edge techniques are not widely available or cost‐effective enough to be employed in routine monitoring programmes to support management decisions. Taxonomic ambiguity, cryptic functional specialisation, incongruence between genomic capability and phylogeny, and genomic flexibility impose severe challenges to our ability to ascribe autecological attributes at a level of taxonomic resolution that is attainable under current management strategies (i.e. Linnaean species). This lack of knowledge prohibits reliable predictions of species' responses to environmental stressors.Cyanobacterial species comprise consortia of metabolically diverse, morphologically indistinct strains that span a range of ecological specialisation. Under current, broadly applied taxonomic concepts, these species functionally embody a generalist ecological strategy—persisting and/or proliferating where other specialised competitors are negatively impacted.We postulate that within current management frameworks, characterising of cyanobacterial species as competing generalists, as well as considering abundance trajectories of well‐characterised, non‐cyanobacterial specialist phytoplankton will generate more scalable, mechanistic, and management‐relevant insight into increasing cHAB frequency and severity in suitable time frames.Here we recommend that cHAB management considers the competitive framework of phytoplankton communities, including cyanobacteria, wherein diverse environmental changes lead to deterministic responses by readily identifiable, documented specialist taxa. Characterising these changes in community structure will quantify the relative importance of altered stressors and resource availability that can be exploited by metabolically flexible cyanobacteria. [ABSTRACT FROM AUTHOR]

Algal blooms formed by some phytoplankton species can produce toxins or alter environmental conditions that can affect aquatic organisms and water quality, with impacts on the aquaculture and fisheries industries that can pose a risk to public health [...]

Dinophysis acuminata produces Diarrhetic Shellfish Toxins (DST) that contaminate natural and farmed shellfish, leading to public health risks and economically impacting mussel farms. For this reason, there is a high interest in understanding and predicting D. acuminata blooms. This study assesses the environmental conditions and develops a sub-seasonal (7 - 28 days) forecast model to predict D. acuminata cells abundance in the Lyngen fjord located in northern Norway. A Support Vector Machine (SVM) model is trained to predict future D. acuminata cells abundance by using the past cell concentration, sea surface temperature (SST), Photosynthetic Active Radiation (PAR), and wind speed. Cells concentration of Dinophysis spp. are measured in-situ from 2006 to 2019, and SST, PAR, and surface wind speed are obtained by satellite remote sensing. D. acuminata only explains 40% of DST variability from 2006 to 2011, but it changes to 65% after 2011 when D. acuta prevalence reduced. The D. acuminata blooms can reach concentration up to 3954 cells l -1 and are restricted to the summer during warmer waters, varying from 7.8 to 12.7 °C. The forecast model predicts with fair accuracy the seasonal development of the blooms and the blooms amplitude, showing a coefficient of determination varying from 0.46 to 0.55. SST has been found to be a useful predictor for the seasonal development of the blooms, while the past cells abundance is needed for updating the current status and adjusting the blooms timing and amplitude. The calibrated model should be tested operationally in the future to provide an early warning of D. acuminata blooms in the Lyngen fjord. The approach can be generalized to other regions by recalibrating the model with local observations of D. acuminata blooms and remote sensing data., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

In 2013, South Australia experienced unusually high and variable water temperatures (5°C above the historic average), with a peak sea surface temperature of approximately 27°C over a wide geographic area covering both gulfs and shelf waters. Over the same period and similar geographic area, a prolonged and widespread marine mortality event occurred. From January to May 2013, low level rates of incidental morbidity and mortality of abalone (Haliotis rubra and H. laevigata) and at least 29 fish species were observed. Mortalities were geographically extensive from Port MacDonnell on the South Coast of South Australia to Point Drummond on Eyre Peninsula, and including two gulf systems, spanning approximately 2,900 km of coastline. Mortalities were investigated using gross pathology, histopathology, bacterial culture and polymerase chain reaction (PCR) techniques. Water samples were collected to assess water column nutrient status and phytoplankton biomass levels and community composition. High nutrient concentrations were suggestive of high phytoplankton productivity, with conditions conducive to diatom blooms. A harmful (abrasive) diatom, Chaetoceros coarctatus, was observed in higher concentrations than the historical average. Observed fish mortalities were restricted to a small proportion of the populations and primarily comprised of temperate small-bodied benthic inshore species. Fish histopathology was suggestive of prolonged stress (melanomacrophage aggregation in spleens and kidneys), physical gill damage (focal gill lesions likely caused by C. coarctatus) and lethal bacterial septicaemia. Infectious and notifiable diseases were ruled out in all fish and abalone samples. Abalone mortalities were also restricted to a small proportion of the population with thermal stress a likely contributing factor that resulted in terminal secondary bacterial infections. A marine heatwave event, which promoted blooms of algae, including C. coarctatus, was likely the primary cause of widespread marine mortalities throughout South Australia in 2013. With marine heatwaves projected to increase in frequency, duration and spatial extent, this investigation demonstrated that most at risk will be temperate species in shallow water habitats already at their upper thermal tolerance limits, particularly those with high site fidelity. This should be considered in future climate proofing strategies, including risk and impact assessments underpinning the management of marine resources, fisheries, aquaculture and ecotourism.

