The Okavango Delta region in Botswana experienced exceptionally intense landscape-wide cyanobacterial harmful algal blooms (CyanoHABs) in 2020. In this study, the drivers behind CyanoHABs were determined from thirteen independent environmental variables, including vegetation indices, climate and meteorological parameters, and landscape variables. Annual Land Use Land Cover (LULC) maps were created from 2017 to 2020, with ∼89% accuracy to compute landscape variables such as LULC change. Generalized Additive Models (GAM) and Structural Equation Models (SEM) were used to determine the most important drivers behind the CyanoHABs. Normalized Difference Chlorophyll Index (NDCI) and Green Line Height (GLH) algorithms served as proxies for chlorophyll-a (green algae) and phycocyanin (cyanobacteria) concentrations. GAM models showed that seven out of the thirteen variables explained 89.9% of the variance for GLH. The models showcased that climate variables, including monthly precipitation (8.8%) and Palmer Severity Drought Index- PDSI (3.2%), along with landscape variables such as changes in Wetlands area (7.5%), and Normalized Difference Vegetation Index (NDVI) (5.4%) were the determining drivers behind the increased cyanobacterial activity within the Delta. Both PDSI and NDVI showed negative correlations with GLH, indicating that increased drought conditions could have led to large increases in toxic CyanoHAB activity within the region. This study provides new information about environmental drivers which can help monitor and predict regions at risk of future severe CyanoHABs outbreaks in the Okavango Delta, Botswana, and other similar data-scarce and ecologically sensitive areas in Africa. Plain Language Summary: The waters of the Okavango Delta in Northern Botswana experienced an exceptional increase in toxic cyanobacterial activity in recent years. Cyanobacterial blooms have been shown to affect local communities and wildlife in the past. To determine the drivers behind this increased bloom activity, we analyzed the effects of thirteen independent environmental variables using two different statistical models. Within this research, we focused on vegetation indices, meteorological, and landscape variables, as previous studies have shown their effect on cyanobacterial activity in other parts of the world. While driver determination for cyanobacteria has been done before, the environmental conditions most important for cyanobacterial growth can be specific to the geographic setting of a study site. The statistical analysis indicated that the increases in cyanobacterial bloom activity within the region were mainly driven by persistent drier conditions. To our knowledge, this is the first study to determine the driving factors behind cyanobacterial activity in this region of the world. Our findings will help to predict and monitor areas at risk of future severe cyanobacterial blooms in the Okavango Delta and other similar African ecosystems.

Clay-algae flocculation is a promising method to remove harmful algal blooms (HABs) in aquatic ecosystems. Many HAB-generating species, such as Microcystis aeruginosa (M. aeruginosa), a common species in lakes, produce toxins and harm the environment, human health, and the economy. Natural clays, such as bentonite and kaolinite, and modification of these clays have been applied to mitigate HABs by forming large aggregates and settling down. In this study, we aim to examine the impact of laponite, a commercially available smectite clay that is synthetic, transparent, compatible with human tissues, and degradable, on removing HABs. We compare the cell removal efficiencies (RE) of laponite, two natural clays, and their polyaluminum chloride (PAC)-modified versions through clay-algae flocculation experiments. Our results show that the optimum concentrations of laponite, bentonite, kaolinite, PAC-modified bentonite, and PAC-modified kaolinite to remove 80 % of the M. aeruginosa cells from the water column are 0.05 g/L, 2 g/L, 4 g/L, 2 g/L and 0.3 g/L respectively. Therefore, to achieve the same cell removal efficiency, the amount of laponite needed is 40 to 80 times less than bentonite and kaolinite, and 6 times less than PAC-modified kaolinite. We demonstrate that the superior performance of laponite clay is because of its smaller particle size, which increases the encounter rate between cells and clay particles. Furthermore, experiments using water samples from Powderhorn Lake confirmed laponite\'s effectiveness in mitigating HABs. Our price analysis also suggests that this commercially-available clay, laponite, can be used in the field at a relatively low cost.

In May-June 2019, the microalga Chrysochromulina leadbeateri caused a massive fish-killing event in several fjords in Northern Norway, resulting in the largest direct impact ever on aquaculture in northern Europe due to toxic algae. Motivated by the fact that no algal toxins have previously been described from C. leadbeateri, we set out to investigate the chemical nature and toxicity of secondary metabolites in extracts of two strains (UIO 393, UIO 394) isolated from the 2019 bloom, as well as one older strain (UIO 035) isolated during a bloom in Northern Norway in 1991. Initial LC-DAD-MS/MS-based molecular networking analysis of the crude MeOH extracts of the cultivated strains showed that their profiles of small organic molecules, including a large number of known lipids, were very similar, suggesting that the same class of toxin(s) were likely the causative agents of the two harmful algal bloom (HAB) events. Next, bioassay-guided fractionation using the RTgill-W1 cell line and metabolomics analysis pointed to a major compound affording [M + H]+ ions at m/z 1399.8333 as a possible toxin, corresponding to a compound with the formula C67H127ClO27. Moreover, our study unveiled a series of minor analogues exhibiting distinct patterns of chlorination and sulfation, together defining a new family of compounds, which we propose to name leadbeaterins. Remarkably, these suspected toxins were detected in situ in samples collected during the 2019 bloom close to Tromsø, thereby consistent with a role in fish kills. The elemental compositions of the putative C. leadbeateri ichthyotoxins strongly indicate them to be long linear polyhydroxylated polyketides, structurally similar to sterolysins reported from a number of dinoflagellates.

