Algal Blooms Research Articles

Compositions, sources, and bioavailability of colloidal organic matter in Lake Taihu

Colloidal organic matter (COM) exists ubiquitously in natural waters, and plays a pivotal role in biogeochemical cycles. Lake Taihu is confronted with severe eutrophication and algal blooms. Field investigations were carried out in Lake Taihu and two inflow rivers for two years to identify the source of COM and explore the bioavailability of COM to algae. Compositions and sources of COM were analyzed through UV absorption coefficients and parallel factor analysis of three-dimensional excitation emission matrix spectra (3D EEMs-PARAFAC). Absorption coefficient a(350) of COM in rivers surpassed that in the lake, SUVA254 exhibited noteworthy seasonal variations, and SR indicated a stable autochthonous characteristic. Three components were identified by PARAFAC analysis: tryptophan-like (C1), humic-like (C2), and tyrosine-like (C3). Fluorescence indexes showed that C1 and C3 were mainly autochthonously produced and C2 was derived from allochthonous inputs. The bioassays were conducted to assess the bioavailability of COM to the dominant species, Microcystis aeruginosa. The results showed that colloids supplied rich carbon sources and trace metals, supporting the growth of Microcystis aeruginosa. The specific growth rate, Chl a content, and biological increment of Microcystis aeruginosa in 50 % colloid-added treatment exceeded those in 20 % and 75 % treatments. Simultaneously, the effective quantum yield (Fv/Fm) and the apparent photosynthetic electron transport rate (ETRmax) demonstrated that the photosynthetic activity of Microcystis aeruginosa was higher in 20 % treatment. These findings help in understanding the intricate mechanisms of COM in lake ecosystems, and provide the robust scientific foundation for water management and protection in Lake Taihu.

Methane dynamics altered by reservoir operations in a typical tributary of the Three Gorges Reservoir

Substantial nutrient inputs from reservoir impoundment typically increase sedimentation rate and primary production. This can greatly enhance methane (CH4) production, making reservoirs potentially significant sources of atmospheric CH4. Consequently, elucidating CH4 emissions from reservoirs is crucial for assessing their role in the global methane budget. Reservoir operations can also influence hydrodynamic and biogeochemical processes, potentially leading to pronounced spatiotemporal heterogeneity, especially in reservoirs with complex tributaries, such as the Three Gorges Reservoir (TGR). Although several studies have investigated the spatial and temporal variations in CH4 emissions in the TGR and its tributaries, considerable uncertainties remain regarding the impact of reservoir operations on CH4 dynamics. These uncertainties primarily arise from the limited spatial and temporal resolutions of previous measurements and the complex underlying mechanisms of CH4 dynamics in reservoirs. In this study, we employed a fast-response automated gas equilibrator to measure the spatial distribution and seasonal variations of dissolved CH4 concentrations in XXB, a representative area significantly impacted by TGR operations and known for severe algal blooms. Additionally, we measured CH4 production rates in sediments and diffusive CH4 flux in the surface water. Our multiple campaigns suggest substantial spatial and temporal variability in CH4 concentrations across XXB. Specifically, dissolved CH4 concentrations were generally higher upstream than downstream and exhibited a vertical stratification, with greater concentrations in bottom water compared to surface water. The peak dissolved CH4 concentration was observed in May during the drained period. Our results suggest that the interplay between aquatic organic matter, which promotes CH4 production, and the dilution process caused by intrusion flows from the mainstream primarily drives this spatiotemporal variability. Importantly, our study indicates the feasibility of using strategic reservoir operations to regulate these factors and mitigate CH4 emissions. This eco-environmental approach could also be a pivotal management strategy to reduce greenhouse gas emissions from other reservoirs.

Scenario-Based Modeling on Chlorophyll-a in Uiam Reservoir of Korea According to Variation of Dam Discharge

This study analyzes quantitative algae mitigation, using chlorophyll-a as an indicator, through waterbody management techniques such as pulses released from upstream dams, employing a three-dimensional numerical model. Numerical simulations focused on algae reduction through dam operations by investigating nine scenarios based on Chuncheon Dam, Soyang Dam, and Uiam Dam, located in the upper and lower reaches of Uiam Reservoir of Korea. These scenarios, aligned with actual dam operation manuals, aimed to differentiate the impact of each dam’s operation by decreasing water residence time for Uiam Reservoir. The Uiam Reservoir, smaller than the upstream Chuncheon Dam and Soyang River Dam, is significantly influenced by their discharge rates. During summer, temperature differences exceeding 7 °C between discharges from Chuncheon Dam and Soyang Dam inflowed into the right side and the left side, respectively, of the reservoir, leading to poor mixing, which was further hindered by islands within the reservoir. Consequently, due to the influence of the different base water temperatures of the Bukhan River and Soyang River and the topographical characteristics, the impact range varied depending on the operation of each dam, and the amount of algae mitigation differed at each point. In emergency situations where algae blooms proliferate rapidly, appropriate dam operations in water bodies with large dams upstream and downstream, like Uiam Reservoir, can be effective in mitigating algae at specific regions of the reservoir.