Harmful cyanobacteria blooms are a growing threat in estuarine waters as upstream blooms are exported into coastal environments. Cyanobacteria can produce potent toxins, one of which-hepatotoxic microcystins (MCs)-can persist and accumulate within the food web. Filter-feeding invertebrates may biomagnify toxins up to 100× ambient concentrations. As such, bivalves can be used as an environmentally relevant and highly sensitive sentinel for MC monitoring. To date there has been little research on cyanotoxin bioaccumulation in estuaries. The Sacramento-San Joaquin Delta (Delta) aquatic food web has undergone a profound change in response to widespread colonization of aquatic invasive species such as Asian clams (Corbicula fluminea) in the freshwater portion of the Delta. These clams are prolific-blanketing areas of the Delta at densities up to 1000 clams/m2 and are directly implicated in the pelagic organism decline of threatened and endangered fishes. We hypothesized that Asian clams accumulate MCs which may act as an additional stressor to the food web and MCs would seasonally be in exceedance of public health advisory levels. MCs accumulation in Delta Asian clams and signal crayfish (Pacifastacus leniusculus) were studied over a two-year period. ELISA and LC-MS analytical methods were used to measure free and protein-bound MCs in clam and crayfish tissues. We describe an improved MC extraction method for use when analyzing these taxa by LC-MS. MCs were found to accumulate in Asian clams across all months and at all study sites, with seasonal maxima occurring during the summer. Although MC concentrations rarely exceeded public health advisory levels, the persistence of MCs year-round still poses a chronic risk to consumers. Crayfish at times also accumulated high concentrations of MCs. Our results highlight the utility of shellfish as sentinel organisms for monitoring in estuarine areas.

Image analysis based on biological morphological differences is an important development direction for classification and determination of planktonic algae. However, it has some shortages, such as high degree of sample imbalance and difficult to have formalized description of local physiological features. To overcome these shortages, this study decomposed recognition of harmful algae microscopic images into sample supplementation, accurate segmentation, feature extraction and classification and identification. Firstly, sample imbalance is solved by Kernel-ADASYN method to generate enough samples. Target cells are separated through integration of multi-directional projections. Refined segmentation between the spine and cingulum detail regions is further realized. Later, effective feature extraction and description of global and local features were performed one by one by matching physiological features of algae with machine recognition features. Finally, the SVM model was applied for multi-class recognition. Results demonstrated that the proposed method can reduce imbalance rate of sample size and realize multi-class recognition of microscopic images of 15 categories of algae cells.

Consistent patterns of Harmful Algal Bloom (HAB) events are not evident across the scientific literature, suggesting that local or regional variability is likely to be important in modulating any overall trend. This study summarizes Scotland-wide temporal and spatial patterns in a robust 15-year high temporal frequency time series (2006–2020) of the incidence of HABs and shellfish biotoxins in blue Mussels (Mytilus edulis), collected as part of the Food Standards Scotland (FSS) regulatory monitoring program. The relationship between the countrywide annual incidence of HAB events and biotoxins with environmental variables was also explored. Temporal patterns exhibited interannual variability, with no year-on-year increase, nor any correlation between annual occurrences. Within years, there was a summer increase in bloom frequency, peaking in July for Dinophysis spp. and Pseudo-nitzschia spp., and a plateau from May to July for Alexandrium spp. Temporal-spatial patterns were analyzed with multivariate statistics on data from monitoring sites aggregated monthly into 50-km grid cells, using Principal Component Analysis (PCA) and cluster K-means analysis. PCA analyses showed correlation between areas with similar temporal dynamics, identifying seasonality as one of the main elements of HAB variability with temporal-spatial patterns being explained by the first and second principal components. Similar patterns among regions in timing and magnitude of blooms were evaluated using K-means clusters. The analysis confirmed that the highest risk from HABs generally occurred during summer, but demonstrated that areas that respond in a similar manner (high or low risk) are not always geographically close. For example, the occurrence of the most prevalent HAB genus, Dinophysis spp., is similar countrywide, but there is a regional trend in risk level with “very-high” and “high” clusters located primarily on the southwest coast, the islands of the central and northern west coast and the Shetland Islands. “Early” and “late” blooms were also associated with certain areas and level of risk. Overall, high risk areas mainly face in a southwest direction, whilst low risk locations face a south or southeast direction. We found relatively few countrywide relationships between environmental variables and HABs, confirming the need for regional analysis to support HAB early warning.

