Harmful Algal Blooms Research Articles

Identification of cyanobacteria overwintering cells and environmental conditions causing growth: Application for preventative management

Abstract Harmful algal blooms (HABs) formed by freshwater cyanobacteria pose risks to human and ecological health globally. Some cyanobacteria form overwintering cells that remain in the sediment during non‐ideal growth conditions and provide an inoculum for HABs during the growing season, perpetuating the cyanobacterial life cycle. Preventative management targeted at decreasing the viability of overwintering cells is an attractive strategy for limiting HAB formation and decreasing risks. However, this approach is novel, and information is needed for sampling, identification and enumeration of overwintering cells in sediments as well as methods for determining if overwintering cells have the potential to contribute to HAB formation. Peer reviewed literature related to these topics are available; yet these data need to be synthesized and placed into the context of management. Therefore, a strategic review was conducted to inform methods and data needs for this preventative strategy. To sample overwintering cells, corers or dredges are used to collect surficial (0–2 cm) sediment layers containing overwintering cells. Identification and enumeration of overwintering cells via light microscopy are aided by dilution, sieving, or density separation of cells from sediment. Incubation studies which simulate environmental conditions triggering akinete germination and cell growth provide evidence of overwintering cell viability. Critical environmental conditions are light (≥0.5 μmol m−2 s−1) and temperature (20–30°C) for triggering akinete germination and growth of quiescent vegetative Microcystis sp. cells, respectively. Limited information was available on the roles of mixing and dissolved oxygen as environmental conditions for germination and growth. Synthesized information can be used to identify potential areas of concern in which overwintering cells are contributing to HABs. Additionally, this information can be used to design incubation studies in which field collected sediments containing overwintering cells are placed in ideal environmental conditions for germination and growth and cyanobacteria transferring to the water column are measured over time. These data inform investigations of areas that are candidates for preventative management and measurements of overwintering cell responses to management.

What's in a name? Political and economic concepts differ in social media references to harmful algae blooms

Policies and management decisions in the marine environment are driven in part by public sentiment which can grow more intense during hazard events like Harmful Algae Blooms (HABs). The public conversations on social media sites like Twitter (before X) reveal the polarized nature of HABs through nuanced language and sentiment. This article uses mixed methods of machine learned topic modeling and inductive qualitative coding to describe the ways the long-term 2017–2019 Karenia brevis “red tide” bloom were politicized across Florida's South West coast. It finds that there are topical differences in keywords related to place (e.g. beach, Florida, coast), agent (individual or organization), and epistemic values (reliance on scientific and/or media reports). These topical differences demonstrate different levels of politicization and partisanship in qualitative analysis. Conceptually, this research demonstrates the ways different dimensions of a long-duration marine hazard can be polarized. Regarding management, this research provides insights to political and organizational stakeholders and the gaps in the discourse shaping marine hazards which can be used to strategically guide future social media engagement to manage politicization.What if all the careful work that resource and environmental managers do can be undone by simple, seemingly uncontroversial words? In an era of increased environmental and marine distress—coupled with short format communication—the ways environmental managers choose their words is crucial, even between ostensibly inconsequential nouns like “red tide” or “algae bloom.” Policies and management decisions in the marine environment are driven in part by public sentiment which can grow more intense during hazard events like Harmful Algae Blooms (HABs). The public conversations on social media sites like Twitter (before X) reveal the polarized nature of HABs through nuanced language and sentiment. This article relies on mining social media posts, and uses mixed methods of machine-learned topic modeling and human-driven inductive qualitative coding to describe the ways the long-term 2017–2019 Karenia brevis “red tide” blooms were politicized across Florida's South West coast. It finds that there are topical differences in keywords related to place (e.g. beach, Florida, coast), agent (individual or organization), and epistemic values (reliance on scientific and/or media reports). These topical differences demonstrate different levels of politicization and partisanship in qualitative analysis. Conceptually, this research demonstrates the ways different dimensions of a long-duration marine hazard can be polarized. Regarding management, this research provides insights to political and organizational stakeholders and the gaps in the discourse shaping marine hazards which can be used to strategically guide future social media engagement to manage politicization.