Investigating the influence of measurement uncertainty on chlorophyll-a predictions as an indicator of harmful algal blooms in machine learning models

Advancements in data availability, including high frequency, near real-time multiparameter sensors, laboratory analysis, and in-situ and remote observations, have driven the development of machine learning (ML) models for applications such as toxic Harmful Algal Bloom (HABs) monitoring. However, the performance of ML predictions is influenced by both model uncertainties due to inherent model structures and errors associated with input dataset measurements. For example, measurement uncertainty arises from sample collection, sensor drift and laboratory analysis and sample handling errors. While impacts of model uncertainty are commonly addressed using probabilistic approaches, the effect of measurement uncertainty is less studied due to the limited availability of detailed measurement information. This study focuses on assessing the impact of measurement uncertainty on the ML prediction of chlorophyll-a concentration as an index of HABs in a mesotrophic lake. Using randomized subsets of input measured datasets that mimic possible chlorophyll-a concentration distributions, the study built 1000 Random Forest (RF) and Support Vector Regression (SVR) models. An independent measured dataset was used to validate the ensemble models, allowing for model performance evaluation and the creation of prediction intervals to measure the propagated uncertainty. Our findings showed that the model predictions have MAE that ranged between 0.16 μg/l and 5.19 μg/l, and RMSE ranging between 0.20 μg/l and 7.39 μg/l. The highest uncertainty coverage of 0.71 was observed in the RF model without chlorophyll-a sensor values as a predictor. The study found that the training dataset sizes due to the high frequency and manually sampled nature influence how much measurement uncertainty is covered. The results of this study demonstrate how well ML models can capture various HABs patterns when given diverse measurement variables. Our findings will give researchers insightful information on how to lessen the impact of measurement uncertainty when using ML models as decision-support tools for HABs management.

Enhancing algal bloom forecasting: A novel framework for machine learning performance evaluation during periods of special temporal patterns

The evaluation of algal bloom forecasting models typically relies on error metrics that quantify the forecasting performance over the whole test set as a single number. Furthermore, the comparison with simple baseline methods is often omitted. To address this, we introduce a novel framework for Model performance Analysis and Visualization of time series forecasting (MAVts). MAVts incorporates novel algorithms for the automatic identification and visualization of time series periods of interest where the forecasting models are evaluated and compared with simple baseline methods. The application of MAVts on evaluating algal bloom forecasting models composed of sophisticated machine learning (ML) methods, reveals that in 85% of experiments a single error metric is not enough and only in 12.5% of experiments a ML model outperforms all baselines on all metrics and periods of interest. Thus, MAVts emerges as a valuable tool for analyzing and comparing ML models, advancing environmental management and protection.

Effects of Relative Humidity and Phase on the Molecular Detection of Nascent Sea Spray Aerosol Using Extractive Electrospray Ionization.

Online mass spectrometry techniques, such as extractive electrospray ionization mass spectrometry (EESI-MS), present an attractive alternative for analyzing aerosol molecular composition due to reduced aerosol sample collection and handling times and improved time resolution. Recent studies show a dependence of EESI-MS sensitivity on particle size and mixing state. This study measured authentic sea spray aerosol (SSA) components generated during a phytoplankton bloom, specifically glycerol, palmitic acid, and potassium ions. We demonstrate temporal variability and trends dependent on specific biological processes occurring in seawater. We found that the EESI-MS sensitivity, after adjusting for pressure variations at the inlet and normalizing to the reagent ion, critically depends on the sample's relative humidity. Relevant SSA species exhibited heightened sensitivity at an elevated relative humidity near the deliquescence relative humidity of sea salt and poorer sensitivity with sparse detection below the efflorescence relative humidity. Modeling the reagent ion's diffusive depth demonstrates that the sample aerosol particle viscosity governs the relative humidity dependence because it modulates the particle's coagulation efficiency and distance the reagent ion diffuses and reacts with components in the particle bulk. The effects of particle size and mixing state are discussed, revealing improved sensitivity of phase-separated components present along the particle surface. This work highlights the importance of the particle phase state in detecting and quantifying molecular components within authentic and complex aerosol particles and the utility of EESI-MS for measuring SSA composition.

