Field and laboratory studies of fluorescence-based technologies for real-time tracking of cyanobacterial cell lysis and potential microcystins release.

Elevated levels of dissolved microcystins (MCs) in source water due to rapid cell lysis of harmful cyanobacterial blooms may pose serious challenges for drinking water treatment. Catastrophic cell lysis can result from outbreaks of naturally-occurring cyanophages - as documented in Lake Erie during the Toledo water crisis of 2014 and in 2019, or through the application of algaecides or water treatment chemicals. Real-time detection of cyanobacterial cell lysis in source water would provide a valuable tool for drinking water plant and reservoir managers. In this study we explored two real-time fluorescence-based devices, PhycoSens and PhycoLA, that can detect unbound phycocyanin (uPC) as a potential indication of cell lysis and MCs release. The PhycoSens was deployed at the Low Service pump station of the City of Toledo Lake Erie drinking water treatment plant from July 15 to October 19, 2022 during the annual cyanobacteria bloom season. It measured major algal groups and uPC in incoming lake water at 15-min intervals during cyanobacteria dominant and senescence periods. Intermittent uPC detections from the PhycoSens over a three-month period coincided with periods of increasing proportions of extracellular MCs relative to total (intracellular and extracellular) MCs, indicating potential for uPC use as an indicator of cyanobacterial cell integrity. Following exposures of laboratory-cultured MCs-producing Microcystis aeruginosa NIES-298 (120 µg chlorophyll/L) to cyanophage Ma-LMM01, copper sulfate (0.5 and 1 mg Cu/L), sodium carbonate peroxyhydrate (PAK® 27, 6.7 and 10 mg H2O2/L), and potassium permanganate (2.5 and 4 mg/L), appearance of uPC coincided with elevated fractions of extracellular MCs. The PhycoLA was used to monitor batch samples collected daily from Lake Erie water exposed to algaecides in the laboratory. Concurrence of uPC signal and surge of dissolved MCs was observed following 24-h exposures to copper sulfate and PAK 27. Overall results indicate the appearance of uPC is a useful indicator of the onset of cyanobacterial cell lysis and the release of MCs when MCs are present.

An assessment of a biosensor system for the quantification of microcystins in freshwater cyanobacterial blooms.

Microcystin-producing cyanobacterial blooms are a global issue threatening drinking water supplies and recreation on lakes and beaches. Direct measurement of microcystins is the only way to ensure waters have concentrations below guideline concentrations; however, analyzing water for microcystins takes several hours to days to obtain data. We tested LightDeck Diagnostics' bead beater cell lysis and two versions of the quantification system designed to give microcystin concentrations within 20 min and compared it to the standard freeze-thaw cycle lysis method and ELISA quantification. The bead beater lyser was only 30 % effective at extracting microcystins compared to freeze-thaw. When considering freeze-thaw samples analyzed in 2021, there was good agreement between ELISA and LightDeck version 2 (n = 152; R2 = 0.868), but the LightDeck slightly underestimated microcystins (slope of 0.862). However, we found poor relationships between LightDeck version 2 and ELISA in 2022 (n = 49, slopes 0.60 to 1.6; R2 < 0.6) and LightDeck version 1 (slope = 1.77 but also a high number of less than quantifiable concentrations). After the quantification issues are resolved, combining the LightDeck system with an already-proven rapid lysis method (such as microwaving) will allow beach managers and water treatment operators to make quicker, well-informed decisions.

Microcystin congeners in Lake Erie follow the seasonal pattern of nitrogen availability.

Cyanobacteria harmful algal blooms produce many toxic secondary metabolites called cyanotoxins. The most studied group of cyanotoxins are microcystins (MC), with over 300 congeners reported. MC-LR is the most studied congener because of its abundance and toxicity. Recent toxicology studies suggest that more hydrophobic MC congeners such as MC-LA, MC-LF, and MC-LW may be less abundant but up to seven times more toxic than MC-LR, whereas, MC-RR's toxicity is only one-fifth that of MC-LR. Hence, understanding the environmental stressors that change the MC congener profile is critical to assessing the negative impact on environmental and human health. A two-year field and experimental study investigated seasonal and spatial changes of MC congener profiles in the western basin of Lake Erie. Both studies showed that nitrogen enrichment favored the production of nitrogen-rich MC-RR (C49H75N13O12). The field study showed that nitrogen depletion favored the low-nitrogen MC-LA (C46H67N7O12). MC-LR (a medium N level, C49H75N10O12) accounted for ∼30% to 50% of the total MC concentration and was stable across nitrogen concentrations. Using the relative toxicity and concentrations of each MC congener, both LC-MS/MS and ELISA overestimated the toxicity early bloom (July) and underestimated it late bloom (September). On 24 July 2019, highly toxic MC-LW and MC-LF were detected at nearshore stations with relative toxicity exceeding drinking water standards. This study demonstrated that the less toxic, high nitrogen MC-RR dominated under nitrogen-replete conditions in the early season, whereas the more toxic, less nitrogen MC-LA dominated under nitrogen-limited conditions later in the season.

