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\nHIGHLIGHTSAt the end of the summer of 2023, in September, an intense water discolouration (red tide) accompanied by fish mortality was observed in the Gulf of Tadjoura. This discolouration of the seawater was caused by a potentially toxic dinoflagellate, Pyrodinium bahamense. The proliferation, located near the coast between the Moucha/Maskali islands and the city of Tadjoura, was significant enough to be detected by satellite imagery. P. bahamense had formed an almost monospecific bloom (90%), with a density of 1.8 × 106 cells l‒1 (22 September 2023). Other dinoflagellates such as Dinophysis miles, Dinophysis caudata, Tripos furca, Lingulaulax sp. (formerly Lingulodinium), Balechina sp. and Protoperidinium sp. were detected at very low concentrations. This study characterises P. bahamense through an integrated approach, combining detailed morphological analysis with molecular phylogenetic analyses based on the internal transcribed spacer (ITS) region and the D1–D3 regions of large subunit ribosomal (LSU rDNA). For the first time, we have molecularly identified the toxic ribotype from the Indo-Pacific in the Gulf of Aden region. This discovery highlights an emerging risk of this toxic ribotype in the eastern Mediterranean basin. This region, already facing various environmental challenges, may see its vulnerability heightened with the emergence of new risks. A red tide was formed in September 2023 by Pyrodinium bahamense.First morpho-molecular identification of P. bahamense in the Gulf of Aden.The genotype corresponded to the toxic ribotype and the Indo-Pacific ribotype.A red tide was formed in September 2023 by Pyrodinium bahamense.First morpho-molecular identification of P. bahamense in the Gulf of Aden.The genotype corresponded to the toxic ribotype and the Indo-Pacific ribotype. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) can release cyanotoxins such as microcystins (MCs), especially, microcystin-leucine-arginine (MC-LR) which is one of the commonest and most toxic, into our water bodies and can lead to several acute or chronic diseases such as liver diseases and respiratory irritation in humans. There is an increasing need for rapid and simple detection of MC-LR in water bodies for early warning of HABs. In this study, we developed an innovative on-site screening electrochemical impedance spectroscopy (EIS) biosensor with a simplified calibration curve that can rapidly detect blooms for early action in similar water bodies. The novel aspect of this research is that various chemical cleaning procedures and surface modifications were evaluated to improve the antibody-embedded electrochemical sensor performance. In addition, a simplified calibration curve was constructed from different water samples to reduce the need for frequent recalibration in practical applications. In this study, two distinct commercially available screen-printed carbon electrodes (SPCEs) were modified as a cost-effective substrate for MC-LR biosensing with anti-MC-LR/MC-LR/cysteamine-coating. The study showed that an appropriate cleaning procedure might minimize the sensor performance difference after each electrode modification. The biosensor showed excellent sensitivity toward MC-LR detection in lake water samples with a limit of detection (LOD) of 0.34 ngL-1. The simplified calibration curve was developed and used to predict unknown MC-LR concentrations in several lake water samples with a relative standard deviation (RSD) of 1.0–4.4% and a recovery of 75–112%, indicating the suitability of the developed biosensor and a streamlined calibration curve for rapid MC-LR measurements for different water bodies with similar water quality. This approach can therefore reduce the need for frequent calibration efforts and can be employed as the first line of testing for MC-LR in drinking and recreational water sources, especially in emergencies. [ABSTRACT FROM AUTHOR]

Fjords are known for their biodiversity and abundant aquaculture resources. However, climate and anthropogenic pressures are altering fjord biological, physical, and chemical processes that will undoubtedly change the ecosystem as a whole. To investigate the impact of climate change on fjord functioning, this study examines the impacts of drought conditions on the physical dynamics and salinity variations in a fjord known for its bolstering aquaculture industry in Northern Chilean Patagonia, the Reloncaví Fjord (41.5° S). Using a high-resolution hydrodynamic model and the Total Exchange Flow (TEF) framework, we analyzed the impacts of river discharge, tides, and wind during a dry year (2016) and a typical year (2018). In 2016, reduced freshwater input decreased exchange flow and increased salinity compared to 2018. In 2018, river discharge dominated TEF variability (74%), while tides and wind contributed 17% and 9%, respectively. In summer 2016, tidal and wind influences rose to 21% and 16%, highlighting their role under low freshwater conditions. Increased wind facilitated destratification, mixing high-salinity subsurface waters with fresh surface layers, affecting ecosystem dynamics. From these results we developed a method to predict long-term stratification variability (1980–2021), identifying critical ecological shifts. Logistic regression models showed significant links between stratification levels and harmful algal blooms (HABs) of Pseudchatonella spp. and Alexandrium catenella. Lower stratification was linked to higher Pseudchatonella spp. HABs in summer, while higher stratification correlated with Alexandrium catenella blooms in spring, tied to increased river discharge. These results suggest that severe HAB events in Northern Patagonia may become more frequent with climate change, underscoring the need to consider local environmental dynamics and stratification in HAB studies. [ABSTRACT FROM AUTHOR]

Algal blooms of Karenia brevis produce brevetoxins that lead to the natural phenomenon of red tide. Beyond monitoring the red tide concentration and forecasting future outbreaks, uncertainty exists in the field when examining these toxins in relation to the physiology of people. Contaminated air that results from outbreaks of K. brevis leads to inhalation of aerosolized brevetoxins, which directly impact the human respiratory system. This scoping review focused on the respiratory effects of red tide and was conducted by using a comparative method between 2 researchers. Relevant abstracts were collected, and full-text articles were reviewed by using PubMed, Science Direct, CINAHL Complete, and BioMed Central databases. Thirty articles were included in the final analysis and categorized by study design, location, and number and age of participants, and were also divided into assessment by respiratory effects, exposure, measurements of K. brevis, and asthma. The research indicates that respiratory health issues exist and can be compounded with exposure to red tide, specifically upper respiratory symptoms. Both symptomatic issues and pulmonary function tests were of concern when individuals were subjected to brevetoxin exposure. Even low levels of K. brevis resulted in negative respiratory health effects. Red tide is common in many areas of the world. The toxins released can cause adverse respiratory effects. This article provides a comprehensive summary of the scholarly literature focused on the respiratory system and red tide produced by K. brevis. [ABSTRACT FROM AUTHOR]

