Harmful Algal Blooms Research Articles

SFMnet: Edge detection of HABs based on spatial feature mapping encoder-decoder network

Achieving high-accuracy real-time recognition of marine red tide algae images is crucial in implementing red tide algae early warning systems. However, due to uneven lighting and the deposition of unknown suspended particles in seawater, real-time collected harmful algal blooms (HABs) microscopic images in marine engineering suffer from poor clarity and blurred cell contours, leading to lower accuracy of current edge detection models for microscopic images. Firstly, to enhance the quality of degraded images in the original HABs dataset, we design an image enhancement algorithm based on underwater image restoration models, which involves precise depth estimation of seawater scenes and fusion of transmission maps. This algorithm effectively eliminates chromatic aberration and enhances image edge details and contrast. Secondly, we propose a deep-learning model based on the VGG16 network. This model integrates multi-scale features through the Spatial Feature Mapping module to improve edge detection accuracy. Experimental results using real-time HABs microscopic image data show that the proposed enhancement method achieves the best results regarding contrast, image enhancement metrics, and clarity gradient. Moreover, the edge detection method achieves an ODS of 0.636 and an OIS of 0.701. The results demonstrate that performing edge detection after the image enhancement preprocess significantly improves detection accuracy.

Exploring factors that affect Microcystis abundance in the sacramento san joaquin delta

Cyanobacteria harmful algal blooms (cHABs) are increasing in frequency, intensity and duration in estuaries worldwide. In the upper San Francisco Estuary, also known as the Sacramento San Joaquin Delta (Delta), cHABs have been a topic of concern over the past two decades. In response, managers are urgently working to understand the factors that drive cHABs and identify feasible management options to avert ecological and human health consequences. We used a six year data set to explore relationships between flow parameters, temperature, and Microcystis biovolume to determine the potential for managing large scale hydrodynamic conditions to address Delta cHABs. We also looked at the relationship between Microcystis biovolume and the low salinity zone to see if it could be used as a proxy for residence time, because residence time is positively related to cyanobacteria abundance. We found the low salinity zone is not a useful proxy for residence time in the area of the Delta that experiences the most severe cHABs. Our finding suggest that climatic conditions (i.e., temperature and water year type) have the greatest influence on Microcystis biovolume in the Delta, with higher biovolume during years with lower flow and higher temperatures. Further, there are interannual differences in Microcystis biovolume that cannot be fully explained by flow parameters or temperature, meaning other factors not included in our model may be involved. We conclude that management actions to increase flow may be ineffective at reducing Microcystis to desired levels if water temperatures remain high.

Metabologenomics reveals strain-level genetic and chemical diversity of Microcystis secondary metabolism.

Microcystis spp. are renowned for producing the hepatotoxin microcystin in freshwater cyanobacterial harmful algal blooms around the world, threatening drinking water supplies and public and environmental health. However, Microcystis genomes also harbor numerous biosynthetic gene clusters (BGCs) encoding the biosynthesis of other secondary metabolites, including many with toxic properties. Most of these BGCs are uncharacterized and currently lack links to biosynthesis products. However, recent field studies show that many of these BGCs are abundant and transcriptionally active in natural communities, suggesting potentially important yet unknown roles in bloom ecology and water quality. Here, we analyzed 21 xenic Microcystis cultures isolated from western Lake Erie to investigate the diversity of the biosynthetic potential of this genus. Through metabologenomic and in silico approaches, we show that these Microcystis strains contain variable BGCs, previously observed in natural populations, and encode distinct metabolomes across cultures. Additionally, we find that the majority of metabolites and gene clusters are uncharacterized, highlighting our limited understanding of the chemical repertoire of Microcystis spp. Due to the complex metabolomes observed in culture, which contain a wealth of diverse congeners as well as unknown metabolites, these results underscore the need to deeply explore and identify secondary metabolites produced by Microcystis beyond microcystins to assess their impacts on human and environmental health.IMPORTANCEThe genus Microcystis forms dense cyanobacterial harmful algal blooms (cyanoHABs) and can produce the toxin microcystin, which has been responsible for drinking water crises around the world. While microcystins are of great concern, Microcystis also produces an abundance of other secondary metabolites that may be of interest due to their potential for toxicity, ecological importance, or pharmaceutical applications. In this study, we combine genomic and metabolomic approaches to study the genes responsible for the biosynthesis of secondary metabolites as well as the chemical diversity of produced metabolites in Microcystis strains from the Western Lake Erie Culture Collection. This unique collection comprises Microcystis strains that were directly isolated from western Lake Erie, which experiences substantial cyanoHAB events annually and has had negative impacts on drinking water, tourism, and industry.