Contributions of temperature and development state to the morphological variation of Ulva prolifera highlight the source management for green tides

Since 2007, the world's largest transregional green tides caused by Ulva prolifera have periodically occurred in China. The morphology of U. prolifera drastically changes during the drifting period, but the reason for this phenomenon has still been under debate. Our results showed that temperature partly explained the changes in the morphology of U. prolifera, with a determining factor of 0.498. The ratio of highly branched thalli decreased as the temperature increased from around 25 to 30 °C. Because morphological changes and physiological acclimation synergistically occurred in floating macroalgae, we hypothesized that if the morphology of U. prolifera is also determined by its development state, and the U. prolifea thalli with different development states should have distinct morphological and physiological traits even under the same environmental conditions. To test the hypothesis, we investigated the photosynthesis of U. prolifera and found a higher photosynthetic capacity but lower photoprotective capacity in algae that grew in the branched development state compared to those in the unbranched development state. Combined with other field observations and lab experiments, we suggest that both temperature and development state contribute to the morphological changes of U. prolifera. Given the varying trends of temperature during U. prolifera blooms in past eleven years and the initial occurrence of U. prolifera thalli in the branched development state in the source of algal bloom, we emphasize the need for source management of green tides.

358 In Vitro Uptake of Harmful Algal Bloom Toxin Microcystin-LR in Human Placental Cells

OBJECTIVES/GOALS: Harmful algal blooms (HABs) are increasing in both frequency and intensity due to climate change. HABs release the toxin microcystin-LR (MC-LR) which enters cells via organic anion-transporting polypeptides (OATPs). In this study, we sought to assess the ability of MC-LR to accumulate in trophoblasts, potentially disrupting placental functions. METHODS/STUDY POPULATION: Intracellular accumulation of MC-LR at exposure concentrations of 0.1, 1, and 10 µM over 6 hrs was evaluated in immortalized JAR placental cytotrophoblasts. Western blotting was used to evaluate protein-bound MC-LR accumulation in JAR cells. The function of OATP transporters in JAR cells was determined by pre-incubating cells with 10µM cyclosporin A, a general OATP inhibitor for 1 hr, and then incubated with 1µM OATP substrate fluorescein for up to 40 min. Fluorescence of fluorescein was measured at Ex/Em: 494nm/515nm by spectrophotometry. RESULTS/ANTICIPATED RESULTS: A concentration-dependent increase of MC-LR bound proteins in JAR cells was observed at 6 hrs with the greatest intracellular accumulation of MC-LR at 10µM. In the transporter experiments, a significant decrease of fluorescein uptake by up to 45% into JAR cells was observed following cyclosporin A inhibition of OATPs. These findings are consistent with the functional expression of OATP transporters in JAR placenta cells. Ongoing studies are evaluating whether the cyclosporin A-mediated inhibition of OATPs also inhibits the uptake of MC-LR. DISCUSSION/SIGNIFICANCE: Although MC-LR is well-known for its hepatotoxic and neurotoxic effects, there is growing interest in examining its potential adverse impacts on female reproductive health, particularly during pregnancy. Active uptake of MC-LR into the placenta could interfere with placental and fetal development.

Comprehensive Insights into Harmful Algal Blooms: A Review of Chemical, Physical, Biological, and Climatological Influencers with Predictive Modeling Approaches

Comprehensive Insights into Harmful Algal Blooms: A Review of Chemical, Physical, Biological, and Climatological Influencers with Predictive Modeling Approaches

Autonomous UAV-Mounted LoRaWAN System for Real-Time Monitoring of Harmful Algal Blooms (HABs) and Water Quality

Autonomous UAV-Mounted LoRaWAN System for Real-Time Monitoring of Harmful Algal Blooms (HABs) and Water Quality

Transformative Ecological and Human Impacts from Diminished Sea Ice in the Northern Bering Sea