Transfers of energy and nutrients from producers to consumers are fundamental to ecosystem structure and functioning. A common example is the transfer of essential amino acids and fatty acids, produced by phototrophs, up through successive trophic levels. A highly specialised example is the transmission of acquired phototrophy between certain plankton. There are > 250 species of marine plankton that exploit acquired phototrophy; the Teleaulax-Mesodinium-Dinophysis (TMD) trinity is the most studied complex. In the TMD-trinity, plastids and nuclear material produced by the cryptophyte Teleaulax are transferred during feeding to the ciliate, Mesodinium and these acquired plastids are subsequently transferred from Mesodinium to its predator, the dinoflagellate Dinophysis. These plastidic non-constitutive mixoplankton, Mesodinium and Dinophysis, are globally ubiquitous and ecologically important organisms. Mesodinium can form red-tide blooms, while Dinophysis spp. cause diarrhetic shellfish poisoning events and shellfisheries closures. However, very little is known about the impact of different environmental stressors on the transmissions of acquired phototrophy, the subsequent decay of that phototrophic potential over time, and the implications for community trophic dynamics. Here, for the first time, the implications of the transmission dynamics of acquired phototrophy for the success of the TMD-trinity were explored under different nitrogen and phosphorus (N:P) nutrient ratios and loadings (eutrophic, mesotrophic, oligotrophic). Using a multi-nutrient simulator, bloom dynamics were shown to be markedly different under these scenarios, highlighting the importance of variable stoichiometry in community ecology. Importantly, dynamics were sensitive to the longevity (half-life) of the acquired phototrophy (especially for Dinophysis at low nutrient high N:P), a feature for which appropriate empirical data are lacking. This work highlights the need to enhance our understanding about how environmental stressors arising from anthropogenic activities (including climate change) will impact transference of acquired phototrophy between trophic levels and thence marine biodiversity and ecosystem services. [ABSTRACT FROM AUTHOR]

Blooms of Gymnodinium catenatum have occurred occasionally in different areas of China and caused tremendous economic loss and even threatened human health. Not only is G. catenatum an important harmful-algal-bloom (HAB)-causing species, but also the only gymnodinioid dinoflagellate known to produce paralytic shellfish poisoning toxins (PSTs). Due to the germination of resting cysts, which often initiates blooms, the distribution and abundance of cysts in sediments and particularly the confirmation of cyst beds are important information for understanding and predicting dinoflagellate blooms. In this research, 199 sediment samples were collected from China's coastal seas, ranging from the Beidaihe in the Bohai Sea (BS) to the southernmost sample from the Nansha Islands of the South China Sea (SCS). TaqMan quantitative PCR (qPCR) assays with species-specific primers and probes were developed to specifically detect the distribution and abundance of cysts in the 199 samples. The detection revealed that G. catenatum cysts were widely present in the sediments (126 of the 199 samples), with 93.55%, 74.65%, 42.37%, and 50% of the samples detected positively from the BS, YS, ECS and SCS, respectively, and covering the vast sea area from Nansha Islands to the Beidaihe area. The single-cyst morpho-molecular identification in the samples from Beidaihe confirmed the existence of G. catenatum cysts in the BS, and the positive detections of G. catenatum cysts using the qPCR methods. While G. catenatum cysts were widely distributed in all four seas of China, the average abundance was relatively low (1.0 cyst per gram of wet sediment). Three samples from the East China Sea (ECS), however, contained G. catenatum cysts at a relatively higher level (23 cysts g−1 wet sediment) than other sea areas, suggesting a pertinence of cyst abundance to the frequent occurrences of G. catenatum blooms in the area during recent years. Collectively, for G. catenatum being such an important toxic and HAB-causing species globally, the ubiquitous distribution of its cysts along the coastal waters of China and higher abundance in the bloom-prone areas warns us of a risk that cyst beds, although currently low in abundance, may seed HABs in any and many sea areas of China at any forthcoming year, and particularly those areas with records of frequent HABs outbreaks in the past. [ABSTRACT FROM AUTHOR]

Beibu Gulf is an important semi-enclosed bay located in the northwestern South China Sea, and is famous for its high bio-productivity and rich bio-diversity. The fast development along the Beibu Gulf Economical Rim has brought pressure to the environment, and algal blooms occurred frequently in the gulf. In this study, surface water samples and micro-plankton samples (20-200 µm) were collected in the northern Beibu Gulf coast. Diversity and distribution of eukaryotic planktonic microalgae were analyzed by both metabarcoding and microscopic analyses. Metabarcoding revealed much higher diversity and species richness of microalgae than morphological observation, especially for dinoflagellates. Metabarcoding detected 144 microalgal genera in 8 phyla, while microscopy only detected 40 genera in 2 phyla. The two methods revealed different microalgal community structures. Dinoflagellates dominated in microalgal community based on metabarcoding due to their high copies of 18 s rRNA gene, and diatoms dominated under microscopy. Altogether 48 algal bloom and/or toxic species were detected in this study, 34 species by metabarcoding and 19 species by microscopy. Our result suggested a high potential risk of HABs in the Beibu Gulf. Microalgal community in the surface water samples demonstrated significantly higher OTU/species richness, alpha diversity, and abundance than those in the micro-plankton samples, although more HAB taxa were detected by microscopic observations in the micro-plankton samples. Furthermore, nano-sized taxa, such as those in chlorophytes, haptophytes, and chrysophyceans, occurred more abundantly in the surface water samples. This study provided a comprehensive morphological and molecular description of microalgal community in the northern Beibu Gulf. [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 escalating proliferation of cyanobacteria poses significant taste and odor (T/O) challenges, impacting freshwater ecosystems, public health, and water treatment costs. We examined monthly variations in four T/O compounds from September 2011 to August 2012 in Chaohu Lake's eastern drinking water source (DECL). More importantly, we compared the reported T/O occurrence and the related factors in freshwater bodies worldwide. The assessment of T/O issues indicated a severe and widespread problem, with many cases surpassing odor threshold values. Remarkably, China reported the highest frequency and severity of odor-related problems. A temporal analysis revealed variations in odor occurrences within the same water body across different years, emphasizing the need to consider high values in all seasons for water safety. Globally, T/O issues were widespread, demanding attention to variations within the same water body and across different layers. Algae were crucial contributors to odor compounds, necessitating targeted interventions due to diverse odorant sources and properties. A correlation analysis alone lacked definitive answers, emphasizing the essential role of further validation, such as algae isolation. Nutrients are likely to have influenced the T/O, as GSM and MIB correlated positively with nitrate and ammonia nitrogen in DECL, resulting in proposed control recommendations. This study offers recommendations for freshwater ecosystem management and serves as a foundation for future research and management strategies to address T/O challenges. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) are on the rise worldwide. Known drivers for the proliferation and intensification of HAB events include increasing nutrient pollution, climate change, regulation and modification of hydrological flow, and the combined effect of climate drivers and nutrient pollution. The San Francisco Bay–Delta system has largely been immune to severe or acute HAB events, but there is both a potential and realized threat which has been underestimated and under-reported, in part because of the lack of coordinated sampling and data reporting. There is also increasing evidence that HABs must be considered in the context of a freshwater-to-marine continuum, and that the physical and political boundaries separating components of the Bay–Delta system are porous barriers to HABs and their toxins. Much remains to be learned about the ecology and physiology of HAB organisms in this system, but five primary environmental drivers can be identified: temperature, salinity, irradiance, nutrients, and stratification/residence time. All these drivers are responding rapidly to climate change, but nutrients are the primary variable that is largely under human control. Plans for the development of a comprehensive monitoring, prediction, and mitigation strategy across the freshwater-to-marine continuum have been documented; effectively following through on these plans provides a roadmap toward identifying the drivers and threats—and reducing the potential consequences now and in the future. While HABs alone are not a sufficient motivator for potentially costly and extensive mitigation efforts, there is strong evidence that decreasing nutrient loads, maintaining hydrological connectivity while minimizing stagnant regions, and managing the biota to maintain biodiversity of the Bay–Delta system will result in multiple co-benefits, including reduction of the HAB threat potential.