Economic valuation of Harmful Algal Blooms (HAB): Methodological challenges, policy implications, and an empirical application

This paper presents a literature review on the economic valuation of Harmful Algal Bloom (HAB) impacts, identifying methodological challenges, policy implications, and gaps. Unlike previous literature reviews, we are particularly interested in determining whether the economic valuations of HABs have included a policy analysis. Our paper provides a conceptual framework that allows us to evaluate whether applications of economic studies of HABs are consistent with a well-defined economic welfare analysis. It links methodologies and techniques with welfare measures, data types, and econometric methods. Based on this literature review, we present an example of economic valuation that closes the gap between policy analysis and valuation methodology. We use a stated preferences study to estimate a “seafood price premium” to create a fund to support monitoring systems and for damage compensation to producers in the presence of HABs. Results show that most economic studies on HAB valuation do not consider any cost-benefit analysis of a defined policy intervention. The predominant economic valuation methodology uses market information to estimate a proxy for welfare measure of the impact of HABs (loss revenue, sales, exports). Moreover, nonuse and indirect use values are ignored in the literature, while stated preference methodologies are underrepresented. Finally, results from 1293 surveys found that people are willing to pay an increase in the price of mussels to support a policy that informs on HAB. However, the lack of institutional trust affects the probability of paying negatively.

Identification and Composition of Cyanobacteria in Ecuadorian Shrimp Farming Ponds-Possible Risk to Human Health.

Toxic cyanobacterial blooms in various water bodies have been given much attention nowadays as they release hazardous substances in the surrounding areas. These toxic planktonic cyanobacteria in shrimp ponds greatly affect the survival of shrimps. Ecuador is the second highest shrimp producing country in the Americas after Brazil; and the shrimp-based economy is under threat due to toxic cyanobacterial blooms in Ecuador shrimp ponds. This study investigated the abundance of different cyanobacteria in the shrimp ponds at the Chone and Jama rivers (in Manabi province) at Ecuadorian pacific coast, focusing on different environmental factors, such as temperature, pH, salinity, and light. Temperature and pH were identified as key factors in influencing the abundance of cyanobacteria, with a significant positive correlation betweenRaphidiopsis raciborskiiand pH. The highest and lowest abundance of cyanobacteria found during the dry season in the shrimp ponds near the Chone and Jama rivers were > 3 × 106 and 1 × 106Cell.m-3, respectively. The Shannon-Wiener Diversity Index fluctuated between 0.41-1.15 and 0.31-1.15 for shrimp ponds of Chone and Jama rivers, respectively. This variation was linked to changes in salinity and the presence of harmful algal blooms, highlighting the importance of continuous monitoring. Additionally, the study areas showed eutrophic conditions with low diversity, underlining the need for additional spatiotemporal studies and expanded research in both rivers, to better understand these complex phenomena. The findings underscore the importance of continuous monitoring and expanded research in cyanobacteria ecology, with implications for public health and aquatic resource management.

The micro-ecological feature of colonies is a potential strategy for Phaeocystis globosa bloom formation