Ignited competition: Impact of bioactive extracellular compounds on organelle functions and photosynthetic systems in harmful algal blooms.

Prevalent interactions among marine phytoplankton triggered by long-range climatic stressors are well-known environmental disturbers of community structure. Dynamic response of phytoplankton physiology is likely to come from interspecies interactions rather than direct climatic effect on single species. However, studies on enigmatic interactions among interspecies, which are induced by bioactive extracellular compounds (BECs), especially between related harmful algae sharing similar shellfish toxins, are scarce. Here, we investigated how BECs provoke the interactions between two notorious algae, Alexandrium minutum and Gymnodinium catenatum, which have similar paralytic shellfish toxin (PST) profiles. Using techniques including electron microscopy and transcriptome analysis, marked disruptions in G. catenatum intracellular microenvironment were observed under BECs pressure, encompassing thylakoid membrane deformations, pyrenoid matrix shrinkage and starch sheaths disappearance. In addition, the upregulation of gene clusters responsible for photosystem-I Lhca1/4 and Rubisco were determined, leading to weaken photon captures and CO2 assimilation. The redistribution of lipids and proteins occurred at the subcellular level based on in situ focal plane array FTIR imaging approved the damages. Our findings illuminated an intense but underestimated interspecies interaction triggered by BECs, which is responsible for dysregulating photosynthesis and organelle function in inferior algae and may potentially account for fitness alteration in phytoplankton community.

When an explosion of life leads to death – hypoxic zones in the Menilite Shales from the Silesian Unit (Polish Outer Carpathians)

Oligocene siliciclastics belonging to the Silesian Unit in the Outer Carpathians were sampled from five locations (Iwonicz Zdrój, Krosno, Równe, Rymanów Zdrój, Zmysłówka) with the first four locations connected to Menilite Shales. The sample from Zmysłówka is an example of the lowermost part of the Krosno Beds. Preliminary geochemical results obtained from the Rock-Eval analysis suggested the presence of immature mixed II/III Type kerogen. Detailed geochemical (GC-MS) and petrological analyses show evidence of extensive phytoplankton blooms, causing the occurrence of episodic ferruginous hypoxic zones. Hypoxic zones were present in the photic zone, where molecular evidence of green and/or brown pigmented sulfur reducing bacteria were marked. The size and character of the blooms were controlled by the palaeoenvironmental conditions. In cases of intense nutrient-rich freshwater loading by a palaeoestuary and/or rainfall, extensive algal blooms were reported. With the increasing aridity and/or decrease of the palaeoestuary impact, the phytoplankton blooms gradually acquired a mostly bacterial character and were reduced in size. The most hypoxic conditions were noted in causes linked with the most intense algal blooms. In most of the cases, algal blooms were dominated by diatoms, suggested by the extensive presence of C25 Highly Branched Isoprenoid, a specific biomarker linked with these organisms. The dinoflagellates only recorded a dominant role in blooms in the Krosno location. A comparison of diterpenoids and triterpenoids revealed that terrestrial organic matter was mostly dominated by gymnosperms like conifers from the Cupressaceae, Pinaceae and Podocarpaceae families. Beside these, the molecular evidence of the angiosperms, bryophytes, and fungi was marked. Both geochemical and petrological analyses confirm the minor role of palaeo-wildfires in the land areas near the deposition place of the analysed samples.

Organic matter composition fluctuations disrupt free-living bacterial communities more than particle-associated bacterial communities in coastal waters

Marine organic matter fuels the growth of microbial communities, shaping the composition of bacteria that specialize in its breakdown. However, responses of free-living (FL) and particle-associated (PA) bacterial communities to the changing pools of dissolved organic matter (DOM) and particulate organic matter (POM) remained unclear. This study investigates the composition of size-fractionated bacterial communities, DOM and POM in coastal waters over a 22-day period that includes a diatom bloom. Co-occurrence analysis showed that the FL bacterial communities were significantly less stable than PA communities. During the diatom bloom, we observed a significant increase in DOM molecules, particularly those derived from amino acids and peptides. In contrast, the relative intensities of major POM molecule classes remained stable despite the algal bloom's influence. Our study revealed a strong negative correlation between bacterial alpha-diversity and the amount of molecules in the organic matter pool. Similarly, bacterial community beta-diversity was found to be related to the composition of organic matter pool. However, the composition of organic matter was more strongly related to the composition of FL bacterial communities compared to PA communities. This suggests that FL bacteria exhibit greater variations in temporal dynamics and higher sensitivity to the specific structure of organic matter molecules.