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]

Harmful blooms of the marine dinoflagellate Kai·enia brevis form over the West Florida Shelf in the Gulf of Mexico and can be transported toward the coast of southwest Florida by currents and winds nearly annually. Once on the coast. blooms can be intensified by multiple factors including anthropogenic land-based nitrogen loads. This study investigates the relationship between two management endpoints: land-based nitrogen loads and the duration of red tide events. For the purposes of this effort. a red tide event was defined as a period exhibiting maximum daily K brevis cell counts >100.000 cells/L or > 10.000 cells/'L for at least 30 days within the study area-between Estero Bay and Sarasota Bay-and considered total nitrogen (TN) loads from the Myakka. Peace (inclusive of Horse Creek and Joshua Creek). and Caloosahatchee Rivers occurring within 130 days of the onset of red tide events. TN loads from the Caloosaliatchee Rii·er exhibited statistically significant correlations with red tide ej·ent duration (under both definitions of a red tide event) whereas TN loads from the Peace and Myakka Rivers did not exhibit such correlations. The results suggest that policy and management efforts to reduce nitrogen loading may substantially reduce the duration of red tide events in southwest Florida. [ABSTRACT FROM AUTHOR]

Shellfish aquaculture farms, due to their coastal position, face the threat of exposure to harmful algal blooms. Such blooms can release, among others, paralytic shellfish toxins (PST) produced by the dinoflagellate Alexandrium catenella and are known to cause the restriction of bivalve harvesting sites. Shellfish can accumulate PSTs in levels that are poisonous for humans, therefore making them unfit for consumption. Thus, the ability to detect PSTs before they reach the critical threshold is crucial for minimizing losses in the industry. Previous studies have demonstrated that toxic algae detection is possible with the use of an early warning system based on the valve-gaping behaviour of blue mussel Mytilus edulis. However, some studies observed the presence of toxin resistance in other species of bivalves when they are regularly exposed to PSTs. If no resistance is observed whatever the past history of the populations would be with regard to PST exposure, this species could be appropriate as a sentinel candidate. In this study, we compare the valve-gaping behaviour of two blue mussel populations with contrasting long-term histories of PSTs events (i.e., regularly vs. not previously exposed to the PSTs producer) were compared using experimental exposure of A. catenella to M. edulis. It was found that mussels from both populations exhibited similar gaping behaviour patterns when exposed to A. catenella. For both populations, the number of valve closures and closure duration tended to increase in the presence of A. catenella, which suggested an avoidance response to the toxic dinoflagellate. In conclusion, our results support the use of M. edulis without origin discrimination

Remote sensing is often used to detect algae, but standard techniques do not provide information on the types of algae present or their potential to form a harmful algal bloom (HAB). We developed a framework for identifying algal genera based on reflectance: SMASH, short for Spectral Mixture Analysis for Surveillance of HABs. The Software Application for SMASH (SAS) was developed in MATLAB and makes use of a Multiple Endmember Spectral Mixture Analysis (MESMA) algorithm implemented in Python but packaged as a standalone executable. SAS includes functions for importing hyperspectral images, resampling spectral libraries, evaluating endmember spectral separability, performing MESMA, and generating various output data products.

Blooms of Gymnodinium catenatum have occurred occasionally in different areas of China and caused tremendous economic loss and even threatened human health. Not only is G. catenatum an important harmful-algal-bloom (HAB)-causing species, but also the only gymnodinioid dinoflagellate known to produce paralytic shellfish poisoning toxins (PSTs). Due to the germination of resting cysts, which often initiates blooms, the distribution and abundance of cysts in sediments and particularly the confirmation of cyst beds are important information for understanding and predicting dinoflagellate blooms. In this research, 199 sediment samples were collected from China’s coastal seas, ranging from the Beidaihe in the Bohai Sea (BS) to the southernmost sample from the Nansha Islands of the South China Sea (SCS). TaqMan quantitative PCR (qPCR) assays with species-specific primers and probes were developed to specifically detect the distribution and abundance of cysts in the 199 samples. The detection revealed that G. catenatum cysts were widely present in the sediments (126 of the 199 samples), with 93.55%, 74.65%, 42.37%, and 50% of the samples detected positively from the BS, YS, ECS and SCS, respectively, and covering the vast sea area from Nansha Islands to the Beidaihe area. The single-cyst morpho-molecular identification in the samples from Beidaihe confirmed the existence of G. catenatum cysts in the BS, and the positive detections of G. catenatum cysts using the qPCR methods. While G. catenatum cysts were widely distributed in all four seas of China, the average abundance was relatively low (1.0 cyst per gram of wet sediment). Three samples from the East China Sea (ECS), however, contained G. catenatum cysts at a relatively higher level (23 cysts g−1 wet sediment) than other sea areas, suggesting a pertinence of cyst abundance to the frequent occurrences of G. catenatum blooms in the area during recent years. Collectively, for G. catenatum being such an important toxic and HAB-causing species globally, the ubiquitous distribution of its cysts along the coastal waters of China and higher abundance in the bloom-prone areas warns us of a risk that cyst beds, although currently low in abundance, may seed HABs in any and many sea areas of China at any forthcoming year, and particularly those areas with records of frequent HABs outbreaks in the past.

Many wild otariids (sea lions and fur seals) strand along the California coast annually with seizures following presumed exposure to harmful algal blooms (HABs). This is a long-term case study of a stranded subadult male Guadalupe fur seal (Arctocephalus townsendi) that stranded in 2001 and within days after admission began demonstrating seizure activity. The epilepsy was stabilized with antiepileptic drug (AED) therapy and advanced imaging was performed. Magnetic resonance (MR) scans showed signs of encephalopathy consistent with domoic acid (DA) toxicosis. This fur seal was deemed “non-releasable” and over the following 19 years, he received supportive veterinary care and AED treatment at a permitted facility. In the summer of 2020, the fur seal showed progressive behavioral and functional deterioration whereupon humane euthanasia was performed. Post-mortem MR and diffusion tensor images (DTI) were acquired. A volumetric comparison with historic scans showed evidence of severe progressive unilateral right hippocampal atrophy. Histopathology confirmed severe chronic right and mild left hippocampal atrophy. The progressive degenerative brain changes demonstrate how adaptive brain function can be with neuronal atrophy secondary to DA exposure. This case highlights some considerations and decision-making processes needed for the rehabilitation and placement of wild stranded otariids with acquired epilepsy secondary to DA toxicity.