Phaeocystis globosa is among the dominant microalgae associated with harmful algal blooms. P. globosa has a polymorphic life cycle and its ecological success has been attributed to algal colony formation, however, few studies have assessed differences in microbial communities and their functional profiles between intra- and extra-colonies during P. globosa blooms. To address this, environmental and metagenomics tools were used to conduct a time-series analysis of the bacterial composition and metabolic characteristics of intra- and extra-colonies during a natural P. globosa bloom. The results show that bacterial composition, biodiversity, and network interactions differed significantly between intra- and extra-colonies. Dominant extra-colonial bacteria were Bacteroidia and Saccharimonadis, while dominant intra-colonial bacteria included Alphaproteobacteria and Gammaproteobacteria. Despite the lower richness and diversity observed in the intra-colonial bacterial community, relative to extra-colonies, the complexity and interconnectedness of the intra-colonial networks were higher. Regarding bacterial function, more functional genes were enriched in substance metabolism (polysaccharides, iron element and dimethylsulfoniopropionate) and signal communication (quorum sensing, indoleacetic acid-IAA) pathways in intra- than in extra-colonies. Conceptual model construction showed that microbial cooperative synthesis of ammonium, vitamin B12, IAA, and siderophores were strongly related to the P. globosa bloom, particularly in the intra-colonial environment. Overall, our data highlight the differences in bacterial structure and functions within and outside the colony during P. globosa blooms. These findings represent fundamental information indicating that phenotypic heterogeneity is a selective strategy that improves microbial population competitiveness and environmental adaptation, benefiting P. globosa bloom formation and persistence.

Review of Allelopathy in Green Tides: The Case of Ulva prolifera in the South Yellow Sea.

The proliferation of large green macroalgae in marine environments has led to the occurrence of green tides, particularly in the South Yellow Sea region of China, where Ulva prolifera has been identified as the primary species responsible for the world's largest green tide events. Allelopathy among plants is a critical factor influencing the dynamics of green tides. This review synthesizes previous research on allelopathic interactions within green tides, categorizing four extensively studied allelochemicals: fatty acids, aldehydes, phenols, and terpenes. The mechanisms by which these compounds regulate the physiological processes of green tide algae are examined in depth. Additionally, recent advancements in the rapid detection of allelochemicals are summarized, and their potential applications in monitoring green tide events are discussed. The integration of advanced monitoring technologies, such as satellite observation and environmental DNA (eDNA) analysis, with allelopathic substance detection is also explored. This combined approach addresses gaps in understanding the dynamic processes of green tide formation and provides a more comprehensive insight into the mechanisms driving these phenomena. The findings and new perspectives presented in this review aim to offer valuable insights and inspiration for researchers and policymakers.

Insights into the nature of ichthyotoxins from the Chrysochromulina leadbeateri blooms in Northern Norwegian fjords

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.

Sirenian (manatees and dugongs) reproductive endocrinology

Reproductive hormones are essential to mating systems, behavior, fertility, gestation, parturition, and lactation in mammals and understanding the role of hormones in these processes is essential for species conservation. Sirenia is a unique order of marine mammals that include manatees, dugongs, and the extinct Steller’s sea cow. Extant Sirenian species are all listed as vulnerable due to habitat loss, cold stress, boat strike trauma, harmful algal bloom toxicity, entanglements, and illegal hunting. Therefore, successful reproduction is essential to maintaining and increasing Sirenian populations. Understanding Sirenian reproductive behavior, endocrinology, and mating strategies will aid conservation and management efforts to protect and provide the proper conditions for successful reproduction. The objectives of this review were to synthesize the current knowledge regarding reproductive cycles and endocrinology of Sirenians and identify knowledge gaps for future investigation. The current literature on Sirenian reproductive physiology reports reproductive seasonality, sexual maturation, estrous cyclicity and acyclicity, pregnancy, and sex differences. However, there remain significant knowledge gaps on the cyclicity and pulsatile release of gonadotropins, maturation in females, and characterization of pregnancy hormone profiles throughout gestation. To date, there is no explanation for confirmed pattern for ovarian acyclicity, nor understanding of the function of the numerous accessory corpus luteum described in manatees. Research including a greater number of longitudinal and postmortem studies on a wider variety of wild manatee populations are important first steps. Taken together, understanding the reproductive endocrinology of these vulnerable and threatened species is critical for policy and management decisions to better inform protection initiatives.