Harmful algae blooms (HABs) are unwelcome annual events on waterbodies in California (USA). The unseemly sights of lifeless fish drifting ashore and the mammalian illnesses resulting from close contacts with HABs once in ahile are telltale signs of their presence. California as such tracks HABs closely for immediate public warnings. That said, a lack of statewide monitoring standards for producing comparable and high-quality data, however, hinders a deeper insight into HABs on California's inland waterbodies. In their absence, the current study demonstrates the utility of empirical dataset in advancing an understanding of spatiotemporal distribution of HABs on inland waterbodies. With a 2016-2021 mostly observational data, the questions asked are whether HABs incidences are expanding in California with time, whether there are localities more prone to HABs than others, and whether bivariate relationships exist between HABs reports and population density, or waterbody size, land area and geographical location. Overall, the frequency with which HABs are observed is found to increase statewide, an increase not correlated with population density, but with land area and inland waterbody size. Results also show that North Coast, Central Valley, and San Diego are the most affected regions of California. Also revealed by this mostly observational data were recent HABs spikes in the January months (California winter) which, if proven, may be signaling an emerging year-round problem that California will have to contend with.

Harmful algae can have profound economic, environmental, and social consequences. As the timing, frequency, and severity of harmful algal blooms (HABs) change alongside global climate, efficient tools to monitor and understand the current ecological context of these taxa are increasingly important. Here we employ environmental DNA metabarcoding to identify patterns in a wide variety of potentially harmful algae and associated ecological communities in the Hood Canal of Puget Sound in Washington State, USA. Tracking trends of occurrence in a series of water samples over a period of 19 months, we find algal sequences from genera with harmful members in a majority of samples, suggesting that these groups are routinely present in local waters. We report patterns in variants of the economically important genus Pseudo-nitzschia (of which some members produce domoic acid; family Bacillariaceae), as well as multiple potentially harmful algal taxa previously unknown or poorly documented in the region, including a cold-water variant from the genus Alexandrium (of which some members produce saxitoxin; family Gonyaulacaceae), two variants from the genus Karlodinium (of which some members produce karlotoxins; family Kareniaceae), and one variant from the parasitic genus Hematodinium (family Syndiniaceae). We then use data on environmental variables and the biological community surrounding each algal taxon to illustrate the ecological context in which they are commonly found. Environmental DNA metabarcoding thus simultaneously (1) alerts us to potential new or cryptic occurrences of algae from harmful genera, (2) expands our knowledge of the co-occurring conditions and species associated with the growth of these organisms in changing marine environments, and (3) suggests a pathway for multispecies monitoring and management moving forward.

The Phaeocystis globosa widely exists in the seawater, which becomes a great threat for the health of humans and animals in the ecological ecosystem. In this work, we reported a promising control strategy with quercetin(QT) enhanced cellulose nanocrystals (CNC). The quercetin enhanced cellulose nanocrystals (QT/CNC) was characterized through Atomic Force Microscopy (AFM), Fourier Transform Infrared Spectrometer (FTIR) and X-ray diffractometer (XRD). The effects of concentrations of CNC and QT on controlled Phaeocystis globosa were investigated. The results showed that the removal rate of Phaeocystis globosa exhibited an optimal value (92.1 %) at 0.05 g L-1 CNC and 0.1 g L-1 QT. Furthermore, the chlorophyll-a content in the Phaeocystis globosa exhibited a remarkable decrease from 3.72 mg L-1 to 0.21 mg L-1 when QT/CNC was interacted. On the basis of these results, we concluded that Phaeocystis globosa could be removed by QT/CNC effectively. During the removal of Phaeocystis globosa, the pH of algal solution decreased from 9.45 to 7.36, indicating that QT/CNC could maintain the normal pH of water. In addition, the testing result of the QT/CNC zeta potentials was negative, which revealed that Phaeocystis globosa was removed through inhibition and flocculation. Accordingly, a possible removal mechanism of Phaeocystis globose by QT/CNC was presumed. This study suggested that QT/CNC might be a potential treatment materials on the removal of Phaeocystis globosa.