The spatiotemporal distribution of harmful algal blooms (HABs) in rivers remains poorly understood, and there is an urgent need to develop a consistent set of metrics to better document HAB occurrences and forecast future events. Using data from seven sites in the Illinois River Basin, we computed metrics focused on HAB conditions related to excess algal growth and hypoxia. Daily mean chlorophyll and dissolved oxygen (DO) concentrations, gross primary productivity (GPP), and net ecosystem productivity (NEP) rates, focused on water quality status, identifying the timing of the transition from a clear-water to an algal dominated state. Early warning indicators (EWIs), the first-order autoregressive process (Ar1) and standard deviation (SD) of chlorophyll concentrations, focused on future events, forecasting blooms. Metrics were compared to either literature-derived or statistical-based thresholds and were normalized by total number of daily samples for an exceedance rate. Exceedances of a daily mean chlorophyll concentration averaged 50 % across all sites using a 10 µg L−1 threshold but increasing the threshold to 50 μg L−1 reduced the average exceedance rate to 5 %. The average exceedance rate for GPP (∼8 g O2 m2d−1 threshold) was 15 %, similar to the daily amplitude DO concentration (∼3 mg L−1 threshold), but the average for NEP (0 g O2 m2 d−1 threshold) was higher, at 28 %. The number of days with at least 1 continuous DO concentration below the threshold of 5, 3, or 2 mg L−1, had basin wide exceedance rates of 9 %, 3 %, and 2 %, respectively. Thresholds for EWIs, Ar1 and SD, were exceeded at 5 of the 7 sites with high chlorophyll concentrations and GPP rates. The correlation between proxies for algal biomass (chlorophyll concentration) and productivity (GPP) was strongest for sites in the middle region of the basin, with R2 values between 0.54 and 0.74. Although, cyanotoxin concentrations are the most commonly used metrics by states to define an inland water HAB, there is a paucity of publicly available data. The wider availability of chlorophyll and oxygen data combined with the results from this study suggest that biomass and productivity state and event-based metrics may be a promising way to assess and predict the vulnerability of rivers to some of the deleterious effects of HABs at broad spatial scales.

Research on interactions between grazers and toxigenic algae is fundamental for understanding toxin dynamics within aquatic ecosystems and developing biotic approaches to mitigate harmful algal blooms. The dinoflagellate Alexandrium minutum is a well-known microalga responsible for paralytic shellfish toxins (PSTs) contamination in many coastal regions worldwide. This study investigated the impact of the ciliate Euplotes balteatus on cell density and PSTs transfer in simulated A. minutum blooms under controlled conditions. E. balteatus exhibited resistance to the PSTs produced by A. minutum with a density of up to 10,000 cells/mL, sustaining growth and reproduction while eliminating algal cells within a few days. The cellular PSTs content of A. minutum increased in response to the grazing pressure from E. balteatus. However, due to the substantial reduction in density, the overall toxicity of the algal population decreased to a negligible level. Most PSTs contained within algal cells were temporarily accumulated in E. balteatus before being released into the water column, suggesting unclear mechanisms for PSTs excretion in unicellular grazers. In principle, the grazing of E. balteatus on A. minutum promotes the transfer of the majority of intracellular PSTs into extracellular portions, thereby mitigating the risk of their accumulation and contamination through marine trophic pathways. However, this process also introduces an increase in the potential environmental hazards posed by extracellular PSTs to some extent.

Hazardous impacts caused by harmful algal blooms (HABs) have facilitated the development of novel effective approaches for controlling the frequent HABs. Recently, bacteria with algicidal effects, as a promising alternative tool for eliminating the HABs-forming species have received wide concerns. In the present study, a marine bacterial strain 6A1 with potent algicidal activity was successfully isolated from a bloom of Akashiwo sanguinea, andthe characteristics related to its algicidal action were systematically investigated. Sequencing results of 16S rDNA suggested that this bacterium belongs to the genus Arenibacter in the family Flavobacteriaceae, while the phylogenetic analysis revealed that Arenibacter sp. strain 6A1 was the only algicidal bacterium in Arenibacter to date, according to the best of our knowledge. Arenibacter sp. strain 6A1 had an extraordinarily high algicidal performance when it was added to A. sanguinea culture with a volume fraction of 1.5% for 2 h. The algicidal performance of strain 6A1 was concentration-dependent and time-dependent. The best algicidal efficacy of strain 6A1 was seen during the stationary phase, while the resistance of A. sanguinea to strain 6A1 declined as the growth cycle progressed. Subsequently, the indirect algicidal mode of Arenibacter sp. strain 6A1 was verified and the algicidal compounds produced by strain 6A1 were proved to be heat-resistant. Further research showed that strain 6A1 caused a severe damage in photosynthesis, oxidative stress, and also damage in three HABs-forming algae to varying degrees. The greatest algicidal performance was found on unarmored dinoflagellate A. sanguinea, followed by raphidophyte Chattonella antiqua and armored dinoflagellate Alexandrium tamarense. The Arenibacter sp. strain 6A1 exhibited selective algicidal activity on a wide range of algal species, primarily targeting Pyrrophyta and Ochrophyta. The proposed bacteria (strain 6A1) can be a powerful and eco-friendly tool for emergency treatment of HABs caused by certain algal species in coastal water bodies. [ABSTRACT FROM AUTHOR]

Remote sensing is often used to detect algae, but standard techniques do not provide information on the types of algae present or their potential to form a harmful algal bloom (HAB). We developed a framework for identifying algal genera based on reflectance: SMASH, short for Spectral Mixture Analysis for Surveillance of HABs. The Software Application for SMASH (SAS) was developed in MATLAB and makes use of a Multiple Endmember Spectral Mixture Analysis (MESMA) algorithm implemented in Python but packaged as a standalone executable. SAS includes functions for importing hyperspectral images, resampling spectral libraries, evaluating endmember spectral separability, performing MESMA, and generating various output data products. [ABSTRACT FROM AUTHOR]

Microcystins (MCs) are toxins produced by cyanobacteria commonly found in harmful algal blooms (HABs). Due to their toxicity to humans and other organisms, the World Health Organization (WHO) sets a guideline of 1 μg L−1 for microcystin-leucine-arginine (MC-LR) in drinking water. However, current analytical techniques for the detection of MC-LR such as liquid chromatography-mass spectrometry (LC-MS) and ELISA are costly, bulky, time-consuming, and mostly conducted in a laboratory, requiring highly trained personnel. An analytical method that can be used in the field for rapid determination is essential. In this study, an anti-MC-LR/MC-LR/cysteamine-coated screen-printed carbon electrode (SPCE) biosensor was newly developed to detect MC-LR, bioelectrochemically, in water. The functionalization of the electrode surface was confirmed with surface characterization methods. The sensor performance was evaluated by electrochemical impedance spectroscopy (EIS), obtaining a linear working range of MC-LR concentrations between 0.1 and 100 μg L−1 with a limit of detection (LOD) of 0.69 ng L−1. Natural water samples experiencing HABs were collected and analyzed using the developed biosensor, demonstrating the excellent performance of the biosensor with a relative standard deviation (RSD) of 0.65%. The interference tests showed minimal error and RSD values against other common MCs and possible coexisting ions found in water. The biosensor showed acceptable functionality with a shelf life of up to 12 weeks. Overall, the anti-MC-LR/MC-LR/cysteamine/SPCE biosensors can be an innovative solution with characteristics that allow for in situ, low-cost, and easy-to-use capabilities which are essential for developing an overarching and integrated "smart" environmental management system. [ABSTRACT FROM AUTHOR]