BTXs removals by modified clay during mitigation of Karenia brevis bloom: Insights from adsorption and transformation

Harmful algal blooms (HABs), especially those caused by toxic dinoflagellates, are spreading in marine ecosystems worldwide. Notably, the prevalence of Karenia brevis blooms and potent brevetoxins (BTXs) pose a serious risk to public health and marine ecosystems. Therefore, developing an environmentally friendly method to effectively control HABs and associated BTXs has been the focus of increasing attention. As a promising method, modified clay (MC) application could effectively control HABs. However, the environmental fate of BTXs during MC treatment has not been fully investigated. For the first time, this study revealed the effect and mechanism of BTX removal by MC from the perspective of adsorption and transformation. The results indicated that polyaluminium chloride-modified clay (PAC-MC, a typical kind of MC) performed well in the adsorption of BTX2 due to the elevated surface potential and more binding sites. The adsorption process was a spontaneous endothermic process that conformed to pseudo-second-order adsorption kinetics (k2 = 6.8 × 10−4, PAC-MC = 0.20 g L−1) and the Freundlich isotherm (Kf = 55.30, 20 °C). In addition, detailed product analysis using liquid chromatography−mass spectrometry/mass spectrometry (LC−MS/MS) indicated that PAC-MC treatment effectively removed the BTX2 and BTX3, especially those in the particulate forms. Surprisingly, PAC-MC could promote the transformation of BTX2 to derivatives, including OR-BTX2, OR-BTX3, and OR-BTX-B5, which were proven to have lower cytotoxicity.

Environmental drivers behind the exceptional increase in cyanobacterial blooms in Okavango Delta, Botswana

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.

The impact of sexual reproduction-induced vertical migration on the complexity of harmful algal blooms in Heterosigma akashiwo

Vertical migration behaviour, which is integral to marine energy circulation, is a prevalent trait among marine organisms. However, the behaviour of phytoplankton, particularly beyond diel vertical migration (DVM), remain underexplored compared to groups like zooplankton. Through the lens of the harmful alga Heterosigma akashiwo, which exhibits active vertical migrations and unique fluctuating bloom dynamics, this study aimed to explore the ecological intricacies and diverse benefits of phytoplankton vertical migration behaviours. During the bloom period of H. akashiwo, we unexpectedly observed a dense concentration of cells at bottom layer during daytime. This phase coincided with the emergence of cells related to this species' sexual reproduction. Laboratory experiments further showed an elevated frequency of sexual reproduction in the cell populations that migrated to deeper depths compared to those at the surface. This finding implies a connection between dense bottom accumulation (BA) and the life cycle transitions of the species. This BA phase persisted for two days, after which the populations returned to their standard DVM behaviour, providing insight into the unique fluctuating bloom dynamics of H. akashiwo. Our study suggests that phytoplankton vertical migrations are not strictly dictated by DVM, revealing diverse vertical migration behaviours that may contribute to the complexity of harmful algal bloom patterns.

The allelopathic effects of Heterosigma akashiwo on Skeletonema costatum: Insights from gene expression and metabolomics analysis

The globally distributed harmful algal blooms (HAB) species, Heterosigma akashiwo, has been found to exhibit ichthyotoxicity. Previous studies have shown that H. akashiwo achieves a competitive edge during bloom occurrences by inhibiting the growth of a coexisting diatom, Skeletonema costatum, through allelopathy. However, the specific allelopathic mechanisms underlying the allelopathic effects of H. akashiwo on S. costatum remain unknown. To bridge this gap, our study utilized a combination of quantitative real-time PCR and metabolomics to examine the allelopathic processes of H. akashiwo on S. costatum. Our results demonstrate that the growth of S. costatum is hindered when co-cultured with H. akashiwo (initial cell concentration, 2 × 104 cell/mL). Gene expression investigation showed a substantial reduction in the mRNA levels of cytochrome b6, ribulose bisphosphate carboxylase large chain, and silicon transporter in S. costatum when grown in co-culture conditions. Furthermore, metabolic pathway analysis suggested that the allelopathic effects of H. akashiwo disrupted several vital metabolic pathways in S. costatum, including a reduction in purine and pyrimidine metabolism and an increase in fatty acid biosynthesis. Our investigation has revealed the intricate and substantial involvement of allelopathy in the formation of H. akashiwo blooms, demonstrating the complexity of the allelopathic interaction between H. akashiwo and S. costatum. These insights also contribute significantly to our understanding of the dynamics within HAB species.

