Harmful Algal Bloom Events Research Articles

Advances in forecasting harmful algal blooms using machine learning models: A case study with Planktothrix rubescens in Lake Geneva

The development of anthropic activities during the 20th century increased the nutrient fluxes in freshwater ecosystems, leading to the eutrophication phenomenon that most often promotes harmful algal blooms (HABs). Recent years have witnessed the regular and massive development of some filamentous algae or cyanobacteria in Lake Geneva. Consequently, important blooms could result in detrimental impacts on economic issues and human health. In this study, we tried to lay the foundation of an HAB forecast model to help scientists and local stakeholders with the present and future management of this peri-alpine lake. Our forecast strategy was based on pairing two machine learning models with a long-term database built over the past 34 years. We created HAB groups via a K-means model. Then, we introduced different lag times in the input of a random forest (RF) model, using a sliding window. Finally, we used a high-frequency dataset to compare the natural mechanisms with numerical interaction using individual conditional expectation plots.We demonstrate that some HAB events can be forecasted over a year scale. The information contained in the concentration data of the cyanobacteria was synthesized in the form of four intensity groups that directly depend on the P. rubescens concentration. The categorical transformation of these data allowed us to obtain a forecast with correlation coefficients that stayed above a threshold of 0.5 until one year for the counting cells and two years for the biovolume data. Moreover, we found that the RF model predicted the best P. rubescens abundance for water temperatures around 14°C. This result is consistent with the biological processes of the toxic cyanobacterium. In this study, we found that the coupling between K-means and RF models could help in forecasting the development of the bloom-forming P. rubescens in Lake Geneva. This methodology could create a numerical decision support tool, which should be a significant advantage for lake managers.

Development of a benthic foraminifera based marine biotic index (Foram-AMBI) for the Gulf of Mexico: A decision support tool

The Gulf of Mexico (GoM) is an economically important region (e.g. oil and gas, fisheries) and with the expansion of oil drilling, harmful algal bloom events, oil blowouts, dead zones, anthropogenic eutrophication and contaminant loading, it is important that the ecological quality statuses (EcoQS) of different localities in the Gulf are closely monitored. The EcoQS, as implemented by the European Water Framework Directive, is an effective tool for monitoring ecological health and developing reference conditions. One such index used to define EcoQS is the AZTI Marine Biotic Index (AMBI), which pairs species abundance with environmental stressors. Benthic foraminifera are ideal specimens to populate the index due to their varying environmental sensitivities among species, preservation potential, and high diversity and abundance in nearly every marine environment. To calculate the benthic foraminiferal AMBI (Foram-AMBI), species are assigned to one of five groups ranging from sensitive (I) to first-order opportunists (V) based on their correlation to total organic matter and sediment grain size. This study constructs a Foram-AMBI from benthic foraminifera assemblages collected at 59 sites throughout the GoM. This approach provides reference EcoQS for the GoM and will satisfy the need for widespread geospatial coverage in the case of future natural or anthropogenic disturbances. This study provides a master assignment list of 155 species and identification plates of 44 of those species from a depth range of 42 m-2975 m. The development of a GoM Foram-AMBI encourages collaborative partnerships between academic scientists and living resource managers throughout the GoM to operationalize, refine and implement the Foram-AMBI as a decision support tool.

A novel method based on time series satellite data analysis to detect algal blooms

Water bodies eutrophication is a worldwide environmental problem characterized by excessive phytoplankton growth which often includes occurrence of harmful algal blooms events. Chlorophyll-a concentration is widely used as an indicator of biomass and can be quantified by optic sensors. In this work, we use a satellite derived Chlorophyll-a concentration time series for the period 2001–2014 obtained from MODIS/TERRA data to detect and characterize algal bloom events in an eutrophic reservoir. Our results demonstrate that fixed threshold methods identify too many bloom dates but a dynamic method based on frequencies analysis and statistical approach, performed better because it represents the normal phytoplankton mass and a bloom is identified like a deviation from it. This approach was tested in San Roque reservoir which supplies fresh water to Córdoba city, one of the most populated of Argentina. According to Carlson index values, this is an eutrophic to hypereutrophic water body. Validation of log10 (Chlorophyll-a concentration) derived from satellite model concentration with ground-based measurements data of Chlorophyll-a concentration demonstrates an acceptable error (RMSE = 0.59) considering data distribution. The implementation of the proposed method to identify blooms over a control data set and validated with LANDSAT 8 - OLI images, demonstrates that the approach described is robust and stable over time.