Shellfish aquaculture farms, due to their coastal position, face the threat of exposure to harmful algal blooms. Such blooms can release, among others, paralytic shellfish toxins (PST) produced by the dinoflagellate Alexandrium catenella and are known to cause the restriction of bivalve harvesting sites. Shellfish can accumulate PSTs in levels that are poisonous for humans, therefore making them unfit for consumption. Thus, the ability to detect PSTs before they reach the critical threshold is crucial for minimizing losses in the industry. Previous studies have demonstrated that toxic algae detection is possible with the use of an early warning system based on the valve-gaping behaviour of blue mussel Mytilus edulis. However, some studies observed the presence of toxin resistance in other species of bivalves when they are regularly exposed to PSTs. If no resistance is observed whatever the past history of the populations would be with regard to PST exposure, this species could be appropriate as a sentinel candidate. In this study, we compare the valve-gaping behaviour of two blue mussel populations with contrasting long-term histories of PSTs events (i.e., regularly vs. not previously exposed to the PSTs producer) were compared using experimental exposure of A. catenella to M. edulis. It was found that mussels from both populations exhibited similar gaping behaviour patterns when exposed to A. catenella. For both populations, the number of valve closures and closure duration tended to increase in the presence of A. catenella, which suggested an avoidance response to the toxic dinoflagellate. In conclusion, our results support the use of M. edulis without origin discrimination [ABSTRACT FROM AUTHOR]

Many wild otariids (sea lions and fur seals) strand along the California coast annually with seizures following presumed exposure to harmful algal blooms (HABs). This is a long-term case study of a stranded subadult male Guadalupe fur seal (Arctocephalus townsendi) that stranded in 2001 and within days after admission began demonstrating seizure activity. The epilepsy was stabilized with antiepileptic drug (AED) therapy and advanced imaging was performed. Magnetic resonance (MR) scans showed signs of encephalopathy consistent with domoic acid (DA) toxicosis. This fur seal was deemed "non-releasable" and over the following 19 years, he received supportive veterinary care and AED treatment at a permitted facility. In the summer of 2020, the fur seal showed progressive behavioral and functional deterioration whereupon humane euthanasia was performed. Post-mortem MR and diffusion tensor images (DTI) were acquired. A volumetric comparison with historic scans showed evidence of severe progressive unilateral right hippocampal atrophy. Histopathology confirmed severe chronic right and mild left hippocampal atrophy. The progressive degenerative brain changes demonstrate how adaptive brain function can be with neuronal atrophy secondary to DA exposure. This case highlights some considerations and decision-making processes needed for the rehabilitation and placement of wild stranded otariids with acquired epilepsy secondary to DA toxicity. [ABSTRACT FROM AUTHOR]

Simple Summary: Recently, the occurrence of harmful algal blooms (HABs) in coastal areas has increased rapidly, negatively impacting fishing resources, public health, and marine ecosystems. Certain microorganisms play a significant role in the termination of HABs. To exploit these algicidal bacteria effectively, it is imperative to amplify their algicidal ratio and devise efficient large-scale cultivation methods; however, research in these areas is underdeveloped. We previously identified Pseudoalteromonas sp. strain FDHY-MZ2, which exhibited significant algicidal activity against Karenia mikimotoi, a species globally acknowledged for forming HAB. To improve the algicidal efficacy of FDHY-MZ2, cultures were progressed from shaking flask conditions to small-scale (5 L) and pilot-scale fermentation (50 L). The optimal fermentation medium and conditions at a pilot-scale level were established, resulting in a substantial improvement in algicidal properties. This enhancement might be due to a rise in algal H2O2 production accompanied by increased cell membrane disintegration, pronounced damage to cell chlorophyll and algal photosynthesis, and severe protein degradation. These findings provide new insights into the previously unknown potential of systematically applied microbial agents for the treatment of HABs. The role of microorganisms in effectively terminating harmful algal blooms (HABs) is crucial for maintaining environmental stability. Recent studies have placed increased emphasis on bio-agents capable of inhibiting HABs. The bacterium Pseudoalteromonas sp. strain FDHY-MZ2 has exhibited impressive algicidal abilities against Karenia mikimotoi, a notorious global HAB-forming species. To augment this capability, cultures were progressively scaled from shake flask conditions to small-scale (5 L) and pilot-scale (50 L) fermentation. By employing a specifically tailored culture medium (2216E basal medium with 1.5% soluble starch and 0.5% peptone), under precise conditions (66 h, 20 °C, 450 rpm, 30 L/min ventilation, 3% seeding, and constant starch flow), a notable increase in algicidal bacterial biomass was observed; the bacterial dosage required to entirely wipe out K. mikimotoi within a day decreased from 1% to 0.025%. Compared to an unoptimized shake flask group, the optimized fermentation culture caused significant reductions in algal chlorophyll and protein levels (21.85% and 78.3%, respectively). Co-culturing induced increases in algal malondialdehyde and H2O2 by 5.98 and 5.38 times, respectively, leading to further disruption of algal photosynthesis. This study underscores the unexplored potential of systematically utilized microbial agents in mitigating HABs, providing a pathway for their wider application. [ABSTRACT FROM AUTHOR]

Abstract Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future.

Dinoflagellates are responsible for most marine harmful algal blooms (HABs) and play vital roles in many ocean processes. More than 90% of dinoflagellates are vitamin B12 auxotrophs and that B12 availability can control dinoflagellate HABs, yet the genetic basis of B12 auxotrophy in dinoflagellates in the framework of the ecology of dinoflagellates and particularly HABs, which was the objective of this work. Here, we investigated the presence, phylogeny, and transcription of two methionine synthase genes (B12-dependent metH and B12-independent metE) via searching and assembling transcripts and genes from transcriptomic and genomic databases, cloning 38 cDNA isoforms of the two genes from 14 strains of dinoflagellates, measuring the expression at different scenarios of B12, and comprehensive phylogenetic analyses of more than 100 organisms. We found that 1) metH was present in all 58 dinoflagellates accessible and metE was present in 40 of 58 species, 2) all metE genes lacked N-terminal domains, 3) metE of dinoflagellates were phylogenetically distinct from other known metE genes, and 4) expression of metH in dinoflagellates was responsive to exogenous B12 levels while expression of metE was not responding as that of genuine metE genes. We conclude that most, hypothetically all, dinoflagellates have either non-functional metE genes lacking N-terminal domain for most species, or do not possess metE for other species, which provides the genetic basis for the widespread nature of B12 auxotrophy in dinoflagellates. The work elucidated a fundamental aspect of the nutritional ecology of dinoflagellates.