Abstract Our goal is to tie climate-scale meteorology to regional physics and ecosystem changes and demonstrate a few resulting impacts to which regional peoples are having to respond in the Alaskan Bering Strait region. The sea ice loss events in the winters of 2017/18 and 2018/19 initiated a series of marine environmental, ecological, and industrial changes through a chain of connected events from jet-stream meanders, storms, southerly winds, warmer sea temperatures, and minimum sea ice cover. Resulting impacts continue as coastal communities respond to ongoing nutritional, cultural, and economic challenges. Global warming potentially initiated these events through a weakened atmospheric Arctic Front. Ecological shifts included a transition/reorganization of the Bering Strait regional marine ecosystem. Subsequent changes included shifts in zooplankton species, increases in large-bodied, predatory fish species moving northward, an ice seal unusual mortality event, and seven consecutive years of multispecies seabird die-offs. These changes in the marine ecosystem create a serious food security concern. Ongoing impacts include large, toxic harmful algal blooms and coastal erosion. Recent changes to the maritime industries of the transboundary waters of the Bering Strait include increased industrial ship traffic, planned development of the Port of Nome, and northward proximity of foreign fishing activity. Projections for the next decades are for an increasing frequency of low sea ice years and continuing ecosystem and industrial transitions that contribute to increasing economic and food security concerns for the 16 coastal communities that compose the Bering Strait region. Significance Statement Extreme events in the atmosphere/oceans and resultant record sea ice minimums in 2018 and 2019 were manifested in marine ecosystem transitions and maritime industry impacts. This led to ongoing concerns over the food safety and food security of marine resources essential to the nutritional, cultural, and economic well-being of Alaskan coastal communities of the Bering Strait region. Persistent weakening of the Arctic Front may signal an increased frequency of low sea ice events into the next decades.

Comparison of Conventional CNN Sequential API and Functional API for Microalgae Identification

Microalgae is widely known for its application in producing biodiesel and other health supplements. However, microalgae are also the leading cause of harmful algae blooms that may affect consumers and sea wildlife. The current microalgae identification method requires professionals, resources, budgets, technologies, and time. Therefore, a novel approach to identifying microalgae has been produced by implementing deep learning, specifically the Convolutional Neural Network (CNN). Due to the blooming of research in the deep learning field for microalgae identification, this research aims to compare application programming interface (API) use and study its effects on the accuracy and loss of a model. Using a light microscope, the microalgae images' datasets are self-collected from the AlBio laboratory at the Malaysia-Japan International Institute of Technology, Universiti Teknologi Malaysia. The microalgae species were Acutodesmus obliquus, Monoraphidium sp, Spirullina sp, Tetradesmus deserticola, and Desmodesmus perforatus. The architecture used to identify the microalgae in this research was the conventional CNN with different APIs, functional and sequential. The functional API resulted in 0.85 accuracies and a loss score of 3.77. On the other hand, the sequential scored 0.89 and a loss of 0.32. This study concluded that the sequential API was better than the functional API for a linear convolutional neural network. However, further improvement to the model could be applied by applying better hyperparameters and parameters to prevent underfitting and improve the model’s accuracy.

Exposure to microplastics renders immunity of the thick-shell mussel more vulnerable to diarrhetic shellfish toxin-producing harmful algae

Despite both microplastics (MPs) and harmful algae blooms (HABs) may pose a severe threat to the immunity of marine bivalves, the toxification mechanism underlying is far from being fully understood. In addition, owing to the prevalence and sudden occurrence characteristics of MPs and HABs, respectively, bivalves with MP-exposure experience may face acute challenge of harmful algae under realistic scenarios. However, little is known about the impacts and underlying mechanisms of MP-exposure experience on the susceptibility of immunity to HABs in bivalve mollusks. Taking polystyrene MPs and diarrhetic shellfish toxin-producing Prorocentrum lima as representatives, the impacts of MP-exposure on immunity vulnerability to HABs were investigated in the thick-shell mussel, Mytilus coruscus. Our results revealed evident immunotoxicity of MPs and P. lima to the mussel, as evidenced by significantly impaired total count, phagocytic activity, and cell viability of haemocytes, which may result from the induction of oxidative stress, aggravation of haemocyte apoptosis, and shortage in cellular energy supply. Moreover, marked disruptions of immunity, antioxidant system, apoptosis regulation, and metabolism upon MPs and P. lima exposure were illustrated by gene expression and comparative metabolomic analyses. Furthermore, the mussels that experienced MP-exposure were shown to be more vulnerable to P. lima, indicated by greater degree of deleterious effects on abovementioned parameters detected. In general, our findings emphasize the threat of MPs and HABs to bivalve species, which deserves close attention and more investigation.

