Science meets policy: A framework for determining impairment designation criteria for large waterbodies affected by cyanobacterial harmful algal blooms

Characterization of Taxonomic and Functional Dynamics Associated with Harmful Algal Bloom Formation in Recreational Water Ecosystems

Harmful algal bloom (HAB) formation leads to the eutrophication of water ecosystems and may render recreational lakes unsuitable for human use. We evaluated the applicability and comparison of metabarcoding, metagenomics, qPCR, and ELISA-based methods for cyanobacteria/cyanotoxin detection in bloom and non-bloom sites for the Great Lakes region. DNA sequencing-based methods robustly identified differences between bloom and non-bloom samples (e.g., the relative prominence of Anabaena and Planktothrix). Shotgun sequencing strategies also identified the enrichment of metabolic genes typical of cyanobacteria in bloom samples, though toxin genes were not detected, suggesting deeper sequencing or PCR methods may be needed to detect low-abundance toxin genes. PCR and ELISA indicated microcystin levels and microcystin gene copies were significantly more abundant in bloom sites. However, not all bloom samples were positive for microcystin, possibly due to bloom development by non-toxin-producing species. Additionally, microcystin levels were significantly correlated (positively) with microcystin gene copy number but not with total cyanobacterial 16S gene copies. In summary, next-generation sequencing-based methods can identify specific taxonomic and functional targets, which can be used for absolute quantification methods (qPCR and ELISA) to augment conventional water monitoring strategies.

A Case Series of Potential Pediatric Cyanotoxin Exposures Associated with Harmful Algal Blooms in Northwest Ohio

Cyanobacterial harmful algal blooms (CyanoHABs) are increasing in prevalence and severity in the Great Lakes region, as well as both globally and locally. CyanoHABs have the potential to cause adverse effects on human health due to the production of cyanotoxins from cyanobacteria. Common routes of exposure include recreational exposure (swimming, skiing, and boating), ingestion, and aerosolization of contaminated water sources. Cyanotoxins have been shown to adversely affect several major organ systems contributing to hepatotoxicity, gastrointestinal distress, and pulmonary inflammation. We present three pediatric case reports that coincided with CyanoHABs exposure with a focus on presentation of illness, diagnostic work-up, and treatment of CyanoHAB-related illnesses. Potential cyanotoxin exposure occurred while swimming in the Maumee River and Maumee Bay of Lake Erie in Ohio during the summer months with confirmed CyanoHAB activity. Primary symptoms included generalized macular rash, fever, vomiting, diarrhea, and severe respiratory distress. Significant labs included leukocytosis and elevated C-reactive protein. All patients ultimately recovered with supportive care. Symptoms following potential cyanotoxin exposure coincide with multiple disease states representing an urgent need to develop specific diagnostic tests of exposure.

Effective Early Treatment of Microcystis Exponential Growth and Microcystin Production with Hydrogen Peroxide and Hydroxyapatite

Mitigating cyanotoxin production is essential to protecting aquatic ecosystems and public health. However, current harmful cyanobacterial bloom (HCB) control strategies have significant shortcomings. Because predicting HCBs is difficult, current HCB control strategies are employed when heavy HCBs have already occurred. Our pilot study developed an effective HCB prediction approach that is employed before exponential cyanobacterial growth and massive cyanotoxin production can occur. We used a quantitative polymerase chain reaction (qPCR) assay targeting the toxin-encoding gene mcyA to signal the timing of treatment. When control measures were applied at an early growth stage or one week before the exponential growth of Microcystis aeruginosa (predicted by qPCR signals), both hydrogen peroxide (H2O2) and the adsorbent hydroxyapatite (HAP) effectively stopped M. aeruginosa growth and microcystin (MC) production. Treatment with either H2O2 (10 mg·L-1) or HAP (40 µm particles at 2.5 g·L-1) significantly reduced both mcyA gene copies and MC levels compared with the control in a dose-dependent manner. While both treatments reduced MC levels similarly, HAP showed a greater ability to reduce mcyA gene abundance. Under laboratory culture conditions, H2O2 and HAP also prevented MC production when applied at the early stages of the bloom when mcyA gene abundance was below 105 copies·mL-1.

Harmonizing science and management options to reduce risks of cyanobacteria

Management of cyanobacteria has become an increasingly complex venture. Cyanobacteria risks have amplified as society moves forward in an era of accelerated global changes. The cyanobacteria management "pendulum" has progressively shifted from prevention to mitigation, with management considerations often put forth after bloom formation. A universal system (i.e., one-size-fits-all management) fails to provide a management path forward due to the inherent complexities of each lake. A tailored management plan is needed: the right species at the right time in the right place (i.e., the three Rs). The three Rs represent a customizable management strategy that is flexible and informed by advances in scientific understanding to lower cyanobacteria-associated risks. Identifying thresholds in risk tolerance, where thresholds are defined by community collectives, is essential to frame cyanobacteria management targets and to decide on what management interventions are warranted.