Identification of microalgal particles using pixel feature analysis of Mueller matrix images

Fine sorting of aquatic particles is of great significance for water environment monitoring. Natural water contains aquatic particles that exhibit a high degree of diversity and complexity, and the identification of aquatic particles remains a persistent challenge in the field. In this article, we propose a new technique for identifying the target species of microalgal particles by using the pixel feature analysis of Mueller matrix images. This technique is independent of any prior knowledge or data about the existing particles in the environment, which is advantageous when applied to real-world situations. The pixel-level polarimetric features are fully leveraged to construct polarization feature templates, which can be used to characterize and filter specific microalgal particles in complex environments. This method could enable the accurate detection of harmful algal blooms species in natural water, which can facilitate early warning of algal blooms. The preliminary results show that the recall rate reached 97.2%, and the average accuracy is 98.9%, which demonstrate the effectiveness of this approach for identifying the target species of aquatic particles in natural water.

Recovery capacity of constructed wetlands in response to multiple disturbances: Microbial interaction perspective

Previous studies have predominantly explored the response mechanisms of constructed wetlands (CWs) to singular disturbances. In practical applications, CWs are frequently subject to multiple disturbances, resulting in complex interference mechanisms. Therefore, this study aims to select harmful algal blooms and microalga ZM-5 as disturbances to investigate the response mechanisms of CWs. Results revealed a dynamic pattern in COD removal efficiency of CWs, with fluctuations at 39.0 ± 6.2 % and 80.1 ± 4.7 % during the disturbances, followed by a recovery to approximately 65.7 ± 3.2 %. Additionally, the CWs exhibited a capacity for self-recovery and enhanced stability by selectively promoting specific microbial communities through the regulation of the genes responsible for indole-3-acetic acid (IAA) and vitamin production. Importantly, this study underscored the establishment of a resilient microbial community structure within CWs following multiple disturbances, characterized by a more interconnected microbial network. These findings shed light on the adaptive mechanisms of CWs in the face of complex environmental challenges.

Geomorphological controls on estuary hydrodynamics with implications for diatom blooms in deglaciated coastal areas

Understanding local hydraulic conditions is imperative to coastal harmful algal bloom (HAB) monitoring. The research summarized herein describes how the locations and tidal phases selected for coastal hazard sampling can influence measurement results used to guide management decisions for HABs. Our study was conducted in Frenchman Bay, Maine, known for its complex deglaciated coastline, strong tidal influence, and shellfishing activities that are susceptible to problematic HABs such as those produced by some species (spp.) of the diatom genus Pseudo-nitzschia. In-situ measurements of current velocity, density, and turbulence collected over a semidiurnal tidal cycle and a companion numerical model simulation of the study area provide concurrent evidence of two adjacent counter-rotating sub-mesoscale eddies (2–4 km diameter) that persist in the depth-averaged residual circulation. The eddies are generated in the wake of several islands in an area with abrupt bathymetric gradients, both legacy conditions partly derived from deglaciation ∼15 kya. Increased concentrations of Pseudo-nitzschia spp. measured during the semidiurnal survey follow a trend of elevated turbulent dissipation rates near the water surface, indicating that surface sampling alone might not adequately indicate species abundance. Additional measurements of Pseudo-nitzschia spp. from two years of weekly sampling in the region show that algal cell abundance is highest where residual eddies form. These findings provide incentive to examine current practices of HAB monitoring and management by linking coastal geomorphology to hydraulic conditions influencing HAB sampling outcomes, coastal morphometric features to material accumulation hotspots, and millennial time scales to modern hydraulic conditions.