Harmful algal blooms (HABs) such as those formed by the ichthyotoxic dinoflagellate, Margalefidinium (aka Cochlodinium) polykrikoides can have adverse effects on bivalves. While M. polykrikoides has caused significant die offs of bivalves and other marine organisms, the Northern quahog or hard clam, Mercenaria mercenaria, is comparatively more resistant to this HAB. This study quantified clearance rates of juvenile hard clams (10-20 mm) exposed to three different North American populations of M. polykrikoides (bloom, strain CP1, strain CPSB-1G) as well as the nonharmful cryptophyte, Rhodomonas salina and the nonharmful dinoflagellate, Gymnodinium aureolum, in single and mixed algal exposures. Multiple biovolume exposures with M. polykrikoides bloom water and R. salina (1,000, 1,500, 3,000 cells mL-1M. polykrikoides biovolume equivalent) were completed to assess the effects of increasing biomass on hard clam clearance rates and selection. Hard clams opened and actively cleared algal mixtures at and below 1,000 M. polykrikoides cells mL-1. During single species exposures, strain CPSB-1G and R. salina were cleared significantly faster than wild M. polykrikoides populations and strain CP1. During mixed exposures, R. salina was cleared significantly faster than CPSB-1G but not other M. polykrikoides populations and there was no difference between hard clam clearance rates of G. aureolum and R. salina. Clearance rates of M. polykrikoides at ≥1,500 cells mL-1M. polykrikoides/R. salina mixtures were not significantly different than zero unlike clearance of those at 1,000 cells mL-1) bloom densities. Given this, and the documented survival of hard clams during blooms, M. mercenaria may be candidate for aquaculture and restoration in regions prone to HABs caused by M. polykrikoides.

Organic effluent enrichment in water may selectively promote algal growth, resulting in water pollution and posing a threat to the aquatic ecosystem. Recent harmful algal blooms (HABs) incidents have highlighted information gaps that still exist, as well as the heightened need for early detection technology developments. Although previous research has demonstrated the importance of deep learning in the identification of algal genera, it is still a challenge to identify or to develop the best-suited convolution neural network (CNN) model for effective monitoring of bloom-forming algae. In the present study, efficiency of deep learning models (MobileNet V-2, Visual Geometry Group-16 (VGG-16), AlexNet, and ResNeXt-50) have been evaluated for the classification of 15 bloom-forming algae. To obtain a high level of accuracy, different convolution layers with adaptive moment estimation (Adam), root-mean-square propagation (RMSprop) as optimizers with softmax and rectified linear unit (ReLU) as activation factors have been used. The classification accuracies of 40, 96, 98, and 99% have been achieved for MobileNet V-2, VGG-16, AlexNet, and ResNeXt-50 model, respectively. We believe that the ResNeXt-50 has the potential to identify algae in a variety of situations with high accuracy and in real time, regardless of the underlying hardware. Such studies pave the path for future AI-based cleaner technologies associated with phycological studies for a sustainable future. [ABSTRACT FROM AUTHOR]

Favot EJ, Holeton C, DeSellas AM, Paterson AM. 2023. Cyanobacterial blooms in Ontario, Canada: continued increase in reports through the 21st century. Lake Reserv Manage. 39:1–20. The Ontario Ministry of the Environment, Conservation and Parks samples algal composition in response to public reports of suspected algal blooms, which have been tracked since 1994. In a previous analysis, Winter et al. noted a significant increase in the number of reports of confirmed algal blooms dominated by cyanobacteria from 1994 to 2009. Here, we determined that this increasing trend in the yearly number of confirmed cyanobacterial bloom reports (CCBRs) has persisted in Ontario over the intervening decade, to 2019. More than half of CCBRs were from waterbodies on the Precambrian Shield, in the Georgian Bay (5E) ecoregion, known for cottaging and water-based tourism. Data from the Ontario Lake Partner Program (LPP) was used to investigate total phosphorus (TP) concentrations in waterbodies with CCBRs. Approximately 44% of the waterbodies with a CCBR (mean TP 12.99 µg/L, n = 135) had average spring TP concentrations less than 10 µg/L, compared to 64% for LPP waterbodies with no reported or confirmed cyanobacterial blooms (mean TP 9.79 µg/L, n = 918). The most common taxon of cyanobacteria dominating bloom samples in inland waterbodies was Dolichospermum, followed by Aphanizomenon in waterbodies on the Precambrian Shield, and Microcystis in the Mixedwood Plains ecozone in southern Ontario. While an increase in public awareness cannot be ruled out in contributing to the rise in CCBRs across Ontario, the high proportion of cyanobacterial blooms occurring in oligotrophic waterbodies suggests that there may be a link to climate warming, rendering conditions more favorable for these blooms to occur. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) pose serious threats to coastal economies and ecosystems, yet effective monitoring remains challenging due to diverse bloom types and complex environmental conditions. This paper proposes a Mixed Algal Blooms Index (MABI) that uses a new color space to improve HABs detection. By employing Sentinel-2's near-infrared, short-wave infrared, and green bands to calculate tristimulus values—replacing traditional RGB bands—MABI significantly enhances the distinction between algal blooms and water. And an improved grid-based Otsu automatic threshold segmentation algorithm is utilized to extract algal blooms. The inter-class distance is employed as an indicator to compare 14 commonly used algal blooms indices. Validation across nine global sites, covering coastal and inland areas, shows MABI's robustness, with an overall accuracy of 0.98 and a Kappa coefficient of 0.95. Compared to traditional algal bloom indices, the proposed MABI shows notable advantages in detecting blooms, effectively identifying both mixed blooms from multiple algae species and single-species blooms. We also verified the effectiveness of MABI with Landsat-8, and the combination of Landsat and Sentinel-2 imagery is expected to enhance its capability to monitor the full lifecycle of algal blooms. While MABI shows some resistance to thin clouds and shadows, its detection accuracy can still be affected in optically complex waters. Therefore, careful threshold selection or combining with other indices is recommended for comprehensive assessment. This study utilized Google Earth Engine (GEE) for data acquisition, processing, algorithm development, and validation, offering an efficient and reliable tool for accurately monitoring HABs with wide-ranging applications. • Proposes MABI for HABs detection using Sentinel-2 bands in a new color space • Enhances distinction between algal blooms and water via tristimulus values • Validates MABI across nine global sites with high accuracy and Kappa coefficient • Outperforms traditional indices in detecting mixed and single-species blooms • Effective for monitoring algal blooms with Landsat-8 integration potential [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) have been frequently occurred with releasing toxic substances, which typically lead to water quality degradation and health problems for humans and aquatic animals. Hence, accurate quantitative analysis and prediction of HABs should be implemented to detect, monitor, and manage severe algal blooms. However, the traditional monitoring required sufficient expense and labor while numerical models were restricted in terms of their ability to simulate the algae dynamic. To address the challenging issue, this study evaluates the applicability of deep learning to simulate chlorophyll-a (Chl-a) and phycocyanin (PC) with the internet of things (IoT) system. Our research adopted LSTM models for simulating Chl-a and PC. Among LSTM models, the attention LSTM model achieved superior performance by showing 0.84 and 2.35 (µg/L) of the correlation coefficient and root mean square error. Among preprocessing methods, the z-score method was selected as the optimal method to improve model performance. The attention mechanism highlighted the input data from July to October, indicating that this period was the most influential period to model output. Therefore, this study demonstrated that deep learning with IoT system has the potential to detect and quantify cyanobacteria, which can improve the eutrophication management schemes for freshwater reservoirs. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) are on the rise worldwide. Known drivers for the proliferation and intensification of HAB events include increasing nutrient pollution, climate change, regulation and modification of hydrological flow, and the combined effect of climate drivers and nutrient pollution. The San Francisco Bay-Delta system has largely been immune to severe or acute HAB events, but there is both a potential and realized threat which has been underestimated and under-reported, in part because of the lack of coordinated sampling and data reporting. There is also increasing evidence that HABs must be considered in the context of a freshwater-to-marine continuum, and that the physical and political boundaries separating components of the Bay-Delta system are porous barriers to HABs and their toxins. Much remains to be learned about the ecology and physiology of HAB organisms in this system, but five primary environmental drivers can be identified: temperature, salinity, irradiance, nutrients, and stratification/residence time. All these drivers are responding rapidly to climate change, but nutrients are the primary variable that is largely under human control. Plans for the development of a comprehensive monitoring, prediction, and mitigation strategy across the freshwater-to-marine continuum have been documented; effectively following through on these plans provides a roadmap toward identifying the drivers and threats--and reducing the potential consequences now and in the future. While HABs alone are not a sufficient motivator for potentially costly and extensive mitigation efforts, there is strong evidence that decreasing nutrient loads, maintaining hydrological connectivity while minimizing stagnant regions, and managing the biota to maintain biodiversity of the Bay-Delta system will result in multiple co-benefits, including reduction of the HAB threat potential. [ABSTRACT FROM AUTHOR]