Use of sea surface discoloration to monitor and discriminate the causative genera of harmful algal blooms (HABs): Practical use of digital repeat photography

Harmful algal blooms (HABs) are associated with water quality degradation, which damages fisheries, ecosystems, and public health. Consequently, techniques for detecting the occurrence of HABs have been developed globally. However, conventional techniques are unable to discriminate the causative species/genera of HABs objectively. Therefore, the aim of the present study was to develop a technique for frequently analyzing the causative genera of HAB events using repeat digital photography with a stationary device named “HABcam.” The HABcam was installed at Okigamisenishi monitoring station in the inner western area of Ariake Bay, Japan, and the digital images obtained were analyzed to quantify the sea surface color and to estimate the probability of a HAB occurrence on a daily basis using Bayes' theorem. The estimated probability of a HAB occurrence accurately discriminated a HAB occurrence or non-occurrence in the research area on 19/21 days (=90.5%) for Chattonella spp. and 7/8 days (=87.5%) for Skeletonema spp. These findings indicate that this technique can be used to objectively determine the causative genera during HAB events and to observe HABs with high accuracy and at a high frequency.

Inequality in the Economic Impacts from Climate Shocks in Fisheries: The Case of Harmful Algal Blooms

Climate impacts disproportionately affect people that are most vulnerable and least able to adapt. The extent to which these equity impacts extend to fishing communities in the developed world is a question that has received surprisingly little attention. Here we explore the distributional impacts of a climate shock in one of the largest and most valuable fisheries on the West Coast of the United States. Specifically, we examine whether a series of two harmful algal blooms (HABs), occurring during the 2014–2016 Northeast Pacific Marine Heatwave, differentially affected small and large vessels in the commercial California Dungeness crab fishery. The HAB events were managed with localized fishery closures in response to elevated levels of the HAB toxin, domoic acid, in crab tissue. We find evidence that large vessels had a greater ability to mitigate losses from the HAB events. Thus, the proportion of total revenue going to small-vessel operators and the proportion of small-vessel participation in the fishery fell in response to the HAB events in several California fishing ports. Our results, therefore, offer empirical evidence that climate impacts on fishing communities are not uniform and offer insights into potential alternative adaptation strategies for different ocean user groups.

The magnitude and drivers of harmful algal blooms in China’s lakes and reservoirs: A national-scale characterization

Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production remain poorly understood and can vary in space and time. It is within this context that we use machine learning (ML) and two 14-year (2005–2018) data sets on water quality and meteorological conditions of China’s lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. General regression neural network (GRNN) models are developed to predict chlorophyll a concentrations for each lake and reservoir during two study periods (2005–2010 and 2011–2018). The developed models with an acceptable model fit are then analyzed by two indices to determine the areal HAB magnitudes and associated drivers. Our national assessment suggests that HAB magnitudes for China’s lakes and reservoirs displayed a decreasing trend from 2006 (1363.3 km2) to 2013 (665.2 km2), and a slightly increasing trend from 2013 to 2018 (775.4 km2). Among the 142 studied lakes and reservoirs, most severe HABs were found in Lakes Taihu, Dianchi and Chaohu with their contribution to the total HAB magnitude varying from 89.2% (2013) to 62.6% (2018). HABs in Lakes Taihu and Chaohu were strongly associated with both total phosphorus and nitrogen concentrations, while our results were inconclusive with respect to the predominant environmental factors shaping the eutrophication phenomena in Lake Dianchi. The present study provides evidence that effective HAB mitigation may require both nitrogen and phosphorus reductions and longer recovery times; especially in view of the current climate-change projections. ML represents a robust strategy to elucidate water quality patterns in lakes, where the available information is sufficient to train the constructed algorithms. Our mapping of HAB magnitudes and associated environmental/meteorological drivers can help managers to delineate hot-spots at a national scale, and comprehensively design the best management practices for mitigating the eutrophication severity in China’s lakes and reservoirs.