Key roles of carbon metabolic intensity of sediment microbes in dynamics of algal blooms in shallow freshwater lakes

Key roles of carbon metabolic intensity of sediment microbes in dynamics of algal blooms in shallow freshwater lakes

The interaction mechanisms of algal organic matter (AOM) and various types and aging degrees of microplastics

Algal blooms can produce substantial amounts of algal organic matter (AOM). Microplastics (MPs) in aquatic environments inevitably interact with AOM. Meanwhile, the aging and type of MPs may increase the uncertainty surrounding interaction. This study focused on polyethylene (PE) and polylactic acid (PLA) to investigate their interaction with AOM before and after aging. The results shw that PLA has a stronger adsorption capacity for AOM than PE. Meanwhile, aging enhanced and weakened the adsorption of PE and PLA for AOM. Compared to unaged PE (UPE) and aged PLA (APLA), aged PE (APE) and unaged PLA (UPLA) more significantly promote the humification of AOM and alter its functional groups. 2D-IR-COS analysis reveals that the sequence of functional group changes in AOM interacting with MPs is influenced by the type and aging of MPs. After interacting with AOM, surface roughness increased for all MPs. FTIR and XPS analyses show that the addition of AOM accelerated the oxidation of MPs surfaces, especially for UPE and APLA, with oxygen content increasing by 9.32 % and 1 %. Aging enhances the interaction between PE and AOM, while weakening the interaction between PLA and AOM. These findings provide new insights into understanding the interplay between AOM and MPs.

Developing a Genetic Algorithm for Selecting Infrastructure Modifications that Optimize Hydrodynamic Flushing in Old Tampa Bay

Impermeable infrastructure such as traffic causeways can reduce the natural hydrodynamic flushing of an estuary, resulting in reduced water quality and increased incidence of harmful algal blooms (HABs). A series of cuts through the three causeways spanning Old Tampa Bay, FL, (OTB) are being considered to help restore the natural circulation of the region, but the number of possible location combinations is computationally challenging to fully assess. A prototype genetic algorithm (GA) was developed to identify the optimal configuration of these cuts through one of the bridge sections that maximizes flushing as represented in a numerical ocean circulation model of OTB. Flushing was measured by integrating the trajectories of over 21,000 passive Lagrangian “particles” using the model velocity fields. The rate of loss of particles initialized near Feather Sound (a region subject to frequent HABs) was used to quantify the “fitness” over which the configurations were optimized. The highest-scoring solution produced a 42% increase in net flushing compared to a no-change baseline. Six independently initialized applications of the GA were conducted. All converged to the same solution within no more than 7 generations. The small population size of the prototype allowed testing of the complete solution space, and verification the found solution was optimal. Elitism (preservation of the highest-ranking solution) was required for convergence. The GA also identified configurations that had similar, but slightly slower, flushing rates. These results will help area managers prioritize or rank combinations of causeway modifications to improve overall water quality conditions in Tampa Bay.

Seasonality of amino acid enantiomers and microbial communities at MOLA time series in the NW Mediterranean Sea

Seasonality in light, temperature, and nutrient availability are well-known to regulate phytoplankton blooms and the bacterioplankton community. During the spring bloom, phytoplankton release biomolecules as part of the dissolved organic matter (DOM) pool exploited by the bacterioplankton. Here, we investigated the seasonal variability of phytoplankton biomass, enantiomers of dissolved hydrolyzable amino acids (DHAA), bacterioplankton abundances and community composition at the Microbial Observatory Laboratory Arago (MOLA) in the NW Mediterranean Sea from 2019 to 2021. Phytoplankton biomass estimated from pigment biomarkers suggests a spring bloom succession from cryptophytes, haptophytes, and prasinophytes in March to diatoms in April. The spring bloom coincided with a 50% increase in L-enantiomers of DHAA and an increase in bacterial abundance. After the spring bloom, elevated concentrations of D-enantiomers of DHAA and gamma-aminobutyric acid suggest bacterial processing of labile biomolecules contributed to the seasonal accumulation of dissolved organic carbon (DOC). Linking organic molecules with the free-living bacterioplankton community showed a seasonal succession of niches and substrate regimes. The parallel analysis of DOM and bacterioplankton community provides an important baseline for bacteria-substrate relationships over the seasonal cycle in the northwestern Mediterranean Sea.