Hydrogen peroxide (H2O2) has been shown to efficiently remove toxic microalgae from enclosed ballast waters and brackish lakes. In this study, in vitro experiments were conducted to assess the side effects of mitigating toxic and non-toxic dinoflagellates with H2O2. Five H2O2 concentrations (50 to 1000 ppm) were used to control the cell abundances of the toxic dinoflagellates Alexandrium catenella and Karenia selliformis and the non-toxic dinoflagellates Lepidodinium chlorophorum and Prorocentrum micans. Photosynthetic efficiency and staining dye measurements showed the high efficiency of H2O2 for mitigating all dinoflagellate species at only 50 ppm. In a bioassay carried out to test cytotoxicity using the cell line RTgill-W1, control experiments (only H2O2) showed cytotoxicity in a concentration- and time- (0 to 24 h) dependent manner. The toxic dinoflagellates, especially K. selliformis, showed basal cytotoxicity that increased with the application of hydrogen peroxide. Unexpectedly, the application of a low H2O2 concentration increased toxicity, even when mitigating non-toxic dinoflagellates. This study suggests that the fatty acid composition of toxic and non-toxic dinoflagellate species can yield toxic aldehyde cocktails after lipoperoxidation with H2O2 that can persist in water for days with different half-lives. Further studies are needed to understand the role of lipoperoxidation products as acute mediators of disease and death in aquatic environments. [ABSTRACT FROM AUTHOR]

This study focuses on predicting harmful algal bloom (HAB) events in Lake Okeechobee, a shallow lake in Florida. A spatiotemporal deep learning model is employed to predict the levels of cyanobacteria Microcystis aeruginosa present in the lake for a single-day and a 14-day prediction horizon. Datasets collected from remote sensing (i.e., satellite images from January 2018 to December 2020) and from a physics-based simulation model (i.e., daily simulation from January 2018 to December 2020) are available. Owing to the low quality of remote sensing data caused by various environmental and technical issues, the two available datasets are fused together to create a multisource hybrid dataset for deep learning model training. A convolutional long-short term memory (ConvLSTM) deep neural model is trained on the datasets, and the results of the predictions are compared to the true cyanobacterial index for that time period. Findings include the following: 1) the deep learning model, ConvLSTM, shows promising performance for short- and mid-term HAB forecasting; and 2) the hybrid dataset that fuses remote sensing with physics-based modeling (a.k.a. modeling based on fundamental physical and biogeochemical principles) speeds up the model learning and improves its performance significantly. The proposed methodologies are reliable and cost-effective and could be used to forecast algal bloom occurrences in shallow lakes with limited sparse observations.

Hong Kong has a long historical record of harmful algal blooms (HABs). In the 1980s–1990s, HABs were mainly pollution-related and most of the events happened in estuaries and enclosed embayment such as Tolo Harbour and Port Shelter. The major cause of HABs in 1980s–1990s was closely related to nutrients enrichment; included but not limited to changes in the concentration and ratio of soluble N and P in seawater. The major causative organisms of HABs in Hong Kong by then were meso-plankton such as selected species of diatoms and dinoflagellates. Sometimes, zooplankton was also a cause of red tides (the common name of HABs). There has been gradual change after the 2000s. It is attributed to higher and higher influences from the region, namely the Zhujiang (Pearl) River delta. There are increasing influences from Chinese mainland due to extraordinary social and economic growths during the past 20 years. In the past 10 years, HABs in Hong Kong was mainly subject to regional impacts in the Zhujiang River delta. Both the duration period and covered areas have been enlarged which overwhelmed the localized influences of stream pollution and self-contamination of aquaculture zones. More flagellates of uncommon happening become dominant species in HAB now. Nevertheless, the seasonal impact of Noctiluca scintillans in late winter to mid spring remained. [ABSTRACT FROM AUTHOR]

Heterosigma akashiwo is the only raphidophyte described for Chilean waters. A recent 2021 fish-killing bloom event of this raphidophyte ignited scientific research, but the ichthyotoxic mechanism and environmental conditions that promote its growth are still unclear. This is the first study confirming the occurrence of H. akashiwo in Chilean waters on the basis of the region D1/D2 of the 28S ribosomal gene. The pigment signature of the CREAN_HA03 strain revealed chlorophyll-a, fucoxanthin, and violaxanthin as the most abundant pigments, but profiles were variable depending on culture and field conditions. A factorial temperature–salinity growth experiment showed a maximal growth rate of 0.48 d−1 at 17 °C and 35 in salinity, but reached a maximal cell abundance of ~50,000 cells mL−1 at 12 °C and 25 in salinity. The fatty acid profile included high levels of saturated (16:0) and polyunsaturated (18:4 ω3; 20:5 ω3) fatty acids, but superoxide production in this strain was low (~0.3 pmol O2– cell−1 h−1). The RTgill-W1 bioassay showed that the H. akashiwo strain was cytotoxic only at high cell concentrations (>47,000 cells mL−1) and after cell rupture. In conclusion, salmon mortality during H. akashiwo bloom events in Patagonian fjords is likely explained by the high production of long-chain PUFAs at high cell densities, but only in the presence of high ROS production. [ABSTRACT FROM AUTHOR]