Examining harmful algal blooms through a disaster risk management lens: A case study of the 2015 U.S. West Coast domoic acid event

The human dimensions of harmful algal blooms (HABs) are becoming increasingly apparent as they grow in frequency and magnitude in some regions of the world under changing ocean conditions. One such region is the U.S. West Coast, where HABs of toxigenic species of Pseudo-nitzschia have been found to coincide with or closely follow periods of warming. In 2015, the region experienced a massive HAB of Pseudo-nitzschia that was associated with the 2014-16 Northeast Pacific marine heatwave. The HAB event delayed the opening of the lucrative commercial Dungeness crab fishery for up to 5 months and closed the popular recreational razor clam fishery, resulting in fishery failures and disaster declarations and causing significant sociocultural and economic impacts to coastal communities. Here, management actions are examined that were taken by federal and state government agencies and responses of coastal residents to this extreme HAB event using a disaster risk management framework consisting of four phases: 1) prediction and early warning, 2) event response, 3) recovery and reconstruction, and 4) mitigation and prevention. Clear differences in management actions at the state level were evident in California, Oregon, and Washington during every phase, producing vastly different perceptions of management by coastal residents. A history of trusted relationships and coordination among agencies and with the fishing industry in Washington State was associated with more transparent and accepted management responses. The examination found that additional education, outreach, and trust-building exercises would provide benefits to communities affected by extreme HAB events. Our findings contribute to an understanding of climate change adaptation in coastal communities dependent on fishery resources.

Over 30 years of HABs in the Philippines and Malaysia: What have we learned?

In the Southeast Asian region, the Philippines and Malaysia are two of the most affected by Harmful Algal Blooms (HABs). Using long-term observations of HAB events, we determined if these are increasing in frequency and duration, and expanding across space in each country. Blooms of Paralytic Shellfish Toxin (PST)-producing species in the Philippines did increase in frequency and duration during the early to mid-1990s, but have stabilized since then. However, the number of sites affected by these blooms continue to expand though at a slower rate than in the 1990s. Furthermore, the type of HABs and causative species have diversified for both toxic blooms and fish kill events. In contrast, Malaysia showed no increasing trend in the frequency of toxic blooms over the past three decades since Pyrodinium bahamense was reported in 1976. However, similar to the Philippines, other PST producers such as Alexandrium minutum and Alexandrium tamiyavanichii have become a concern. No amnesic shellfish poisoning (ASP) has been confirmed in either Philippines or Malaysia thus far, while ciguatera fish poisoning cases are known from the Philippines and Malaysia but the causative organisms remain poorly studied. Since the 1990s and early 2000s, recognition of the distribution of other PST-producing species such as species of Alexandrium and Gymnodinium catenatum in Southeast Asia has grown, though there has been no significant expansion in the known distributions within the last decade. A major more recent problem in the two countries and for Southeast Asia in general are the frequent fish-killing algal blooms of various species such as Prorocentrum cordatum, Margalefidinium polykrikoides, Chattonella spp., and unarmored dinoflagellates (e.g., Karlodinium australe and Takayama sp.). These new sites affected and the increase in types of HABs and causative species could be attributed to various factors such as introduction through mariculture and eutrophication, and partly because of increased scientific awareness. These connections still need to be more concretely investigated. The link to the El Niño Southern Oscillation (ENSO) should also be better understood if we want to discern how climate change plays a role in these patterns of HAB occurrences.