Inhibition of JNK transcription via the Nrf2/Keap1a pathway to resist microcystin-induced oxidative stress and apoptosis in freshwater mussels Cristaria plicata

With global warming and increasing eutrophication of water bodies, a variety of algal toxins, including microcystin (MC), released into water by cyanobacterial blooms pose a serious threat to the survival of aquatic organisms. To investigate the mechanism of the Nrf2/Keap1a pathway on resisting MC-induced oxidative stress and apoptosis in Cristata plicata, we cloned the full-length cDNA of CpBcl-2. The cDNA full-length of CpBcl-2 was 760 bp, encoded a 177 amino acid peptide, and contained a highly conserved Bcl-2-like superfamily domain. MC stimulation increased the expression and activity levels of related antioxidant enzymes. After CpNrf2 knockdown, the transcription levels of NAD(P)H quinone redox Enzyme-1 (NQO1) and related antioxidant enzymes activity in the gills and kidney of C. plicata were significantly down-regulated upon MC stress, but that was significantly upregulated after knockdown of CpKeap1a. Additionally, Upon MC stress, the mRNA levels of CpBcl-2 were increased in the gills and kidney after knockdown of CpNrf2 at 24 h, and that of CpBcl-2 were decreased at 72 and 96 h in the CpKeap1a-siRNA+MC group. Moreover, MC stimulation significantly inhibited CpJNK expression in the gills and kidney, but which regulated the Nrf2/Keap1a pathway in C. plicata. However, the JNK inhibitor SP600125 promoted the expression of CpNrf2 and related enzymes with antioxidant response element (ARE-driven enzyme) in the gills and kidney. Then, we speculated that CpKeap1a was a negative regulator of CpNrf2, and C. plicata resisted MC-induced oxidative damage and apoptosis by inhibiting JNK transcription via the Nrf2/Keap1a pathway.

Cyanobacterial Blooms in Environmental Water: Causes and Solutions

Cyanobacterial Blooms in Environmental Water: Causes and Solutions

The causes of algal blooms exist significant scale effect in tributary of the Three Gorges Reservoir

Algal blooms of rivers becomes a global issue, while there is controversy over the attribution of blooms due to the differences of research scales. This study utilized random forest and spatiotemporal geographically weighted models to explore the triggers and mechanisms of blooms from the different spatial resolutions (river, local and grid scales) in tributary bay of the Three Gorges reservoir based on Sentinel-2 data and Environmental Fluid Dynamics Code model. The results indicated that blooms in the Daning River were more severe during the spring and summer, with the average chlorophyll about 10.15 ug/L and 9.55 ug/L. The high-risk areas primarily located in the middle reaches (10.65 ug/L). The causes of blooms existed significant scaling effect. The water temperature recognized at the river scale was not a sufficient condition for blooms in the early stage of drainage. Compared with temperature, the relative importance of Zme ranked in the top three, which highlighted the influences of Zme at the local and grid scales. The macro-analysis identified the importance of water level fluctuations during drainage stage and the low level period, with ranking in the top two. The effects indirectly altered Zme and Zm, thus highlighting triggering effect of Zme and Zm at local scales. During the stage, thermal stratification and water circulation patterns determined the heterogeneity of blooms. The lag time between chlorophyll and these key factors ranged from 1 to 5 days. This diagnostic to the spatiotemporal scale contributes to understand of the formation mechanism of algal blooms in the tributary bay of the Three Gorges reservoir, providing reference for early warning and prevention strategy.

A sequence of weather‐driven hydrodynamic events stimulates the formation of harmful algal blooms on an oligotrophic lake

AbstractHarmful algal blooms (HABs) are common in many eutrophic lakes and frequently associated with nutrient excesses, warm waters, and calm conditions. While HABs can also occur in oligotrophic waterbodies, bloom‐stimulating factors remain elusive for these ecosystems. Here, using a high‐frequency sensor platform supported by hydrodynamic modeling, we document a clearly linked sequence of three hydrodynamic events that immediately preceded each HAB event on Skaneateles Lake, NY during 2018. HABs were first preceded by interactions between internal waves in the thermal structure of the lake with the northern slope of the lakebed. These interactions disturbed sediments resulting in upwelling of nutrient‐rich sediment and possibly cyanobacterial cells into the lower water column. Next, moderate winds stimulated Langmuir circulation which facilitated the transport of material from the lower water column to well‐lit surface waters. Finally, the sequence culminated with a calm wind period, which is often classically associated with surface HAB formation. While individual steps in this sequence occurred independently and repeatedly throughout the year, the complete sequence occurred only eight times, immediately preceding each of the eight documented HABs. We empirically derive thresholds for and timing of the sequence to independently predict HAB occurrence and elevated cyanobacteria levels in the lake. The discovery of this specific and repeated event sequence and the identified thresholds provides the potential for forecasting of HABs days in advance. Ongoing climate change impacts, including increasing water column thermal stratification and changing wind speeds may alter the frequency, timing, and duration of this sequence and consequent HAB formation.