Algal blooms can threaten human health if cyanotoxins such as microcystin are produced by cyanobacteria. Regularly monitoring microcystin concentrations in recreational waters to inform management action is a tool for protecting public health; however, monitoring cyanotoxins is resource- and time-intensive. Statistical models that identify waterbodies likely to produce microcystin can help guide monitoring efforts, but variability in bloom severity and cyanotoxin production among lakes and years makes prediction challenging. We evaluated the skill of a statistical classification model developed from water quality surveys in one season with low temporal replication but broad spatial coverage to predict if microcystin is likely to be detected in a lake in subsequent years. We used summertime monitoring data from 128 lakes in Iowa (USA) sampled between 2017 and 2021 to build and evaluate a predictive model of microcystin detection as a function of lake physical and chemical attributes, watershed characteristics, zooplankton abundance, and weather. The model built from 2017 data identified pH, total nutrient concentrations, and ecogeographic variables as the best predictors of microcystin detection in this population of lakes. We then applied the 2017 classification model to data collected in subsequent years and found that model skill declined but remained effective at predicting microcystin detection (area under the curve, AUC ≥ 0.7). We assessed if classification skill could be improved by assimilating the previous years\' monitoring data into the model, but model skill was only minimally enhanced. Overall, the classification model remained reliable under varying climatic conditions. Finally, we tested if early season observations could be combined with a trained model to provide early warning for late summer microcystin detection, but model skill was low in all years and below the AUC threshold for two years. The results of these modeling exercises support the application of correlative analyses built on single-season sampling data to monitoring decision-making, but similar investigations are needed in other regions to build further evidence for this approach in management application.

Dinoflagellates within the genus Karenia are well known for their potential to cause harmful algal blooms and induce detrimental ecological consequences. In this study, five Karenia species, Karenia longicanalis, Karenia papilionacea, Karenia mikimotoi, Karenia selliformis, and a new species, Karenia hui sp. nov., were isolated from Chinese coastal waters. The new species exhibits the typical characteristics of the genus Karenia, including a linear apical groove and butanoyl-oxyfucoxanthin as the major accessory pigment. It is distinguished from the other Karenia species by a wide-open sulcal intrusion onto the epicone, a conical epicone with an apical crest formed by the rim of the apical groove, and a hunchbacked hypocone. It is most closely related to Karenia cristata, with a genetic divergence of 3.16 % (22 bp out of 883 bp of LSU rDNA). Acute toxicity tests indicated that the five Karenia species from China are all toxic to marine medaka Oryzias melastigma. Karenia selliformis and K. hui were very toxic to O. melastigma, resulting in 100 % mortality within 4 h and 24 h, respectively. Further analysis by high-performance liquid chromatography revealed that four species, K. selliformis, K. longicanalis, K. papilionacea and K. mikimotoi were capable of producing Gymnodimine-A (GYM-A). The highest GYM-A content was in K. selliformis (strain HK-43), in which the value was 889 fg/cell. No GYM-A was detected in the new species K. hui, however and its toxin remains unknown. Below we provide a comprehensive report of the morphology, phylogeny, pigment composition, and toxicity profiles of Karenia species along the Chinese coast. These findings contribute new insights for monitoring of Karenia species, with important toxicological and ecological implications.

Fast environmental changes and high coastal human pressures and impacts threaten the Mediterranean Sea. Over the last decade, recurrent blooms of the harmful dinoflagellate Ostreopsis cf. ovata have been recorded in many Mediterranean beaches. These microalgae produce toxins that affect marine organisms and human health. Understanding the environmental conditions that influence the appearance and magnitude of O. cf. ovata blooms, as well as how climate change will modify its future distribution and dynamics, is crucial for predicting and managing their effects. This study investigates whether the spatio-temporal distribution of this microalga and the frequency of its blooms could be altered in future climate change scenarios in the Mediterranean Western basin. For the first time, an ecological habitat model (EHM) is forced by physico-chemical climate change simulations at high-resolution, under the strong greenhouse gas emission trajectory (RCP8.5). It allows to characterize how O. cf. ovata may respond to projected conditions and how its distribution could shift over a wide spatial scale, in this plausible future. Before being applied to the EHM, future climate simulations are further refined by using a statistical adaptation method (Cumulative Distribution Function transform) to improve the predictions robustness. Temperature (optimum 23-26 °C), high salinity (>38 psu) and high inorganic nutrient concentrations (nitrate >0.25 mmol N·m-3 and phosphate >0.035 mmol P·m-3) drive O. cf. ovata abundances. High spatial disparities in future abundances are observed. Namely, O. cf. ovata abundances could increase on the Mediterranean coasts of France, Spain and the Adriatic Sea while a decrease is expected in the Tyrrhenian Sea. The bloom period could be extended, starting earlier and continuing later in the year. From a methodological point of view, this study highlights best practices of EHMs in the context of climate change to identify sensitive areas for current and future harmful algal blooms.