Quantification of microcystin production and biodegradation rates in the western basin of Lake Erie.

Cyanobacterial biomass forecasts currently cannot predict the concentrations of microcystin, one of the most ubiquitous cyanotoxins that threaten human and wildlife health globally. Mechanistic insights into how microcystin production and biodegradation by heterotrophic bacteria change spatially and throughout the bloom season can aid in toxin concentration forecasts. We quantified microcystin production and biodegradation during two growth seasons in two western Lake Erie sites with different physicochemical properties commonly plagued by summer Microcystis blooms. Microcystin production rates were greater with elevated nutrients than under ambient conditions and were highest nearshore during the initial phases of the bloom, and production rates were lower in later bloom phases. We examined biodegradation rates of the most common and toxic microcystin by adding extracellular stable isotope-labeled microcystin-LR (1 µg L-1), which remained stable in the abiotic treatment (without bacteria) with minimal adsorption onto sediment, but strongly decreased in all unaltered biotic treatments, suggesting biodegradation. Greatest biodegradation rates (highest of -8.76 d-1, equivalent to the removal of 99.98% in 18 h) were observed during peak bloom conditions, while lower rates were observed with lower cyanobacteria biomass. Cell-specific nitrogen incorporation from microcystin-LR by nanoscale imaging mass spectrometry showed that a small percentage of the heterotrophic bacterial community actively degraded microcystin-LR. Microcystin production and biodegradation rates, combined with the microcystin incorporation by single cells, suggest that microcystin predictive models could be improved by incorporating toxin production and biodegradation rates, which are influenced by cyanobacterial bloom stage (early vs. late bloom), nutrient availability, and bacterial community composition.

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.

Roles of Nutrient Limitation on Western Lake Erie CyanoHAB Toxin Production.

Cyanobacterial harmful algal bloom (CyanoHAB) proliferation is a global problem impacting ecosystem and human health. Western Lake Erie (WLE) typically endures two highly toxic CyanoHABs during summer: a Microcystis spp. bloom in Maumee Bay that extends throughout the western basin, and a Planktothrix spp. bloom in Sandusky Bay. Recently, the USA and Canada agreed to a 40% phosphorus (P) load reduction to lessen the severity of the WLE blooms. To investigate phosphorus and nitrogen (N) limitation of biomass and toxin production in WLE CyanoHABs, we conducted in situ nutrient addition and 40% dilution microcosm bioassays in June and August 2019. During the June Sandusky Bay bloom, biomass production as well as hepatotoxic microcystin and neurotoxic anatoxin production were N and P co-limited with microcystin production becoming nutrient deplete under 40% dilution. During August, the Maumee Bay bloom produced microcystin under nutrient repletion with slight induced P limitation under 40% dilution, and the Sandusky Bay bloom produced anatoxin under N limitation in both dilution treatments. The results demonstrate the importance of nutrient limitation effects on microcystin and anatoxin production. To properly combat cyanotoxin and cyanobacterial biomass production in WLE, both N and P reduction efforts should be implemented in its watershed.

Effect of temperature on phosphorus flux from anoxic western Lake Erie sediments.

The western basin of Lake Erie experiences annual Harmful Algal Blooms (HABs), which degrade water quality, threaten drinking water supplies, and deter recreation. The size of HABs in Lake Erie is highly correlated with the external loading of phosphorus (P) from a major tributary, the Maumee River, during spring and summer months. Because HAB size is largely explained by external loading, the contribution of P from lake sediments (internal loading) is considered to be minimal. However, if lake sediments become warmer and more hypoxic or anoxic in response to climate change, the relative contribution of internal P loading from sediments may become greater. In this study, we examined the potential effect of elevated lake temperatures on internal loading of P under anoxic conditions. Sediment cores were collected during Summer 2014 from 4 locations in the western basin of Lake Erie ranging from highly productive areas near Maumee Bay to less productive offshore areas. Cores were incubated for 4 days under anoxic conditions under different temperatures (10 °C, 20 °C, and 30 °C). P flux varied greatly between temperature treatments and sites. Average P flux at 20 °C and 30 °C were 2 and 14 times higher respectively, than for cores incubated at 10 °C. The site closest to the mouth of the Maumee River had the highest P flux, 10 times higher than the furthest site, and highest total P concentration in the surface sediment, 2 times higher than the furthest site, suggesting a gradient of sediment P characteristics associated with the Maumee River plume. Extrapolating these fluxes across the western basin suggests that with four days of anoxia at 30 °C, lake sediments could contribute ∼415 metric tons of dissolved P, which is equivalent to the springtime dissolved P loading from the Maumee River for 2011, the second-largest HAB on record.