Integrating temporal decomposition and data-driven approaches for predicting coastal harmful algal blooms

Frequent coastal harmful algal blooms (HABs) threaten the ecological environment and human health. Biscayne Bay in southeastern Florida also faces algal bloom issues; however, the mechanisms driving these blooms are not fully understood, emphasizing the importance of HAB prediction for effective environmental management. The overarching goal of this study is to offer a robust HAB predictive framework and try to enhance the understanding of HAB dynamics. This study established three scenarios to predict chlorophyll-a concentrations, a recognized representative of HABs: Scenario 1 (S1) using single nonlinear machine learning (ML) algorithms, hybrid Scenario 2 (S2) combining linear models and nonlinear ML algorithms, and hybrid Scenario 3 (S3) combining temporal decomposition and ML (TD-ML) algorithms. The novel-developed S3 TD-ML hybrid models demonstrated superior predictive capabilities, achieving all R2 values above 0.9 and MAPE under 30% in tests, significantly outperforming the S1 with an average R2 of 0.16 and the S2 with an R2 of −0.06. S3 models effectively captured the algal dynamics, successfully predicting complex time series with extremes and noise. In addition, we unveiled the relationship between environmental variables and chlorophyll-a through correlation analysis and found that climate change might intensify the HABs in Biscayne Bay. This research developed a precise predictive framework for early warning and proactive management of HABs, offering potential global applicability and improved prediction accuracy to address HAB challenges.

Evaluation of best management practices for mitigating harmful algal blooms risk in an agricultural lake basin using a watershed model integrated with Bayesian Network approach

Lake eutrophication caused by nitrogen and phosphorus has led to frequent harmful algal blooms (HABs), especially under the unknown challenges of climate change, which have seriously damaged human life and property. In this study, a coupled SWAT-Bayesian Network (SWAT-BN) model framework was constructed to elucidate the mechanisms between non-point source nitrogen pollution in agricultural lake watersheds and algal activities. A typical agricultural shallow lake basin, the Taihu Basin (TB), China, was chosen in this study, aiming to investigate the effectiveness of best management practices (BMPs) in controlling HABs risks in TB. By modeling total nitrogen concentration of Taihu Lake from 2007 to 2022 with four BMPs (filter strips, grassed waterway, fertilizer application reduction and no-till agriculture), the results indicated that fertilizer application reduction proved to be the most effective BMP with 0.130 of Harmful Algal Blooms Probability Reduction (HABs-PR) when reducing 40% of fertilizer, followed by filter strips with 0.01 of HABs-PR when 4815ha of filter strips were conducted, while grassed waterway and no-till agriculture showed no significant effect on preventing HABs. Furthermore, the combined practice between 40% fertilizer application reduction and 4815ha filter strips construction showed synergistic effects with HABs-PR increasing to 0.171. Precipitation and temperature data were distorted to model scenarios of extreme events. As a result, the combined approach outperformed any single BMP in terms of robustness under extreme climates. This research provides a watershed-level perspective on HABs risks mitigation and highlights the strategies to address HABs under the influence of climate change.

Use of multiple sampling techniques for cyanobacteria and cyanotoxin monitoring in the Sacramento-San Joaquin Delta under different hydrologic regimes

Cyanobacteria harmful algal blooms (CHABs) are a growing water quality problem in the upper San Francisco Estuary (California), also known as the Sacramento-San Joaquin Delta. We conducted cyanobacteria and cyanotoxin monitoring from 2020 to 2023, which spanned California's driest consecutive 3-year period and one of the wettest years on record (2023). To assess the impact of CHABs over this range of hydrologic conditions, we monitored invasive Asian Clams (Corbicula fluminea) for microcystin contamination and used molecular tools (qPCR and sequencing) to characterize cyanobacteria in the water column. We also used solid phase adsorption toxin tracking (SPATT) samplers to track microcystins (MCs) and other cyanotoxins in 2023. During the drought years, record breaking MCs, in excess of 1000 μg/L, were documented in water grab samples and Asian clams also accumulated higher MCs relative to the wet year. However, MCs were present in Asian clams during the entire study period. SPATT's confirmed MC presence during wet 2023 and sequencing results corroborated the integrative sampler findings. Yet, no MC was detected in water grab samples at our primary sampling sites during the drought year of 2022 or the wet year of 2023. This highlights the importance of using multiple sampling modalities to provide a more accurate assessment of MC contamination, especially in large estuaries where traditional discrete monitoring can easily miss episodic and transient CHAB events.