Perceived Intensification in Harmful Algal Blooms Is a Wave of Cumulative Threat to the Aquatic Ecosystems

Simple Summary

Harmful algal blooms (HABs) are a serious threat to aquatic environments. The intensive expansion of HABs across the world is a warning signal of environmental deterioration. Global climatic change enforced variations in environmental factors causing stressed environments in aquatic ecosystems that favor the occurrence, distribution, and persistence of HABs. Perceived intensification in HABs increases toxin production, affecting the ecological quality as well as serious consequences on organisms including humans. This review outlines the causes and impacts of harmful algal blooms, including algal toxicity, grazing defense, management, control measures, emerging technologies, and their limitations for controlling HABs in aquatic ecosystems.

Abstract

Aquatic pollution is considered a major threat to sustainable development across the world, and deterioration of aquatic ecosystems is caused usually by harmful algal blooms (HABs). In recent times, HABs have gained attention from scientists to better understand these phenomena given that these blooms are increasing in intensity and distribution with considerable impacts on aquatic ecosystems. Many exogenous factors such as variations in climatic patterns, eutrophication, wind blowing, dust storms, and upwelling of water currents form these blooms. Globally, the HAB formation is increasing the toxicity in the natural water sources, ultimately leading the deleterious and hazardous effects on the aquatic fauna and flora. This review summarizes the types of HABs with their potential effects, toxicity, grazing defense, human health impacts, management, and control of these harmful entities. This review offers a systematic approach towards the understanding of HABs, eliciting to rethink the increasing threat caused by HABs in aquatic ecosystems across the world. Therefore, to mitigate this increasing threat to aquatic environments, advanced scientific research in ecology and environmental sciences should be prioritized.

Metagenomic and Metatranscriptomic Insights into Population Diversity of Microcystis Blooms: Spatial and Temporal Dynamics of mcy Genotypes, Including a Partial Operon That Can Be Abundant and Expressed

Cyanobacterial harmful algal blooms (cyanoHABs) degrade freshwater ecosystems globally. Microcystis aeruginosa often dominates cyanoHABs and produces microcystin (MC), a class of hepatotoxins that poses threats to human and animal health. Microcystin toxicity is influenced by distinct structural elements across a diversity of related molecules encoded by variant mcy operons. However, the composition and distribution of mcy operon variants in natural blooms remain poorly understood. Here, we characterized the variant composition of mcy genes in western Lake Erie Microcystis blooms from 2014 and 2018. Sampling was conducted across several spatial and temporal scales, including different bloom phases within 2014, extensive spatial coverage on the same day (2018), and frequent, autonomous sampling over a 2-week period (2018). Mapping of metagenomic and metatranscriptomic sequences to reference sequences revealed three Microcystis mcy genotypes: complete (all genes present [mcyA-J]), partial (truncated mcyA, complete mcyBC, and missing mcyD-J), and absent (no mcy genes). We also detected two different variants of mcyB that may influence the production of microcystin congeners. The relative abundance of these genotypes was correlated with pH and nitrate concentrations. Metatranscriptomic analysis revealed that partial operons were, at times, the most abundant genotype and expressed in situ, suggesting the potential biosynthesis of truncated products. Quantification of genetic divergence between genotypes suggests that the observed strains are the result of preexisting heterogeneity rather than de novo mutation during the sampling period. Overall, our results show that natural Microcystis populations contain several cooccurring mcy genotypes that dynamically shift in abundance spatiotemporally via strain succession and likely influence the observed diversity of the produced congeners. IMPORTANCE Cyanobacteria are responsible for producing microcystins (MCs), a class of potent and structurally diverse toxins, in freshwater systems around the world. While microcystins have been studied for over 50 years, the diversity of their chemical forms and how this variation is encoded at the genetic level remain poorly understood, especially within natural populations of cyanobacterial harmful algal blooms (cyanoHABs). Here, we leverage community DNA and RNA sequences to track shifts in mcy genes responsible for producing microcystin, uncovering the relative abundance, expression, and variation of these genes. We studied this phenomenon in western Lake Erie, which suffers annually from cyanoHAB events, with impacts on drinking water, recreation, tourism, and commercial fishing.