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.

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.

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

Toxic cyanobacterial harmful algal blooms (cyanoHABs) are one of the most significant threats to the security of Earth's surface freshwaters. In the United States, the Federal Water Pollution Control Act of 1972 (i.e., the Clean Water Act) requires that states report any waterbody that fails to meet applicable water quality standards. The problem is that for fresh waters impacted by cyanoHABs, no scientifically-based framework exists for making this designation. This study describes the development of a data-based framework using the Ohio waters of western Lake Erie as an exemplar for large lakes impacted by cyanoHABs. To address this designation for Ohio's open waters, the Ohio Environmental Protection Agency (EPA) assembled a group of academic, state and federal scientists to develop a framework that would determine the criteria for Ohio EPA to consider in deciding on a recreation use impairment designation due to cyanoHAB presence. Typically, the metrics are derived from on-lake monitoring programs, but for large, dynamic lakes such as Lake Erie, using criteria based on discrete samples is problematic. However, significant advances in remote sensing allows for the estimation of cyanoHAB biomass of an entire lake. Through multiple years of validation, we developed a framework to determine lake-specific criteria for designating a waterbody as impaired by cyanoHABs on an annual basis. While the criteria reported in this manuscript are specific to Ohio's open waters, the framework used to determine them can be applied to any large lake where long-term monitoring data and satellite imagery are available.

Updating the ELISA standard curve fitting process to reduce uncertainty in estimated microcystin concentrations.

This study is aimed at exploring the optimal ELISA standard curve fitting process for reducing measurement uncertainty. Using an ELISA kit for measuring cyanobacterial toxin (microcystin), we show that uncertainty associated with the estimated microcystin concentrations can be reduced by defining the standard curve as a four-parameter logistic function on the natural log concentration scale, instead of the current approach of defining the curve on the concentration scale. The model comparison method is outlined in this paper, allowing it to be transferable to test different statistical models for other ELISA test kits.

The reduction of Chlorella vulgaris concentrations through UV-C radiation treatments: A nature-based solution (NBS).

Algal blooms have become a pressing issue in inland freshwater systems on local and global scales. A plausible approach to reducing algae without the use of chemical/biological agents is through the use of UV-C radiation from lamps potentially powered by in situ solar panels to eliminate algae. Yet, the quantitative scientific base has not been established. Our objective is to conduct a controlled experiment to quantify the effectiveness of UV-C radiation on the reduction of Chlorella vulgaris, a common algal species in the Great Lakes region. A full factorial design of three intensities of UV-C radiation (0, 15, and 30W) and three sources of C. vulgaris was constructed to test the corresponding hypotheses. Empirical models were constructed to predict the reductions. UV-C radiation effectively reduced the algal concentration with clear differences by radiation level and source of algal water. Algal concentration decreased exponentially over time, with distinct decreasing trends among the radiation intensities and the samples. With 15W UV-C radiation, algal concentration of three samples were reduced to 75.3%, 51.5%, and 70.0% of the initial level within an hour, respectively. We also found a clear density-dependent reduction rate by UV radiation. Using this information, more efficient treatment systems could be constructed and implemented for cleaning algae-contaminated water.

Tracking cyanobacteria blooms: Do different monitoring approaches tell the same story?