Simultaneous inactivation of Microcystis aeruginosa and degradation of microcystin-LR in water by activation of periodate with sunlight

Harmful algal blooms pose tremendous threats to ecological safety and human health. In this study, simulated solar light (SSL) irradiation was used to activate periodate (PI) for the inactivation of Microcystis aeruginosa and degradation of microcystin-LR (MC-LR). We found that PI-SSL system could effectively inactivate 5 × 106 cells·mL−1 algal cells below the limit of detection within 180 min. ·OH and iodine (IO3· and IO4·) radicals generated in PI-SSL system could rupture cell membranes, releasing intracellular substances including MC-LR into the reaction system. However, the released MC-LR could be degraded into non-toxic small molecules via hydroxylation and ring cleavage processes in PI-SSL system, reducing their environmental risks. High algae inactivation performance of PI-SSL system in solution with a wide pH range (3–9), with the coexisting anions (Cl−, NO3− and SO42−) and the copresence of natural organic matters (humic acid and fulvic acid), real water (lake water and river water), as well as in continuous-flow reactor (14 h) were also achieved. In addition, under natural sunlight irradiation, effective algae inactivation could also be achieved in an enlarged reactor (1 L). Overall, our study showed that PI-SSL system could avoid the inference by the background substances and could be employed as a feasible technique to treat algal bloom water.

A synthetic and transparent clay removes Microcystis aeruginosa efficiently

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.

Chlorophyll a in lakes and streams of the United States (2005–2022)

The concentration of chlorophyll a in phytoplankton and periphyton represents the amount of algal biomass. We compiled an 18-year record (2005–2022) of pigment data from water bodies across the United States (US) to support efforts to develop process-based, machine learning, and remote sensing models for prediction of harmful algal blooms (HABs). To our knowledge, this dataset of nearly 84,000 sites and over 1,374,000 pigment measurements is the largest compilation of harmonized discrete, laboratory-extracted chlorophyll data for the US. These data were compiled from the Water Quality Portal (WQP) and previously unpublished U.S. Geological Survey’s National Water Quality Laboratory (NWQL) data. Data were harmonized for reporting units, pigment type, duplicate values, collection depth, site name, negative values, and some extreme values. Across the country, data show great variation by state in sampling frequency, distribution, and methods. Uses for such data include the calibration of models, calibration of field sensors, examination of relationship to nutrients and other drivers, evaluation of temporal trends, and other applications addressing local to national scale concerns.

Underway measurement of cyanobacterial microcystins using a surface plasmon resonance sensor on an autonomous underwater vehicle

AbstractFreshwater cyanobacterial harmful algal blooms (CHABs) are a well‐known global public health threat. Monitoring and early detection of CHAB toxins are currently accomplished using labor‐intensive sampling techniques and subsequent shore‐based analyses, with results typically reported 24–48 h after sample collection. We have developed and implemented an uncrewed, autonomous mobile sampler‐analytical system capable of conducting targeted in situ toxin measurements in < 2 h. A surface plasmon resonance (SPR) instrument was combined with the environmental sample processor (ESP) to fully automate detection and quantification of particle‐associated cyanobacterial microcystins (pMC). This sensor‐sampler system was integrated with a long‐range autonomous underwater vehicle (LRAUV) and deployed in western Lake Erie for field trials in the summer of 2021. The LRAUV was remotely piloted to acquire samples at selected locations within and adjacent to a CHAB. Sixteen pMC measurements ranging from 0.09 to 0.55 μg/L lake water were obtained over a 14‐day period without recovery of the LRAUV. The SPR/ESP/LRAUV system complements existing satellite, aerial, and manual sampling CHAB survey techniques, and could be used to enhance predictive models that underpin bloom and toxicity forecasts. This system is also extensible to detection of other algal toxins in freshwater and marine environments, with its near real‐time assessment of bloom toxin levels potentially offering additional socioeconomic benefits and public health protection in a variety of settings.