The Lake Erie HABs Grab: A binational collaboration to characterize the western basin cyanobacterial harmful algal blooms at an unprecedented high-resolution spatial scale

Monitoring of cyanobacterial bloom biomass in large lakes at high resolution is made possible by remote sensing. However, monitoring cyanobacterial toxins is only feasible with grab samples, which, with only sporadic sampling, results in uncertainties in the spatial distribution of toxins. To address this issue, we conducted two intensive "HABs Grabs" of microcystin (MC)-producing Microcystis blooms in the western basin of Lake Erie. These were one-day sampling events during August of 2018 and 2019 in which 100 and 172 grab samples were collected, respectively, within a six-hour window covering up to 2,270 km² and analyzed using consistent methods to estimate the total mass of MC. The samples were analyzed for 57 parameters, including toxins, nutrients, chlorophyll, and genomics. There were an estimated 11,513 kg and 30,691 kg of MCs in the western basin during the 2018 and 2019 HABs Grabs, respectively. The bloom boundary poses substantial issues for spatial assessments because MC concentration varied by nearly two orders of magnitude over very short distances. The MC to chlorophyll ratio (MC:chl) varied by a factor up to 5.3 throughout the basin, which creates challenges for using MC:chl to predict MC concentrations. Many of the biomass metrics strongly correlated (r > 0.70) with each other except chlorophyll fluorescence and phycocyanin concentration. While MC and chlorophyll correlated well with total phosphorus and nitrogen concentrations, MC:chl correlated with dissolved inorganic nitrogen. More frequent MC data collection can overcome these issues, and models need to account for the MC:chl spatial heterogeneity when forecasting MCs.

Antibiotic pollution promotes dominance by harmful cyanobacteria: A case study examining norfloxacin exposure in competition experiments

Cyanobacterial harmful algal blooms (cyanoHABs) in freshwater lakes across the globe are often combined with other stressors. Pharmaceutical pollution, especially antibiotics in water bodies, poses a potential hazard in aquatic ecosystems. However, how antibiotics influence the risk of cyanoHABs remains unclear. Here, we investigated the effects of norfloxacin (NOR), one of the most widely used antibiotics globally, to a bloom-forming cyanobacterium (Microcystis aeruginosa) and a common green alga (Scenedesmus quadricauda), under both mono- and coculture conditions. Taxon-specific responses to NOR were evaluated in monoculture. In addition, the growth rate and change in ratio of cyanobacteria to green algae when cocultured with exposure to NOR were determined. In monocultures of Microcystis, exposure to low concentrations of NOR resulted in decreases in biomass, chlorophyll a and soluble protein content, while superoxide anion content and superoxide dismutase activity increased. However, NOR at high concentration only slightly affected Scenedesmus. During the co-culture trials of Microcystis and Scenedesmus, the 5 μg · L^-1 NOR treatment increased the ratio of Microcystis to co-cultured Scenedesmus by 47.2%. Meanwhile, although Scenedesmus growth was enhanced by 4.2% under NOR treatment in monoculture, it was conversely inhibited by 63.4% and 38.2% when co-cultured with Microcystis with and without NOR, respectively. Our results indicate that antibiotic pollution has a potential risk to enhance the perniciousness of cyanoHABs by disturbing interspecific interaction between cyanobacteria and green algae. These results reinforce the need for scientists and managers to consider the influence of xenobiotics in shaping the outcome of interactions among multiple species in aquatic ecosystems.

Elevated pH Conditions Associated With Microcystis spp. Blooms Decrease Viability of the Cultured Diatom Fragilaria crotonensis and Natural Diatoms in Lake Erie

Cyanobacterial Harmful Algal Blooms (CyanoHABs) commonly increase water column pH to alkaline levels ≥9.2, and to as high as 11. This elevated pH has been suggested to confer a competitive advantage to cyanobacteria such as Microcystis aeruginosa. Yet, there is limited information regarding the restrictive effects bloom-induced pH levels may impose on this cyanobacterium’s competitors. Due to the pH-dependency of biosilicification processes, diatoms (which seasonally both precede and proceed Microcystis blooms in many fresh waters) may be unable to synthesize frustules at these pH levels. We assessed the effects of pH on the ecologically relevant diatom Fragilaria crotonensis in vitro, and on a Lake Erie diatom community in situ. In vitro assays revealed F. crotonensis monocultures exhibited lower growth rates and abundances when cultivated at a starting pH of 9.2 in comparison to pH 7.7. The suppressed growth trends in F. crotonensis were exacerbated when co-cultured with M. aeruginosa at pH conditions and cell densities that simulated a cyanobacteria bloom. Estimates demonstrated a significant decrease in silica (Si) deposition at alkaline pH in both in vitro F. crotonensis cultures and in situ Lake Erie diatom assemblages, after as little as 48 h of alkaline pH-exposure. These observations indicate elevated pH negatively affected growth rate and diatom silica deposition; in total providing a competitive disadvantage for diatoms. Our observations demonstrate pH likely plays a significant role in bloom succession, creating a potential to prolong summer Microcystis blooms and constrain diatom fall resurgence.