Physical and Biogeochemical Factors Driving Spatially Heterogeneous Phytoplankton Blooms in Nearshore Waters of Santa Monica Bay, USA

Phytoplankton blooms in nearshore waters are difficult to predict using only biogeochemical factors known to control phytoplankton growth, yet the need to understand these events continues to grow with expanding harmful algal bloom (HAB) events. The present study investigated the spatial and temporal dynamics of phytoplankton blooms and their drivers in King Harbor, a harbor in Santa Monica Bay in the Southern California Bight. High-frequency sensor measurements of environmental variables and biomass and discrete sampling of phytoplankton community composition and nutrients over an annual cycle were obtained. Eleven distinct bloom events, nine of which were numerically dominated by dinoflagellates, were identified over the study period. Results from both regression-based and time series analyses show that these blooms were correlated with increased temperature, changes in nutrient concentrations, and decreased tidally driven mixing, revealing an opportunity for bloom initiation close to neap tides. Predictors of chlorophyll biomass and environmental factors that explained differences in microplankton community structure differed between the two basins of King Harbor, despite their close and connected nature. Biomass and HAB taxa abundances in the harbor were significantly correlated with those in Santa Monica Bay with a 1-week lag in the harbor data, suggesting possible onshore transport of organisms into the harbor. The results of this study quantify the significant influence of tidal cycle as a physical process operating locally and at timescales of hours to days and provide evidence for a high degree of spatial heterogeneity in bloom dynamics in nearshore environments.

Hurricanes, El Ni\xf1o and harmful algal blooms in two sub-tropical Florida estuaries: Direct and indirect impacts

Future increases in the intensity of hurricanes and El Niño periods predicted by climate change models have focused attention on their role in stimulating harmful algal blooms (HABs). A series of hurricanes that recently impacted Florida (USA) provided a unique opportunity to explore the relationships between hurricanes, El Niño and HABs in two Florida estuaries subject to repeated intense ecosystem disruptive HABs, the Indian River Lagoon and the St. Lucie Estuary. The roles that hurricanes and El Niño play in contributing to HAB events are examined in the context of key structural and functional features of each estuary and their watersheds, including morphology, water residence time and hydrology, such as the influence of Lake Okeechobee discharges into the St. Lucie Estuary. The most direct impact was the increase in rainfall associated with hurricanes and El Niño, resulting in enhanced nutrient loads which drive HABs in the Indian River Lagoon and Lake Okeechobee. Major HABs in Lake Okeechobee also present an indirect threat of freshwater HAB blooms in the St. Lucie Estuary via mandated discharges from the lake into the estuary during high rainfall periods. Conversely, during the absence of HABs in Lake Okeechobee, short water residence times produced by discharges into the St. Lucie Estuary can result in lower bloom intensities.

Mathematical analysis of plankton population dynamics

Harmful algal blooms (HABs) event that causes enormous economic loss and health effect raises concerns among environmentalists. In this paper, a mathematical model of interaction between nutrient, toxin-producing phytoplankton (TPP), non-toxic phytoplankton (NTP), zooplankton, and toxic chemicals is proposed to study on how the process of these HABs occurred. The model of interaction is represented by Ordinary Differential Equations (ODEs) and stability analysis of the model is conducted. Several conditions for the system to be stable around trivial and interior equilibrium point are obtained. From the analysis, it is observed that under nutrient limitation, the amounts of toxic chemicals secreted out by the TPP are increased. As a result, NTP population and zooplankton population are affected by the situation. If this situation is prolonged, this will result in the extinction of both populations. Overall, this study shows that TPP release more toxic chemicals when the nutrient is limited and gives a better understanding on the occurrence of HABs event.

Harmful Algal Blooms: Identifying Effective Adaptive Actions Used in Fishery-Dependent Communities in Response to a Protracted Event

The ‘blob’ of anomalously warm surface water that persisted in the North Pacific Ocean from 2013-2016 resulted in a massive harmful algal bloom (HAB) of Pseudo-nitzschia along the entire U.S. West Coast. The bloom produced record-breaking concentrations of domoic acid, a marine neurotoxin, that contaminated seafood and necessitated fisheries harvest closures beginning in May 2015. The subsequent closures were unprecedented in length and geographic extent, generating an economic shock for fishing communities. We sought to identify effective adaptive actions used in fishery-dependent communities in response to this event. Using survey data collected across 16 fishing communities following the 2015 HAB event, we empirically identified factors affecting an individual’s: 1) absolute magnitude of income loss, 2) likelihood of income loss recovery, and 3) severity of emotional stress. Our findings indicate that individuals who suffered greater absolute income losses were exposed to longer fisheries closures, more dependent on shellfish as a source of income, and employed in the fishing industry. Income diversification was an effective strategy for reducing and/or recovering HAB related income losses. Advertising was also found to be an effective income recovery strategy, but for fishers it was associated with increased emotional stress. If increasing the adaptive capacity of fishery-dependent coastal communities to HAB events is a policy goal, then costs to adaptive action such as emotional stress, limited access to alternate fisheries, new fishing gear, a lack of alternate job skills or access to job networks, and a lack of advertising know-how will need to be addressed.