2019–2021年中国近海有毒有害微藻和藻毒素分布数据集

China's coastal waters, including the Bohai Sea, the Yellow Sea, the East China Sea and the South China Sea, are rich in marine resources and of strategic importance to the nation’s economic development. However, in recent years, the problem of water safety caused by algae and algal toxins is becoming more and more serious, with the frequency and scale of harmful algal blooms are escalating in China's coastal waters. This dataset collected and organized the survey data of toxic and harmful microalgae and algal toxins in China's coastal waters from 2019 to 2021, containing 3,429 entries of microalgae data, 33,240 entries of microalgae molecular species data, 489 entries of phytoplankton algal toxin data, 76 entries of seawater algal toxin data and 440 entries of economic species algal toxin data. The research teams providing the data ensured the accuracy of the test data through rigorous inter-project and international collation efforts. In order to display the distribution of toxic and harmful microalgae and algal toxins in China's coastal waters, we included 115 microalgae distribution maps and 29 algal toxin distribution maps in the dataset. This dataset can provide data support for studying the spatial and temporal distribution of toxic and harmful microalgae and algal toxins in China's coastal waters, and offers valuable data support for the prevention, warning and control of harmful algal blooms.

New insights on the spatial and temporal distribution characteristics of Chinese marine environmental quality and its driving factors from 2003 to 2021

As land and sea integration continues to accelerate, it will inevitably have an effect on the marine ecological environment. However, the study on spatial and temporal distribution characteristics of Chinese marine environmental quality and its driving factors was lacking. This paper employs Regression Analysis, Spearman Correlation Analysis, Canonical Correlation Analysis, Boston Consulting Group Matrix and Environmental Kuznets Curve to examine the spatial–temporal distribution characteristics and correlation factors of Chinese jurisdictional sea areas environmental quality. The environmental quality of the waters under China's jurisdiction improved on average from 2003 to 2021, the area of sea with excellent water quality increased by 7.21 × 104 km2. The spatial distribution showed “South superior, North inferior” trend. The accumulated red tide area is 2.01 × 105 km2, and the green tide has the average maximum area of distribution is 3.13 × 104 km2. The marine dumping area's volume of waste has a three stages of slow rise (2003–2007), steady (2008–2014) and rapid rise (2015–2021). The average percentage of seawater bathing areas with good water quality is 82.10 %. Urban Environmental Infrastructure Investment and Urban Drainage Construction Investments are positively correlated with excellent water quality and negatively correlated with light-sewage water quality. The typical correlation for the group “Environmental Quality/Environmental Governance” is 0.911, and the strongest correlation is between excellent water quality and urban drainage construction investment. The typical correlation coefficient for the “Environmental Quality/Socioeconomic” group is 0.960, and the strongest correlation is between excellent water quality and per capita GDP. The Gross Ocean Product, Per Capita GDP, Proportion of Non-agricultural Industries, Year-end Resident Population, and excellent water quality are positively correlated whereas light-sewage water quality is negatively correlated. Liaoning, Tianjin, Shandong and Guangdong shift from high-pollution-low-investment to low-pollution-low-investment model. Shanghai, Zhejiang, Fujian and Hainan maintain high-pollution-low-investment model, Hainan maintains high-pollution-high-investment model. Jiangsu maintains low-pollution-low-investment model. Hebei and Guangxi shift from low-pollution-low-investment to low-pollution-high-investment model. Liaoning, Hebei, Tianjin, Shandong, Guangxi and Shanghai show inverted “N” shape, Jiangsu shows positive “N” shape, Zhejiang and Fujian show monotonic decline shape, Guangdong and Hainan show positive “U” shape. The results could provide valuable suggestions for coastal provinces to accomplish economic development and environmental improvement, which to prevent the old way of “pollution first and treatment later”.