Multiple co-occurring and persistently detected cyanotoxins and associated cyanobacteria in adjacent California lakes

The global proliferation of toxin producing cyanobacterial blooms has been attributed to a wide variety of environmental factors with nutrient pollution, increased temperatures, and drought being three of the most significant. The current study is the first formal assessment of cyanotoxins in two impaired lakes, Canyon Lake and Lake Elsinore, in southern California that have a history of cyanobacterial blooms producing high biomass as measured by chl-a. Cyanotoxins in Lake Elsinore were detected at concentrations that persistently exceeded California recreational health thresholds, whereas Canyon Lake experienced persistent concentrations that only occasionally exceeded health thresholds. The study results are the highest recorded concentrations of microcystins, anatoxin-a, and cylindrospermopsin detected in southern California lakes. Concentrations exceeded health thresholds that caused both lakes to be closed for recreational activities. Cyanobacterial identifications indicated a high risk for the presence of potentially toxic genera and agreed with the cyanotoxin results that indicated frequent detection of multiple cyanotoxins simultaneously. A statistically significant correlation was observed between chlorophyll-a (chl-a) and microcystin concentrations for Lake Elsinore but not Canyon Lake, and chl-a was not a good indicator of cylindrospermopsin, anatoxin-a, or nodularin. Therefore, chl-a was not a viable screening indicator of cyanotoxin risk in these lakes. The study results indicate potential acute and chronic risk of exposure to cyanotoxins in these lakes and supports the need for future monitoring efforts to help minimize human and domestic pet exposure and to better understand potential effects to wildlife. The frequent co-occurrence of complex cyanotoxin mixtures further complicates the risk assessment process for these lakes given uncertainty in the toxicology of mixtures.

Elucidating controls on cyanobacteria bloom timing and intensity via Bayesian mechanistic modeling

The adverse impacts of harmful algal blooms (HABs) are increasing worldwide. Lake Erie is a North American Great Lake highly affected by cultural eutrophication and summer cyanobacterial HABs. While phosphorus loading is a known driver of bloom size, more nuanced yet crucial questions remain. For example, it is unclear what mechanisms are primarily responsible for initiating cyanobacterial dominance and subsequent biomass accumulation. To address these questions, we develop a mechanistic model describing June-October dynamics of chlorophyll a, nitrogen, and phosphorus near the Maumee River outlet, where blooms typically initiate and are most severe. We calibrate the model to a new, geostatistically-derived dataset of daily water quality spanning 2008-2017. A Bayesian framework enables us to embed prior knowledge on system characteristics and test alternative model formulations. Overall, the best model formulation explains 42% of the variability in chlorophyll a and 83% of nitrogen, and better captures bloom timing than previous models. Our results, supported by cross validation, show that onset of the major midsummer bloom is associated with about a month of water temperatures above 20 °C (occurring 19 July to 6 August), consistent with when cyanobacteria dominance is usually reported. Decreased phytoplankton loss rate is the main factor enabling biomass accumulation, consistent with reduced zooplankton grazing on cyanobacteria. The model also shows that phosphorus limitation is most severe in August, and nitrogen limitation tends to occur in early autumn. Our results highlight the role of temperature in regulating bloom initiation and subsequent loss rates, and suggest that a 2 °C increase could lead to blooms that start about 10 days earlier and grow 23% more intense.

Physical drivers facilitating a toxigenic cyanobacterial bloom in a major Great Lakes tributary