HABNet: Machine Learning, Remote Sensing-Based Detection of Harmful Algal Blooms

This article describes the application of machine learning techniques to develop state-of-the-art detection and prediction system for spatiotemporal events found within remote sensing data; specifically, harmful algal bloom (HAB) events. We propose HAB detection system based on a ground truth historical record of HAB events, a novel spatiotemporal datacube representation of each event (from MODIS and GEBCO bathymetry data), and a variety of machine learning architectures utilizing the state-of-the-art spatial and temporal analysis methods based on convolutional neural networks, long short-term memory components together with random forest, and support vector machine classification methods. This work has focused specifically on the case study of the detection of Karenia brevis algae ( K. brevis ) HAB events within the coastal waters of Florida (over 2850 events from 2003 to 2018; an order of magnitude larger than any previous machine learning detection study into HAB events). The development of multimodal spatiotemporal datacube data structures and associated novel machine learning methods give a unique architecture for the automatic detection of environmental events. Specifically, when applied to the detection of HAB events, it gives a maximum detection accuracy of 91% and a Kappa coefficient of 0.81 for the Florida data considered. A HAB forecast system was also developed where a temporal subset of each datacube was used to predict the presence of a HAB in the future. This system was not significantly less accurate than the detection system being able to predict with 86% accuracy up to 8 d in the future.

Market Impacts of a Toxic Algae Event: The Case of California Dungeness Crab

Perceptions of seafood safety are a known driver of seafood demand, and misinformation about seafood safety has generated documented welfare losses in seafood markets. Welfare losses known as avoidance costs can occur when consumers respond to imperfect information about a contamination event, perceiving a health risk from seafood consumption where one does not exist. Furthermore, contamination events can enable other indirect economic impacts in the form of welfare transfers within the seafood supply chain. Here we explore the indirect economic impacts generated by the prolonged 2015 harmful algal bloom event in California. During this event, harmful algae produced high levels of domoic acid (a neurotoxin), resulting in closures for all commercial Dungeness crab fisheries in California that lasted roughly four and a half months. To estimate the impacts of the event, we investigate whether Dungeness crab prices, both at the ex-vessel and consumer levels, were negatively impacted by the event after the closures were lifted and the crab was declared safe to eat. We find ex-vessel prices fell by at least 9.6% while consumer prices were not impacted. We put forth three competing theories to explain these outcomes and discuss the efficiency and distributional implications of each alternative.

Atmospheric transport of nutrients during a harmful algal bloom event

A large-scale, mixed Prorocentrum dentatum Stein and Skeletonema costatum bloom developed in the coastal waters of Zhejiang province, China (Zhoushan city and Liuheng Island) from May 3 to 8, 2006. We used the Global Nested Air Quality Prediction Modeling System (GNAQPMS) to show that nutrients (nitrate, ammonium and FeII) were atmospherically transported to the East China Sea before the harmful algal bloom. We suggest that atmospheric transport is a significant source of nutrients in the East China Sea when the hydrological setting is dominated by the oligotrophic Taiwan warm current in spring. This atmospheric transport of nutrients is a possible cause of harmful algal blooms along the coast of the East China Sea during dust events.