Valvometry is a non-invasive technique used to continuously monitor gaping behaviour of bivalves at high frequency. In previous laboratory studies, valvometry has revealed a behavioural sensitivity of bivalves to the presence of toxic microalgae in seawater. However, the application of valvometry as an early-warning system for detecting natural occurrences of toxic microalgae and their resulting toxicity in bivalves remains largely unexplored. In this study, valvometry was used to characterise changes in blue mussels (Mytilus edulis) gaping behaviour during gradual exposure to the toxic dinoflagellate, Alexandrium catenella, which produces paralytic shellfish toxins (PST). Laboratory experiments were first performed to identify specific gaping behaviour changes and these responses were subsequently validated in natural seawater conditions in a second experiment. Under both laboratory and natural seawater conditions, mussels exposed to A. catenella tended to remain open (yawning) longer than non-exposed mussels. This change in gaping behaviour was observed at PST concentration as low as 30 μg STXeq 100 g–1 of mussel tissue. We suggest that increased opening is likely related to temporary muscular paralysis induced by toxic algae, as this mechanism has been previously reported in other bivalve species. Furthermore, we observed that biological rhythms of valve behaviour related to tidal and daily rhythms were modified when mussels were intoxicated by PSP (Paralytic Shellfish Poisoning). In conclusion, the effects of toxic algae on mussel gaping behaviour reveals that valvometry could be used as an early-warning tool for the presence of toxic Alexandrium sp. in the environment prior to mussels reaching the regulatory threshold (80 μg STXeq 100 g–1) for harvest interdiction.

• Random forest models forecast K. brevis abundance over one- and four-week horizons. • Models were trained on 'live' data to assess performance under realistic conditions. • The one-week and four-week forecasts exhibited 73 % and 84 % accuracy, respectively. • The forecasts correctly predicted bloom onset 80 % and 50 % of the time, respectively. Karenia brevis blooms occur nearly annually along the southwest coast of Florida, and effective mitigation of ecological, public health, and economic impacts requires reliable real-time forecasting. We present two boosted random forest models that predict the weekly maximum K. brevis abundance category across the Greater Charlotte Harbor estuaries over one-week and four-week forecast horizons. The feature set was restricted to data available in near-real time, consistent with adoption of the models as decision-support tools. Features include current and lagged K. brevis abundance statistics, Loop Current position, sea surface temperature, sea level, and riverine discharges and nitrogen concentrations. During cross-validation, the one-week and four-week forecasts exhibited 73 % and 84 % accuracy, respectively, during the 2010–2023 study period. In addition, we assessed the models' reliability in forecasting the onset of 10 bloom events on time or in advance; the one-week and four-week models anticipated the onset eight times and five times, respectively. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) impose major costs on aquatic ecosystems worldwide, including the Laurentian Great Lakes. Microbial consumers, including fungi, can have important interactions with bloom-forming algae and cyanobacteria, although relatively few studies have investigated the relationship between fungi and HABs. We examined changes in the aquatic fungal community coincident with the occurrence of large cyanobacterial blooms in two areas of the Great Lakes (western Lake Erie and Saginaw Bay, Lake Huron). We collected water samples over the course of bloom development, peak, and decline from 3 sites in western Lake Erie on 11 dates and 2 sites in Saginaw Bay on 4 dates. Single molecule sequencing (PacBio RS II) with two molecular markers (the internal transcribed spacer (ITS) of the rRNA locus using fungal-specific primers and the 18S rRNA with primers targeting early-diverging lineages of fungi) was used to estimate fungal community composition. Results indicate a diverse fungal community within the lakes, including several major fungal phyla. The Chytridiomycota were particularly well-represented (54.8% and 45.4% of ITS and 18S sequences, respectively), and we also found representation from both Cryptomycota and Aphelidiomycota, which are putatively obligate intracellular parasites. Further, we found associations between the fungal community (alpha diversity; community composition) and measures of bloom magnitude (chlorophyll a , phycocyanin, and microcystin concentrations) in western Lake Erie. Our results suggest potentially important spatial and temporal heterogeneity in the fungal community that motivates further research on functional importance of fungi in the Great Lakes and consequences for HABs and freshwater ecosystems more broadly. [ABSTRACT FROM AUTHOR]

The harmful algal bloom species, Karenia brevis, forms annual, often intense blooms in the Gulf of Mexico, particularly along the west Florida shelf. Though the ability of K. brevis blooms to cause mass mortalities in juvenile fish are well documented, the direct effect of bloom concentrations on larval fish has not been studied extensively. To better understand the potential effect of K. brevis on larval fish survival, laboratory spawned red porgy (Pagrus pagrus) larvae from 4–26 days post-hatch were exposed to concentrations of K. brevis observed in the field for either 24 or 48 h. This species is representative of fish which spawn in regions of the Gulf of Mexico and whose larvae are epipelagic and may encounter K. brevis blooms. In this study, three different K. brevis strains varying in the amount of brevetoxin produced were tested. Larval survivorship was found to be inversely proportional to the amount of brevetoxin produced by each strain. The EC50 value from the combined 24 h experiments was ~163,000 K. brevis cells L−1, which corresponds to cell concentrations found in moderately dense blooms. Larval mortality also increased substantially in the 48 h versus 24 h exposure treatments. These findings indicate K. brevis blooms have the potential to contribute to natural mortality of fish larvae and further reduce inter-annual recruitment of fishery species whose stocks in the Gulf of Mexico may already be depleted. [ABSTRACT FROM AUTHOR]

Harmful algal blooms (HABs) cause harm to human health or hinder sustainable use of the marine environment in Blue Economy sectors. HABs are temporally and spatially variable and hence their mitigation is closely linked to effective early warning. The European Union (EU) Interreg Atlantic Area project “PRIMROSE”, Predicting Risk and Impact of Harmful Events on the Aquaculture Sector, was focused on the joint development of HAB early warning systems in different regions along the European Atlantic Area. Advancement of the existing HAB forecasting systems requires development of forecasting tools, improvements in data flow and processing, but also additional data inputs to assess the distribution of HAB species, especially in areas away from national monitoring stations, usually located near aquaculture sites. In this contribution, we review different novel technologies for acquiring HAB data and report on the experience gained in several novel local data collection exercises performed during the project. Demonstrations include the deployment of autonomous imaging flow cytometry (IFC) sensors near two aquaculture areas: a mooring in the Daoulas estuary in the Bay of Brest and pumping from a bay in the Shetland Islands to an inland IFC; and several drone deployments, both of Unmanned Aerial Vehicles (UAV) and of Autonomous Surface vehicles (ASVs). Additionally, we have reviewed sampling approaches potentially relevant for HAB early warning including protocols for opportunistic water sampling by coastguard agencies. Experiences in the determination of marine biotoxins in non-traditional vectors and how they could complement standard routine HAB monitoring are also considered.