Cyanobacteria blooms are a major environmental issue worldwide. Our understanding of the biophysical processes driving cyanobacterial proliferation and the ability to develop predictive models that inform resource managers and policy makers rely upon the accurate characterization of bloom dynamics. Models quantifying relationships between bloom severity and environmental drivers are often calibrated to an individual set of bloom observations, and few studies have assessed whether differences among observing platforms could lead to contrasting results in terms of relevant bloom predictors and their estimated influence on bloom severity. The aim of this study was to assess the degree of coherence of different monitoring methods in (1) capturing short- and long-term cyanobacteria bloom dynamics and (2) identifying environmental drivers associated with bloom variability. Using western Lake Erie as a case study, we applied boosted regression tree (BRT) models to long-term time series of cyanobacteria bloom estimates from multiple in-situ and remote sensing approaches to quantify the relative influence of physico-chemical and meteorological drivers on bloom variability. Results of BRT models showed remarkable consistency with known ecological requirements of cyanobacteria (e.g., nutrient loading, water temperature, and tributary discharge). However, discrepancies in inter-annual and intra-seasonal bloom dynamics across monitoring approaches led to some inconsistencies in the relative importance, shape, and sign of the modeled relationships between select environmental drivers and bloom severity. This was especially true for variables characterized by high short-term variability, such as wind forcing. These discrepancies might have implications for our understanding of the role of different environmental drivers in regulating bloom dynamics, and subsequently for the development of models capable of informing management and decision making. Our results highlight the need to develop methods to integrate multiple data sources to better characterize bloom spatio-temporal variability and improve our ability to understand and predict cyanobacteria blooms.

Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions.

In 2011, Lake Erie experienced the largest harmful algal bloom in its recorded history, with a peak intensity over three times greater than any previously observed bloom. Here we show that long-term trends in agricultural practices are consistent with increasing phosphorus loading to the western basin of the lake, and that these trends, coupled with meteorological conditions in spring 2011, produced record-breaking nutrient loads. An extended period of weak lake circulation then led to abnormally long residence times that incubated the bloom, and warm and quiescent conditions after bloom onset allowed algae to remain near the top of the water column and prevented flushing of nutrients from the system. We further find that all of these factors are consistent with expected future conditions. If a scientifically guided management plan to mitigate these impacts is not implemented, we can therefore expect this bloom to be a harbinger of future blooms in Lake Erie.

Detection and quantification of Microcystis spp. and microcystin-LR in Western Lake Erie during the summer of 2007.

Microcystis spp. blooms have occurred annually in western Lake Erie since about 1995. Microcystis produce a group of toxins known as microcystins which can be harmful to livestock and to humans. In this study, surface water samples were collected from six sites during six sampling events from July to October in 2007. In situ environmental data (e.g. pH, temperature) and laboratory analyses (e.g. nutrients) were carried out to characterize the six sites. The Microcystis spp. density ranged from 10(2) to 10(7) cells/ml. Microcystin-LR concentration of 20 of all 36 samples were below the detection limit (0.15-5 ppb), while the microcystin-LR concentration in the 16 remaining samples ranged from 0.5 to 3 x 10(3) microg per gram dry weight. The aim of this research was to investigate the relationships between sampling location, environmental parameters, Microcystis spp. concentration, and microcystin-LR concentration. The results suggest that temperature, nutrient concentration, turbidity, and wind speed and direction (P<0.05) are factors which affected Microcystis spp. density. Sampling site 8M, located 13 m from the Maumee River, provided an advantage for Microcystis spp. growth, presumably due to intermediate water depth (5.5 m) combined with impact from the river. No relationship was found between Microcystis spp. density and microcystin-LR concentration. Temperature, nutrient concentration and DO (P<0.05) were associated with the production of microcystin-LR.

Recruitment of Hexagenia mayfly nymphs in western Lake Erie linked to environmental variability.

After a 40-year absence caused by pollution and eutrophication, burrowing mayflies (Hexagenia spp.) recolonized western Lake Erie in the mid 1990s as water quality improved. Mayflies are an important food resource for the economically valuable yellow perch fishery and are considered to be major indicator species of the ecological condition of the lake. Since their reappearance, however, mayfly populations have suffered occasional unexplained recruitment failures. In 2002, a failure of fall recruitment followed an unusually warm summer in which western Lake Erie became temporarily stratified, resulting in low dissolved oxygen levels near the lake floor. In the present study, we examined a possible link between Hexagenia recruitment and periods of intermittent stratification for the years 1997 2002. A simple model was developed using surface temperature, wind speed, and water column data from 2003 to predict stratification. The model was then used to detect episodes of stratification in past years for which water column data are unavailable. Low or undetectable mayfly recruitment occurred in 1997 and 2002, years in which there was frequent or extended stratification between June and September. Highest mayfly reproduction in 2000 corresponded to the fewest stratified periods. These results suggest that even relatively brief periods of stratification can result in loss of larval mayfly recruitment, probably through the effects of hypoxia. A trend toward increasing frequency of hot summers in the Great Lakes region could result in recurrent loss of mayfly larvae in western Lake Erie and other shallow areas in the Great Lakes.