Phycosphere bacteria can regulate the dynamics of different algal blooms that impact marine ecosystems. Phaeocystis globosa can alternate between solitary free-living cells and colonies and the latter morphotype is dominate during blooms. The mechanisms underlying the formation of these blooms have received much attention. High throughput sequencing results showed that the bacterial community composition differed significantly between colony and solitary strains in bacterial composition and function. It was found that the genera SM1A02 and Haliea were detected only among the colony strains and contribute to ammonium accumulation in colonies, and the genus Sulfitobacter was abundant among the colony strains that were excellent at producing DMS. In addition, the bacterial communities of the two colony strains exhibited stronger abilities for carbon and sulfur metabolism, energy metabolism, vitamin B synthesis, and signal transduction, providing inorganic and organic nutrients and facilitating tight communication with the host algae, thereby promoting growth and bloom development.

Harmful algal blooms (HABs) or higher levels of de facto water reuse (DFR) can increase the levels of certain contaminants at drinking water intakes. Therefore, the goal of this study was to use multi-class supervised machine learning (SML) classification with data collected from six online instruments measuring fourteen total water quality parameters to detect cyanobacteria (corresponding to approximately 950 cells/mL, 2900 cells/mL, and 8600 cells/mL) or DFR (0.5, 1 and 2 % for wastewater effluent) events in the raw water entering an intake. Among 56 screened models from the caret package in R, four (mda, LogitBoost, bagFDAGCV, and xgbTree) were selected for optimization. mda had the greatest testing set accuracy, 98.09 %, after optimization with 7 false alerts. Some of the most important water parameters for the different models were phycocyanin-like fluorescence, UVA254, and pH. SML could detect algae blending events (estimated <9000 cells/mL) due in part to the phycocyanin-like fluorescence sensor. UVA254 helped identify higher concentrations of DFR. These results show that multi-class SML classification could be used at drinking water intakes in conjunction with online instrumentation to detect and differentiate HABs and DFR events. This could be used to create alert systems for the water utilities at the intake, rather than the finished water, so any adjustment to the treatment process could be implemented.

The catastrophic loss of aquatic life in the Central European Oder River in 2022, caused by a toxic bloom of the haptophyte microalga Prymnesium parvum (in a wide sense, s.l.), underscores the need to improve our understanding of the genomic basis of the toxin. Previous morphological, phylogenetic, and genomic studies have revealed cryptic diversity within P. parvum s.l. and uncovered three clade-specific (types A, B, and C) prymnesin toxins. Here, we used state-of-the-art long-read sequencing and assembled the first haplotype-resolved diploid genome of a P. parvum type B from the strain responsible for the Oder disaster. Comparative analyses with type A genomes uncovered a genome-size expansion driven by repetitive elements in type B. We also found conserved synteny but divergent evolution in several polyketide synthase (PKS) genes, which are known to underlie toxin production in combination with environmental cues. We identified an approximately 20-kbp deletion in the largest PKS gene of type B that we link to differences in the chemical structure of types A and B prymnesins. Flow cytometry and electron microscopy analyses confirmed diploidy in the Oder River strain and revealed differences to closely related strains in both ploidy and morphology. Our results provide unprecedented resolution of strain diversity in P. parvum s.l. and a better understanding of the genomic basis of toxin variability in haptophytes. The reference-quality genome will enable us to better understand changes in microbial diversity in the face of increasing environmental pressures and provides a basis for strain-level monitoring of invasive Prymnesium in the future.

Harmful algal blooms (HABs) of Alexandrium pacificum have affected the Marlborough Sounds in New Zealand since 2010, posing a threat to green-lipped mussel (GLM, Perna canaliculus) farming. Previous studies have shown A. pacificum has negative effects GLM embryos and larvae. To further investigate these toxic mechanisms, in vitro bioassays were conducted on GLM spermatozoa, hemocytes, and the diatom, Chaetoceros muelleri. The three cell types were exposed to several treatments of A. pacificum for 2 h and responses were measured using flow cytometry and pulse amplitude-modulated fluorometry. Significant spermatozoa mortality was recorded in treatments containing A. pacificum cells or fragments, while hemocyte and C. muelleri mortality was recorded in cell-free treatments of A. pacificum which contained paralytic shellfish toxins (PSTs). Variation in sensitivity between cell types as well as the sublethal effects observed, emphasise the diverse toxic mechanisms of A. pacificum on co-occurring species in the environment.