The Maumee River is the primary source for nutrients fueling seasonal Microcystis-dominated blooms in western Lake Erie's open waters though such blooms in the river are infrequent. The river also serves as source water for multiple public water systems and a large food services facility in northwest Ohio, USA. On 20 September 2017, an unprecedented bloom was reported in the Maumee River estuary within the Toledo metropolitan area, which triggered a recreational water advisory. Here we (1) explore physical drivers likely contributing to the bloom's occurrence, and (2) describe the toxin concentration and bacterioplankton taxonomic composition. A historical analysis using ten-years of seasonal river discharge, water level, and local wind data identified two instances when high-retention conditions occurred over ≥10 days in the Maumee River estuary: in 2016 and during the 2017 bloom. Observation by remote sensing imagery supported the advection of cyanobacterial cells into the estuary from the lake during 2017 and the lack of an estuary bloom in 2016 due to a weak cyanobacterial bloom in the lake. A rapid-response survey during the 2017 bloom determined levels of the cyanotoxins, specifically microcystins, in excess of recreational contact limits at sites within the lower 20 km of the river while amplicon sequencing found these sites were dominated by Microcystis. These results highlight the need to broaden our understanding of physical drivers of cyanobacterial blooms within the interface between riverine and lacustrine systems, particularly as such blooms are expected to become more prominent in response to a changing climate.

Dissolved Microcystin Release Coincident with Lysis of a Bloom Dominated by Microcystis spp. in Western Lake Erie Attributed to a Novel Cyanophage

Western Lake Erie (Laurentian Great Lakes) is prone to annual cyanobacterial harmful algal blooms (cHABs) dominated by Microcystis spp. that often yield microcystin toxin concentrations exceeding the federal EPA recreational contact advisory of 8 μg liter-1 In August 2014, microcystin levels were detected in finished drinking water above the World Health Organization 1.0 μg liter-1 threshold for consumption, leading to a 2-day disruption in the supply of drinking water for >400,000 residents of Toledo, Ohio (USA). Subsequent metatranscriptomic analysis of the 2014 bloom event provided evidence that release of toxin into the water supply was likely caused by cyanophage lysis that transformed a portion of the intracellular microcystin pool into the dissolved fraction, rendering it more difficult to eliminate during treatment. In August 2019, a similar increase in dissolved microcystins at the Toledo water intake was coincident with a viral lytic event caused by a phage consortium different in composition from what was detected following the 2014 Toledo water crisis. The most abundant viral sequence in metagenomic data sets was a scaffold from a putative member of the Siphoviridae, distinct from the Ma-LMM01-like Myoviridae that are typically documented to occur in western Lake Erie. This study provides further evidence that viral activity in western Lake Erie plays a significant role in transformation of microcystins from the particulate to the dissolved fraction and therefore requires monitoring efforts from local water treatment plants. Additionally, identification of multiple lytic cyanophages will enable the development of a quantitative PCR toolbox to assess viral activity during cHABs.IMPORTANCE Viral attack on cHABs may contribute to changes in community composition during blooms, as well as bloom decline, yet loss of bloom biomass does not eliminate the threat of cHAB toxicity. Rather, it may increase risks to the public by delivering a pool of dissolved toxin directly into water treatment utilities when the dominating Microcystis spp. are capable of producing microcystins. Detecting, characterizing, and quantifying the major cyanophages involved in lytic events will assist water treatment plant operators in making rapid decisions regarding the pool of microcystins entering the plant and the corresponding best practices to neutralize the toxin.

A risk assessment method for remote sensing of cyanobacterial blooms in inland waters

The widespread occurrence of Cyanobacterial blooms (CABs) in inland waters is a typical and severe challenge for water resources management and environment protection. An accurate and spatially continuous risk assessment of CABs is critical for prediction and preparedness in advance. In this study, a multivariate integrated risk assessment (MIRA) method of CABs in inland waters was proposed. MIRA was simplified with the trophic levels, cyanobacterial and other aquatic plant condition using remote sensing indexes, including the Trophic State Index (TSI), Floating Algae Index (FAI) and Cyanobacteria and Macrophytes Index (CMI). First, the dates of risk assessment were carefully selected based on TSI. Then, we obtained the trophic levels, cyanobacterial, and other aquatic plant condition of water using TSI, CMI and FAI on the selected date, and further scored them pixel by pixel to quantify the risk value. Finally, the risk of CABs in water was accurately assessed based on the pixel risk value. Based on Landsat 8 OLI dataset, MIRA was executed and validated in three different lakes of Wuhan urban agglomeration (WUA) with different trophic states. The results demonstrated that the risk of CABs in Lake LongGan was overall higher than that in Lake LiangZi and Lake FuTou. And the risk of CABs in the east part of Lake LongGan was higher than the other parts. Seasonally, the risk level ranking in Lake LiangZi was the highest in summer, while lowest in winter. However, the seasonal risk ranking was spring, summer, autumn, and winter in Lake LongGan. Based on the comparisons with monthly water quality classification data and results of the existing study, including trophic level, ecology risk, and algal extent, the MIRA method was valuable for accurate and spatially continuous identifying the risk of CABs in inland waters with potential eutrophication trends.