An algorithm for constructing spatial vector data storage based on KD-tree and density estimation

With the widespread application of spatial vector data in various fields, this paper proposes a novel algorithm for constructing spatial vector data storage. The algorithm is based on KD-tree and density estimation techniques, aiming to improve the storage efficiency and query performance of large-scale spatial vector data. The algorithm first efficiently organizes spatial vector data using KD-tree, and then performs density estimation based on the Locality Sensitive Hashing (LSH) algorithm. Algorithm optimizations for spatial partitioning are applied to the KD-tree construction algorithm, reducing the search range during queries and improving retrieval speed. By testing with Green Tide data, the algorithm based on KD-tree and density estimation demonstrates higher query efficiency and better scalability across multiple test datasets. Particularly, when dealing with large-scale datasets characterized by non-uniform data distributions, this algorithm significantly improves data retrieval speed while maintaining low storage overhead.

Pulse Feature-Enhanced Classification of Microalgae and Cyanobacteria Using Polarized Light Scattering and Fluorescence Signals.

Harmful algal blooms (HABs) pose a global threat to the biodiversity and stability of local aquatic ecosystems. Rapid and accurate classification of microalgae and cyanobacteria in water is increasingly desired for monitoring complex water environments. In this paper, we propose a pulse feature-enhanced classification (PFEC) method as a potential solution. Equipped with a rapid measurement prototype that simultaneously detects polarized light scattering and fluorescence signals of individual particles, PFEC allows for the extraction of 38 pulse features to improve the classification accuracy of microalgae, cyanobacteria, and other suspended particulate matter (SPM) to 89.03%. Compared with microscopic observation, PFEC reveals three phyla proportions in aquaculture samples with an average error of less than 14%. In this paper, PFEC is found to be more accurate than the pulse-average classification method, which is interpreted as pulse features carrying more detailed information about particles. The high consistency of the dominant and common species between PFEC and microscopy in all field samples also demonstrates the flexibility and robustness of the former. Moreover, the high Pearson correlation coefficient accounting for 0.958 between the cyanobacterial proportion obtained by PFEC and the cyanobacterial density given by microscopy implies that PFEC serves as a promising early warning tool for cyanobacterial blooms. The results of this work suggest that PFEC holds great potential for the rapid and accurate classification of microalgae and cyanobacteria in aquatic environment monitoring.

Anisotropic Green Tide Patch Information Extraction Based on Deformable Convolution

Green tides are marine disasters caused by the explosive proliferation or high concentration of certain large algae in seawater, which causes discoloration of the water body. Accurate monitoring of its distribution area is highly important for early warning and the protection of marine ecology. However, existing deep learning methods have difficulty in effectively identifying green tides with anisotropic characteristics due to the complex and variable shapes of the patches and the wide range of scales. To address this issue, this paper presents an anisotropic green tide patch extraction network (AGE-Net) based on deformable convolution. The main structure of AGE-Net consists of stacked anisotropic feature extraction (AFEB) modules. Each AFEB module contains two branches for extracting green tide patches. The first branch consists of multiple connected dense blocks. The second branch introduces a deformable convolution module and a depth residual module based on a multiresolution feature extraction network for extracting anisotropic features of green tide patches. Finally, an irregular green tide patch feature enhancement module is used to fuse the high-level semantic features extracted from the two branches. To verify the effectiveness of the AGE-Net model, experiments were conducted on the MODIS Green Tide dataset. The results show that AGE-Net has better recognition performance, with F1-scores and IoUs reaching 0.8317 and 71.19% on multi-view test images, outperforming other comparison methods.