Phycosphere Microbial Succession Patterns and Assembly Mechanisms in a Marine Dinoflagellate Bloom

Given the ecological significance of microorganisms in algal blooming events, it is critical to understand the mechanisms regarding their distribution under different conditions. We tested the hypothesis that microbial community succession is strongly associated with algal bloom stages, and that the assembly mechanisms are cocontrolled by deterministic and stochastic processes. Community structures and underlying ecological processes of microbial populations (attached and free-living bacteria) at three algal bloom stages (pre-, during, and postbloom) over a complete dinoflagellate Scrippsiella trochoidea bloom were investigated. Both attached and free-living taxa had a strong response to the bloom event, and the latter was more sensitive than the former. The contribution of environmental parameters to microbial variability was 40.2%. Interaction analysis showed that complex positive or negative correlation networks exist in phycosphere microbes. These relationships were the potential drivers of mutualist and competitive interactions that impacted bacterial succession. Null model analysis showed that the attached bacterial community primarily exhibited deterministic processes at pre- and during-bloom stages, while dispersal-related processes contributed to a greater extent at the postbloom stage. In the free-living bacterial community, homogeneous selection and dispersal limitation dominated in the initial phase, which gave way to more deterministic processes at the two later stages. Relative contribution analyses further demonstrated that the community turnover of attached bacteria was mainly driven by environmental selection, while stochastic factors had partial effects on the assembly of free-living bacteria. Taken together, these data demonstrated that a robust link exists between bacterioplankton community structure and bloom progression, and phycosphere microbial succession trajectories are cogoverned by both deterministic and random processes.IMPORTANCE Disentangling the mechanisms shaping bacterioplankton communities during a marine ecological event is a core concern for ecologists. Harmful algal bloom (HAB) is a typical ecological disaster, and its formation is significantly influenced by alga-bacterium interactions. Microbial community shifts during the HAB process are relatively well known. However, the assembly processes of microbial communities in an HAB are not fully understood, especially the relative influences of deterministic and stochastic processes. We therefore analyzed the relative contributions of deterministic and stochastic processes during an HAB event. Both free-living and attached bacterial groups had a dramatic response to the HAB, and the relative importance of determinism versus stochasticity varied between the two bacterial groups at various bloom stages. Environmental factors and biotic interactions were the main drivers impacting the microbial shift process. Our results strengthen the understanding of the ecological mechanisms controlling microbial community patterns during the HAB process.

Paralytic Shellfish Toxins and Ocean Warming: Bioaccumulation and Ecotoxicological Responses in Juvenile Gilthead Seabream (Sparus aurata).

Warmer seawater temperatures are expected to increase harmful algal blooms (HABs) occurrence, intensity, and distribution. Yet, the potential interactions between abiotic stressors and HABs are still poorly understood from ecological and seafood safety perspectives. The present study aimed to investigate, for the first time, the bioaccumulation/depuration mechanisms and ecotoxicological responses of juvenile gilthead seabream (Sparus aurata) exposed to paralytic shellfish toxins (PST) under different temperatures (18, 21, 24 °C). PST were detected in fish at the peak of the exposure period (day five, 0.22 µg g−1 N-sulfocarbamoylGonyautoxin-1-2 (C1 and C2), 0.08 µg g−1 Decarbamoylsaxitoxin (dcSTX) and 0.18 µg g−1 Gonyautoxin-5 (B1)), being rapidly eliminated (within the first 24 h of depuration), regardless of exposure temperature. Increased temperatures led to significantly higher PST contamination (275 µg STX eq. kg−1). During the trial, fish antioxidant enzyme activities (superoxide dismutase, SOD; catalase, CAT; glutathione S-transferase, GST) in both muscle and viscera were affected by temperature, whereas a significant induction of heat shock proteins (HSP70), Ubiquitin (Ub) activity (viscera), and lipid peroxidation (LPO; muscle) was observed under the combination of warming and PST exposure. The differential bioaccumulation and biomarker responses observed highlight the need to further understand the interactive effects between PST and abiotic stressors, to better estimate climate change impacts on HABs events, and to develop mitigation strategies to overcome the potential risks associated with seafood consumption.