Mitigating the global expansion of harmful cyanobacterial blooms: Moving targets in a human- and climatically-altered world

Cyanobacterial harmful algal blooms (CyanoHABs) are a major threat to human and environmental health. As global proliferation of CyanoHABs continues to increase in prevalence, intensity, and toxicity, it is important to identify and integrate the underlying causes and controls of blooms in order to develop effective short- and long-term mitigation strategies. Clearly, nutrient input reductions should receive high priority. Legacy effects of multi-decadal anthropogenic eutrophication have altered limnetic systems such that there has been a shift from exclusive phosphorus (P) limitation to nitrogen (N) limitation and N and P co-limitation. Additionally, climate change is driving CyanoHAB proliferation through increasing global temperatures and altered precipitation patterns, including more extreme rainfall events and protracted droughts. These scenarios have led to the "perfect storm scenario"; increases in pulsed nutrient loading events, followed by persistent low-flow, long water residence times, favoring bloom formation and proliferation. To meet the CyanoHAB mitigation challenge, we must: (1) Formulate watershed and airshed-specific N and P input reductions on a sliding scale to meet anthropogenic and climatic forcings. (2) Develop CyanoHAB management strategies that incorporate current and anticipated climatic changes and extremes. (3) Make nutrient management strategies compatible with other physical-chemical-biological mitigation approaches, such as altering freshwater flow and flushing, dredging, chemical applications, introduction of selective grazers, etc. (4) Target CyanoHAB toxin production and developing management approaches to reduce toxin production. (5) Develop broadly applicable long-term strategies that incorporate the above recommendations.

Field-Validated Detection of Aureoumbra lagunensis Brown Tide Blooms in the Indian River Lagoon, Florida, Using Sentinel-3A OLCI and Ground-Based Hyperspectral Spectroradiometers

Frequent Aureoumbra lagunensis blooms in the Indian River Lagoon (IRL), Florida, have devastated populations of seagrass and marine life and threaten public health. To substantiate a more reliable remote sensing early-warning system for harmful algal blooms, we apply varimax-rotated principal component analysis (VPCA) to 12 images spanning ~1.5 years. The method partitions visible-NIR spectra into independent components related to algae, cyanobacteria, suspended minerals, and pigment degradation products. The components extracted by VPCA are diagnostic for identifiable optical constituents, providing greater specificity in the resulting data products. We show that VPCA components retrieved from Sentinel-3A Ocean and Land Colour Instrument (OLCI) and a field-based spectroradiometer are consistent despite vast differences in spatial resolution (~50 cm vs. 300 m). Furthermore, the VPCA components associated with A. lagunensis in both spectral datasets indicate high correlations to Ochrophyta cell counts (R2 ≥ 0.92, p < 0.001). Recombining components exhibiting a red-edge response produces a Chl a algorithm that outperforms empirical band ratio algorithms and preforms as well or better than a variety of semianalytical algorithms. The results from the VPCA spectral decomposition method are more efficient than traditional Empirical Orthogonal Function or PCA, requiring fewer components to explain as much or more variance. Overall, our observations provide excellent validation for Sentinel-3A OLCI-based VPCA spectral identification and indicate A. lagunensis was highly concentrated within the Banana River region of the IRL during the study. These results enable improved brown tide monitoring to identify blooms at an early stage, allowing more time for stakeholder response to this public health problem.

Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing

Cyanobacterial harmful algal blooms are the most common form of harmful algal blooms in freshwater systems throughout the world. However, in situ sampling of cyanobacteria in inland lakes is limited both spatially and temporally. Satellite data has proven to be an effective tool to monitor cyanobacteria in freshwater lakes across the United States. This study uses data from the European Space Agency Envisat MEdium Resolution Imaging Spectrometer and the Sentinel-3 Ocean and Land Color Instrument to provide a national overview of the percentage of lakes experiencing a cyanobacterial bloom on a weekly basis for 2008-2011, 2017, and 2018. A total of 2321 lakes across the contiguous United States were included in the analysis. We examined four different thresholds to define when a waterbody is classified as experiencing a bloom. Across these four thresholds, we explored variability in bloom percentage with changes in seasonality and lake size. As a validation of algorithm performance, we analyzed the agreement between satellite observations and previously established ecological patterns, although data availability in the wintertime limited these comparisons on a year-round basis. Changes in cyanobacterial bloom percentage at the national scale followed the well-known temporal pattern of freshwater blooms. The percentage of lakes experiencing a bloom increased throughout the year, reached a maximum in fall, and decreased through the winter. Wintertime data, particularly in northern regions, were consistently limited due to snow and ice cover. With the exception of the Southeast and South, regional patterns mimicked patterns found at the national scale. The Southeast and South exhibited an unexpected pattern as cyanobacterial bloom percentage reached a maximum in the winter rather than the summer. Lake Jesup in Florida was used as a case study to validate this observed pattern against field observations of chlorophyll a. Results from this research establish a baseline of annual occurrence of cyanobacterial blooms in inland lakes across the United States. In addition, methods presented in this study can be tailored to fit the specific requirements of an individual system or region.