An Improved Data Interpolating Empirical Orthogonal Function Method for Data Reconstruction: A Case Study of the Chlorophyll-a Concentration in the Bohai Sea, China

Chlorophyll-a (chl-a) serves as a key indicator in water quality and harmful algal blooms (HABs) research. While satellite ocean color data have greatly advanced chl-a research and HABs monitoring, missing data caused by cloud cover and other factors limit the spatiotemporal continuity and the utility of remote sensing data products. The Data Interpolating Empirical Orthogonal Function (DINEOF) method, widely used to reconstruct missing values in remote sensing datasets, is open to improvement in terms of computational accuracy and efficiency. We propose an improved method called Concentration-Stratified DINEOF (CS-DINEOF), which uses a coordinate–value correlative data division strategy to stratify the study area into several subregions based on annual average chl-a concentration. The proposed method clusters data points with similar spatiotemporal patterns, allowing for more targeted and effective reconstruction in each sub-dataset. The feasibility and advantage of the proposed method are tested and evaluated in the experiments of chl-a data reconstruction in the water of the Bohai Sea. Compared with the ordinary DINEOF method, the CS-DINEOF method improves the reconstruction accuracy, with an average Root Mean Square Error (RMSE) reduction of 0.0281 mg/m3, and saves computational time by 228.9%. Furthermore, the gap-free images generated from CS-DINEOF are able to illustrate small variations and details of the chl-a distribution in local areas. We can conclude that the proposed CS-DINEOF method is superior in providing significant insights for water quality and HABs studies in the Bohai Sea region.

The Cyclic Imine Core Common to the Marine Macrocyclic Toxins Is Sufficient to Dictate Nicotinic Acetylcholine Receptor Antagonism.

Macrocyclic imine phycotoxins are an emerging class of chemical compounds associated with harmful algal blooms and shellfish toxicity. Earlier binding and electrophysiology experiments on nAChR subtypes and their soluble AChBP surrogates evidenced common trends for substantial antagonism, binding affinities, and receptor-subtype selectivity. Earlier, complementary crystal structures of AChBP complexes showed that common determinants within the binding nest at each subunit interface confer high-affinity toxin binding, while distinctive determinants from the flexible loop C, and either capping the nest or extending toward peripheral subsites, dictate broad versus narrow receptor subtype selectivity. From these data, small spiroimine enantiomers mimicking the functional core motif of phycotoxins were chemically synthesized and characterized. Voltage-clamp analyses involving three nAChR subtypes revealed preserved antagonism for both enantiomers, despite lower subtype specificity and binding affinities associated with faster reversibility compared with their macrocyclic relatives. Binding and structural analyses involving two AChBPs pointed to modest affinities and positional variability of the spiroimines, along with a range of AChBP loop-C conformations denoting a prevalence of antagonistic properties. These data highlight the major contribution of the spiroimine core to binding within the nAChR nest and confirm the need for an extended interaction network as established by the macrocyclic toxins to define high affinities and marked subtype specificity. This study identifies a minimal set of functional pharmacophores and binding determinants as templates for designing new antagonists targeting disease-associated nAChR subtypes.

Microbial Diversity Impacts Non-Protein Amino Acid Production in Cyanobacterial Bloom Cultures Collected from Lake Winnipeg.

Lake Winnipeg in Manitoba, Canada is heavily impacted by harmful algal blooms that contain non-protein amino acids (NPAAs) produced by cyanobacteria: N-(2-aminoethyl)glycine (AEG), β-aminomethyl-L-alanine (BAMA), β-N-methylamino-L-alanine (BMAA), and 2,4-diaminobutyric acid (DAB). Our objective was to investigate the impact of microbial diversity on NPAA production by cyanobacteria using semi-purified crude cyanobacterial cultures established from field samples collected by the Lake Winnipeg Research Consortium between 2016 and 2021. NPAAs were detected and quantified by ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) using validated analytical methods, while Shannon and Simpson alpha diversity scores were determined from 16S rRNA metagenomic sequences. Alpha diversity in isolate cultures was significantly decreased compared to crude cyanobacterial cultures (p < 0.001), indicating successful semi-purification. BMAA and AEG concentrations were higher in crude compared to isolate cultures (p < 0.0001), and AEG concentrations were correlated to the alpha diversity in cultures (r = 0.554; p < 0.0001). BAMA concentrations were increased in isolate cultures (p < 0.05), while DAB concentrations were similar in crude and isolate cultures. These results demonstrate that microbial community complexity impacts NPAA production by cyanobacteria and related organisms.