The Indian River Lagoon (IRL), located on the east coast of Florida, is a complex estuarine ecosystem that is negatively affected by recurring harmful algal blooms (HABs) from distinct taxonomic/functional groups. Enhanced monitoring was established to facilitate rapid quantification of three recurrent bloom taxa, Aureoumbra lagunensis, Pyrodinium bahamense, and Pseudo-nitzschia spp., and included corroborating techniques to improve the identification of small-celled nanoplankton (2 × 108 cells L–1) were observed in all 6 years sampled and across multiple seasons. In contrast, abundance of P. bahamense, largely driven by the annual temperature cycle that moderates life cycle transitions and growth, displayed a strong seasonal pattern with blooms (105–107 cells L–1) generally developing in early summer and subsiding in autumn. However, P. bahamense bloom development was delayed and abundance was significantly lower in years and locations with sustained A. lagunensis blooms. Pseudo-nitzschia spp. were broadly distributed with sporadic bloom concentrations (reaching 107 cells L–1), but with minimal concentrations of the toxin domoic acid detected (

Harmful algal blooms (HABs) are common disastrous ecological anomalies in coastal waters. An effective algae monitoring approach is important for natural disaster warning and environmental governance. However, conducting rapid and sensitive detection of multiple algae is still challenging. Here, we designed an ultrasensitive, rapid and portable double-layer microfluidic biochip for the simultaneous quantitative detection of six species of algae. Specific DNA probes based on the 18S ribosomal DNA (18S rDNA) gene fragments of HABs were designed and labeled with the fluorescent molecule cyanine-3 (Cy3). The biochip had multiple graphene oxide (GO) nanosheets-based reaction units, in which GO nanosheets were applied to transfer target DNA to the fluorescence signal through a photoluminescence detection system. The entire detection process of multiple algae was completed within 45 min with the linear range of fluorescence recovery of 0.1 fM–100 nM, and the detection limit reached 108 aM. The proposed approach has a simple detection process and high detection performance and is feasible to conduct accurate detection with matched portable detection equipment. It will have promising applications in marine natural disaster monitoring and environmental care.

Across the European Atlantic Arc (Scotland, Ireland, England, France, Spain, and Portugal) the shellfish aquaculture industry is dominated by the production of mussels, followed by oysters and clams. A range of spatially and temporally variable harmful algal bloom species (HABs) impact the industry through their production of biotoxins that accumulate and concentrate in shellfish flesh, which negatively impact the health of consumers through consumption. Regulatory monitoring of harmful cells in the water column and toxin concentrations within shellfish flesh are currently the main means of warning of elevated toxin events in bivalves, with harvesting being suspended when toxicity is elevated above EU regulatory limits. However, while such an approach is generally successful in safeguarding human health, it does not provide the early warning that is needed to support business planning and harvesting by the aquaculture industry. To address this issue, a proliferation of web portals have been developed to make monitoring data widely accessible. These systems are now transitioning from “nowcasts” to operational Early Warning Systems (EWS) to better mitigate against HAB-generated harmful effects. To achieve this, EWS are incorporating a range of environmental data parameters and developing varied forecasting approaches. For example, EWS are increasingly utilizing satellite data and the results of oceanographic modeling to identify and predict the behavior of HABs. Modeling demonstrates that some HABs can be advected significant distances before impacting aquaculture sites. Traffic light indices are being developed to provide users with an easily interpreted assessment of HAB and biotoxin risk, and expert interpretation of these multiple data streams is being used to assess risk into the future. Proof-of-concept EWS are being developed to combine model information with in situ data, in some cases using machine learning-based approaches. This article: (1) reviews HAB and biotoxin issues relevant to shellfish aquaculture in the European Atlantic Arc (Scotland, Ireland, England, France, Spain, and Portugal; (2) evaluates the current status of HAB events and EWS in the region; and (3) evaluates the potential of further improving these EWS though multi-disciplinary approaches combining heterogeneous sources of information.

Ecosystem service flows may change or disappear temporarily or permanently as a result of environmental changes or ecological disturbances. In coastal areas, ecological disturbances caused by toxin-producing harmful algae blooms can impact flows of ecosystem services, particularly provisioning (e.g., seafood harvesting) and cultural services (e.g., recreation). This study uses a random utility model of recreational boating choices to simulate changes in the value of cultural ecosystem services provided by recreation in coastal ecosystems resulting from prolonged ecological disturbances caused by harmful algae blooms. The empirical application relies on observed trips to 35 alternative boat access ramps in Lee County, an important marine access destination in southwest Florida. Results indicate that reduced boating access from harmful algae blooms may have resulted in losses of $3 million for the 2018 blooms, which lasted from the end of June to the end of September.