Recent Patterns in Lake Erie Phosphorus and Chlorophyll a Concentrations in Response to Changing Loads

Despite the initial success of extensive efforts to reduce phosphorus (P) loading to Lake Erie as a part of the Great Lakes Water Quality Agreement, Lake Erie appears to be undergoing a re-eutrophication and it is plagued by harmful algal blooms. To offer insights into potential lake responses under differing Maumee River loads and reveal recent changes with time, we explored patterns in phosphorus and chlorophyll a data from 2008 to 2018 collected in western Lake Erie near the mouth of the Maumee River. We found high, but relatively stable Maumee River and lake concentrations of total P (TP) and soluble reactive P (SRP) with no discernable annual or seasonal patterns. Maumee spring TP load was not strongly related to lake TP, and lake SRP concentrations were positively but weakly related to SRP loads. Lake TP was a strong predictor of chlorophyll a, but the relationship was weaker at sites closer to the Maumee. These results highlight spatial differences both in P concentration and the relationship between TP and chlorophyll a, and these indicate that spring phosphorus loads are a weak algal biomass predictor in the portion of the western basin of Lake Erie represented by these sampling stations.

Prediction of Optical and Non-Optical Water Quality Parameters in Oligotrophic and Eutrophic Aquatic Systems Using a Small Unmanned Aerial System

The purpose of this study was to create different statistically reliable predictive algorithms for trophic state or water quality for optical (total suspended solids (TSS), Secchi disk depth (SDD), and chlorophyll-a (Chl-a)) and non-optical (total phosphorus (TP) and total nitrogen (TN)) water quality variables or indicators in an oligotrophic system (Grand River Dam Authority (GRDA) Duck Creek Nursery Ponds) and a eutrophic system (City of Commerce, Oklahoma, Wastewater Lagoons) using remote sensing images from a small unmanned aerial system (sUAS) equipped with a multispectral imaging sensor. To develop these algorithms, two sets of data were acquired: (1) In-situ water quality measurements and (2) the spectral reflectance values from sUAS imagery. Reflectance values for each band were extracted under three scenarios: (1) Value to point extraction, (2) average value extraction around the stations, and (3) point extraction using kriged surfaces. Results indicate that multiple variable linear regression models in the visible portion of the electromagnetic spectrum best describe the relationship between TSS (R2 = 0.99, p-value = <0.01), SDD (R2 = 0.88, p-value = <0.01), Chl-a (R2 = 0.85, p-value = <0.01), TP (R2 = 0.98, p-value = <0.01) and TN (R2 = 0.98, p-value = <0.01). In addition, this study concluded that ordinary kriging does not improve the fit between the different water quality parameters and reflectance values.

A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent

Harmful algal blooms (HABs) have been increasing in intensity worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework for estimating HAB intensity and extent using chlorophyll a data sampled during the HAB season (June-October) from 2008 to 2017 by five independent monitoring programs. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results demonstrate that space-time kriging explains over half of the variability in daily, location-specific chlorophyll observations, on average. Conditional simulations provide, for the first time, comprehensive estimates of overall bloom biomass (based on depth-integrated concentrations) and surface areal extent with quantified uncertainties. These new estimates are contrasted with previous Lake Erie HAB monitoring studies, and deviations among estimates are explored and discussed. Overall, results highlight the importance of maintaining sufficient monitoring coverage to capture bloom dynamics, as well as the benefits of the proposed approach for synthesizing data from multiple monitoring programs to improve estimation accuracy while reducing uncertainty.

Measurement of Cyanobacterial Bloom Magnitude using Satellite Remote Sensing

Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatiotemporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio (USA) respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Sentinel-3 Ocean Land Color Imager (OLCI) data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.