EDNA metabarcoding reveals biodiversity and depth stratification patterns of dinoflagellate assemblages within the epipelagic zone of the western Coral Sea

BackgroundDinoflagellates play critical roles in the functioning of marine ecosystems but also may pose a hazard to human and ecosystem health by causing harmful algal blooms (HABs). The Coral Sea is a biodiversity hotspot, but its dinoflagellate assemblages in pelagic waters have not been studied by modern sequencing methods. We used metabarcoding of the 18 S rRNA V4 amplicon to assess the diversity and structure of dinoflagellate assemblages throughout the water column to a depth of 150 m at three stations in the Western Coral Sea. Additionally, at one station we compared metabarcoding with morphological methods to optimise identification and detection of dinoflagellates.ResultsStratification of dinoflagellate assemblages was evident in depth-specific relative abundances of taxonomic groups; the greatest difference was between the 5–30 m assemblages and the 130–150 m assemblages. The relative abundance of Dinophyceae (photosynthetic and heterotrophic) decreased with increasing depth, whereas that of Syndiniales (parasitic) increased with increasing depth. The composition of major taxonomic groups was similar among stations. Taxonomic richness and diversity of amplicon sequence variants (ASVs) were similar among depths and stations; however, the abundance of dominant taxa was highest within 0–30 m, and the abundance of rare taxa was highest within 130–150 m, indicating adaptations to specific depth strata. The number of unclassified ASVs at the family and species levels was very high, particularly for Syndinian representatives.ConclusionsDinoflagellate assemblages in open water of the Coral Sea are highly diverse and taxonomically stratified by depth; patterns of relative abundance along the depth gradient reflect environmental factors and ecological processes. Metabarcoding detects more species richness than does traditional microscopical methods of sample analysis, yet the methods are complementary, with morphological analysis revealing additional richness. The large number of unclassified dinoflagellate-ASVs indicates a need for improved taxonomic reference databases and suggests presence of dinoflagellate-crypto and–morphospecies.

Editorial: The impacts of anthropogenic activity and climate change on the formation of harmful algal blooms (HABs) and its ecological consequence

Editorial: The impacts of anthropogenic activity and climate change on the formation of harmful algal blooms (HABs) and its ecological consequence

Harmful blooms caused by dinoflagellates in the Pacific of Guatemala (2019–2022)

Plankton studies in Guatemala are associated with the history of harmful algal blooms (HAB). An important event was observed in 1987, with 193 human poisonings due to shellfish consumption, of which 22 were lethal. The causative organism was Pyrodinium bahamense var. compressum. This species was reported again in November 2019 in the coastal Guatemalan Pacific. The species reached an abundance of 1 × 104 cells/L. In September 2020, the abundance of the Margalefidinium polykrikoides vegetative stage reached 1.24 × 106 cells/L, and its cysts 1.5 × 106 cells/L. Noctiluca scintillans proliferated (the first quantitatively estimated bloom of this species in Guatemala) in November 2020 and March 2021 (up to 1.2 × 106 cells/L). From January to December 2021, monthly monitoring was carried out in front of the Port of Quetzal at three sites (bottle and 25 μm mesh net samples). In April 2022, 11 cases of humans presenting symptoms of paralytic shellfish poisoning (PSP) were recorded in the western sector of the Guatemalan Pacific, in particular, in the municipality of Tiquisate in the department of Escuintla. From May 3 to 27, 2022, a HAB event caused the death of 4 and the poisoning of 34 humans in the departments near Mexico: Retalhuleu (Champerico), San Marcos (Tilapa) and Escuintla (Tiquisate, Buena Vista and Iztapa). The maximum saxitoxin (STX) concentration was determined in Retalhuleu (14,099 MU/100 g); until 7 July 2022, STX continued to be detected in Tilapa and Tiquisate (1,021 MU/100 g). The P. bahamense cells were observed in the stomach contents of the clam Tagelus sp. (Bivalvia: Solecurtidae).