Harmful algal blooms (HABs) caused by Prorocentrum minimum have seriously posed economic losses and ecological disasters. To reduce these losses, aptamers are used as a new molecular probe to establish rapid methods. Herein, to improve the affinity and application of aptamers in the detection of harmful algae, the optimization was performed on the previously reported aptamers against P. minimum. First, a total of seven candidate aptamers, including three truncated aptamers (TA1, TA2 and TA3) and four mutant aptamers (MA1, MA2, MA3 and MA4), were obtained by truncation and G-quadruplex (GQ)-forming mutation. Next, the specificity and affinity test by flow cytometry revealed that except for TA1 and TA2, all of the candidate aptamers are specific with the equilibrium dissociation constant of (40.4 ± 5.5) nM for TA3, (63.3 ± 24.0) nM for MA1, (71.7 ± 14.6) nM for MA2, (365.9 ± 74.4) nM for MA3, and (21.1 ± 0.5) nM for MA4, respectively. The circular dichroism analysis of the mutant aptamers demonstrated that the GQ structures formed by MA1/MA2, MA3 and MA4 were antiparallel, mixed parallel and parallel, respectively. The affinity of aptamers with various GQ is in the order of parallel structure > antiparallel structure > mixed parallel structure. In addition, to further improve binding ability, the binding conditions of MA4 were optimized as follows: binding time, 60 min; binding temperature, 37 °C; pH of the binding buffer, 7.5; and Na + /Mg 2+ concentration in the binding buffer, 100 mM/0.5 mM. The binding examination by fluorescence microscopy showed that MA4 had a stronger binding ability to P. minimum than the original aptamer. Taken together, this study not only obtained an aptamer with higher affinity than the original aptamer, which laid a good foundation for subsequent application, but also may provide a feasible reference method for aptamer optimization., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Simple Summary: Harmful algae are those which release toxins to the aquatic ecosystems. Excessive growth of these algae can kill fish, create anoxia, impede aquaculture activities and contaminate aquatic food. Therefore, it is important to investigate their occurrence, diversity and abundance in pond aquaculture systems. In this study, we have identified 81 genera of harmful algae from 30 coastal homestead ponds mainly consisting of Microcystis spp. (30.14%) and Actinoptycus spp. (18.32%). Based on taxonomic classes, the community assemblage was dominated by Cyanophyceae, Chlorophyceae and Bacillariophyceae. Statistical analyses demonstrated that that dissolved oxygen, nitrates, phosphates, sulphates, salinity and transparency influence the abundance of identified algal genera. Algae are the naturally produced food for fish in any aquatic ecosystem and an indicator of a productive pond. However, excess abundance of harmful algae can have detrimental effects on fish health. In this study, the algal communities of 30 coastal homestead fish ponds were investigated to identify the diversity, assemblage and controlling environmental variables of harmful algae from a tropical coastal area. The findings showed that 81 of the 89 genera of identified algae were harmful, with the majority of them being in the classes of Cyanophyceae (50.81%), Chlorophyceae (23.75%), Bacillariophyceae (9.5%), and Euglenophyceae (8.47%). Microcystis spp. alone contributed 28.24% to the total abundance of harmful algae. Significant differences (p < 0.05) in algal abundance were found among the ponds with the highest abundance (470 ± 141.74 × 103 cells L−1) at pond (S25) near agricultural fields and the lowest abundance (109.33 ± 46.91 × 103 cells L−1) at pond (S14) which was lacking sufficient sunlight and nutrients. Diversity indices, e.g., dominance (D), evenness (J′), richness (d) and Shannon diversity index (H′) ranged from 0.17 to 0.44, 0.23 to 0.6, 0.35 to 2.23 and 0.7 to 1.79, respectively, indicating a moderate range of diversity and community stability. Community composition analysis showed the assemblage was dominated by Cyanophyceae, Chlorophyceae and Bacillariophyceae, whereas, multivariate cluster analyses (CA) identified 11 major clusters. To identify the factors controlling their distribution or community assemblages, eight environmental variables (temperature, pH, dissolved oxygen (DO), salinity, transparency, nitrates, phosphates and sulphate) were measured. ANOVA analysis showed that the variables significantly differed (p < 0.05) among the ponds, and canonical correspondence analysis (CCA) demonstrated that DO, nitrates, phosphates, sulphates, salinity and transparency have the most impact on the abundance of algal genera. In addition, analyses with Pearson's correlation coefficient showed that the abundance of total algae, diversity and community were mainly governed by phosphates and sulphates. These results can be used to identify and control these toxic algal groups in the local aquaculture sector. [ABSTRACT FROM AUTHOR]