Advanced coagulation using in-situ generated liquid ferrate, Fe (VI), for enhanced pretreatment in seawater RO desalination during algal blooms

Harmful algal blooms (HABs) are considered a major threat for seawater reverse osmosis (SWRO) plants. The presence of HABs in the raw feed water can cause increase of chemical consumption within the desalination plant, increase membrane fouling rate and might lead to plant shutdown. The removal of Algal Organic Matters (AOMs) during the pretreatment will help in increasing the membrane lifetime, reduce operation cost and increase the plant reliability. In this study, the efficiency of liquid ferrate and ferric chloride during coagulation on the removal of AOMs was investigated. The liquid ferrate was generated in-situ by wet oxidation of ferric iron using hypochlorite in a caustic medium. Two seawater models were employed, the first one contains 10 mg c/L of sodium alginate and the second one contains also 10 mg c/L of Chaetoceros affinis algae (CA). During the advanced coagulation, liquid ferrate proved to be more effective in removing AOM than ferric chloride, with an overall DOC removal of 90%, enabling 100% algal removal and the inactivation of 99.99% of the microorganisms. The results presented in this study highlights the efficiency of liquid ferrate as seawater pretreatment during the HABs events.

Diversity and toxic potential of algal bloom-forming species from Takaroa lagoon (Tuamotu, French Polynesia): a field and mesocosm study

Pearl farming lagoons are economically important, yet poorly studied ecosystems in French Polynesia. This paper describes a study conducted in 2016 in Takaroa (Tuamotu Archipelago), an atoll recurrently affected by harmful algal bloom (HAB) events. The objectives were to gain insight into phytoplankton community composition, identify the main bloom-forming species and investigate their potential for toxicity. A mesocosm approach was used to assess the response of phytoplankton communities to 3 nutrient treatments: Conway with Si, Si-depleted f/2 and a commercial N-P fertilizer. In total, 87 morpho-species were described from Takaroa lagoon, with dinoflagellates as the most diverse group. Diatoms (Extubocellulus sp., Cylindrotheca closterium, Nitzschia spp.), dinoflagellates (Gymnodinium spp., Heterocapsa spp.) and flagellates (Cryptomonas sp., Pyraminonas spp.) were among the major bloom-forming species identified. Most markedly, Extubocellulus sp., a diatom never reported from French Polynesia before, was able to bloom even in Si-poor environments. Additionally, in vitro cultures of 12 bloom-forming strains were successfully established and tested for their toxicity. Preliminary results suggest that 9 strains, including dinoflagellates (Prorocentrum lima, Amphidinium spp., Heterocapsa sp.), Pyraminonadales (Pyramimonas sp.) and cryptophytes (Cryptomonas sp.), are the likely producers of cyclic imine neurotoxins and toxins acting on voltage-gated sodium channels. The contribution of these toxins to the mortality events previously reported in Takaroa lagoon is further discussed. Overall, this study highlights the relevance of a mesocosm approach which can be applied to other understudied atolls of French Polynesia recurrently threatened by HABs.

A Comprehensive Review: Development of Electrochemical Biosensors for Detection of Cyanotoxins in Freshwater.

Cyanobacteria harmful algal blooms are increasing in frequency and cyanotoxins have become an environmental and public concern in the U.S. and worldwide. In this Review, the majority of reported studies and developments of electrochemical affinity biosensors for cyanotoxins are critically reviewed and discussed. Essential background information about cyanobacterial toxins and electrochemical biosensors is combined with the rapidly moving development of electrochemical biosensors for these toxins. Current issues and future challenges for the development of useful electrochemical biosensors for cyanotoxin detection that meet the demands for applications in field freshwater samples are discussed. The major aspects of the entire review article in a prescribed sequence include (i) the state-of-the-art knowledge of the toxicity of cyanotoxins, (ii) important harmful algal bloom events, (iii) advisories, guidelines, and regulations, (iv) conventional analytical methods for determination of cyanotoxins, (v) electrochemical transduction, (vi) recognition receptors, (vii) reported electrochemical biosensors for cyanotoxins, (viii) summary of analytical performance, and (ix) recent advances and future trends. Discussion includes electrochemical techniques and devices, biomolecules with high affinity, numerous array designs, various detection approaches, and research strategies in tailoring the properties of the transducer-biomolecule interface. Scientific and engineering aspects are presented in depth. This review aims to serve as a valuable source to scientists and engineers entering the interdisciplinary field of electrochemical biosensors for detection of cyanotoxins in freshwaters.