Effects of Habitat Partitioning on the Distribution of Bacterioplankton in Deep Lakes

In deep lakes, many investigations highlighted the existence of exclusive groups of bacteria adapted to deep oxygenated and hypoxic and anoxic hypolimnia. Nevertheless, the extent of bacterial strain diversity has been much less scrutinized. This aspect is essential for an unbiased estimation of genetic variation, biodiversity, and population structure, which are essential for studying important research questions such as biogeographical patterns, temporal and spatial variability and the environmental factors affecting this variability. This study investigated the bacterioplankton community in the epilimnetic layers and in the oxygenated and hypoxic/anoxic hypolimnia of five large and deep lakes located at the southern border of the Alps using high throughput sequencing (HTS) analyses (16S rDNA) and identification of amplicon sequence variants (ASVs) resolving reads differing by as little as one nucleotide. The study sites, which included two oligomictic (Garda and Como) and three meromictic lakes (Iseo, Lugano, and Idro) with maximum depths spanning from 124 to 410 m, were chosen among large lakes to represent an oxic-hypoxic gradient. The analyses showed the existence of several unique ASVs in the three layers of the five lakes. In the case of cyanobacteria, this confirmed previous analyses made at the level of strains or based on oligotyping methods. As expected, the communities in the hypoxic/anoxic monimolimnia showed a strong differentiation from the oxygenated layer, with the exclusive presence in single lakes of several unique ASVs. In the meromictic lakes, results supported the hypothesis that the formation of isolated monimolimnia sustained the development of highly diversified bacterial communities through ecological selection, leading to the establishment of distinctive biodiversity zones. The genera identified in these layers are well-known to activate a wide range of redox reactions at low O₂ conditions. As inferred from 16S rDNA data, the highly diversified and coupled processes sustained by the monimolimnetic microbiota are essential ecosystem services that enhance mineralization of organic matter and formation of reduced compounds, and also abatement of undesirable greenhouse gasses.

Efficient elimination and re-growth inhibition of harmful bloom-forming cyanobacteria using surface-functionalized microbubbles

The elimination of cyanobacteria is frequently required for treating and controlling the waters with harmful algal blooms. In this study, an improved flotation technology was developed using colloidal gas aphrons (CGAs) surface-modified with the inorganic coagulant of polyaluminum chloride (PACl); the Microcystis aeruginosa (M. aeruginosa) cells were efficiently removed and their re-growth was effectively inhibited. The so-created coagulative CGAs (CCGAs) exhibited the attractive characteristics of both CGAs and PACl for the cell removal. The experimental results clearly showed that 94.2-99.2% of cells were removed within 3 min at the optimum dosage of cetyltrimethyl ammonium bromide (CTAB) and PACl at three different initial cell densities (OD₆₈₀ = 0.05, 0.26 and 0.76); and the re-growth of M. aeruginosa did not occur in 10 days. The flocs derived from the CCGA-flotation were of smaller size and looser configuration in contrast with those obtained from coagulation-flotation. The CCGAs were robust in charge neutralization, cell capture, cell attack and destruction. Even at low CTAB dosages, those bubbles could provide large surface area for capturing the M. aeruginosa cells in both unicellular and colonial form compared with the unmodified CTAB-CGAs. The CCGAs reduced 59.5-87.9% of CTAB dosage with the assistance of PACl and the required flotation retention time was largely shortened in comparison with the sedimentation and flotation-based treatment options. This would lead to low treatment cost and sludge production. The present work provides a novel insight into the development of flotation technologies for treating and controlling dense harmful algal blooms.

Perspectives on Harmful Algal Blooms (HABs) and the Cyberbiosecurity of Freshwater Systems

Harmful Algal Blooms (HABs) have been observed in all 50 states in the U.S., ranging from large freshwater lakes, such as the Great Lakes, to smaller inland lakes, rivers, and reservoirs, as well as marine coastal areas and estuaries. In 2014, a HAB on Lake Erie containing microcystin (a liver toxin) contaminated the municipal water supply in Toledo, Ohio, providing non-potable water to 400,000 people. Studying HABs is complicated as different cyanobacteria produce a range of toxins that impact human health, such as microcystins, saxitoxin, anatoxin-a, and cylindrospermopsin. HABs may be increasing in prevalence with rising temperatures and higher nutrient runoff. Consequently, new tools and technology are needed to rapidly detect, characterize, and respond to HABs that threaten our water security. A framework is needed to understand cyber threats to new and existing technologies that monitor and forecast our water quality. To properly detect, assess, and mitigate security threats on water infrastructure, it is necessary to envision water security from the perspective of a cyber-physical system (CPS). In doing so, we can evaluate risks and research needs for cyber-attacks on HAB-monitoring networks including data injection attacks, automated system hijacking attacks, node forgery attacks, and attacks on learning algorithms. Herein, we provide perspectives on the research needed to understand both the threats posed by HABs and the coupled cyber threats to water security in the context of HABs.