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Concerted efforts have been made to reduce the occurrence and frequency of algal blooms in the Great Lakes via phosphorus abatement. Despite this, blooms remain common in shallow, nutrient enriched nearshore habitats. From a food web perspective, algal blooms are complex ecological entities that include autotrophs (phytoplankton, picoplankton) and heterotrophs (bacteria, nanoflagellates, ciliates, rotifers, zooplankton). Our research and monitoring programs have captured a variety of blooms (Cyanobacteria, diatoms etc) from the Bay of Quinte and Hamilton Harbour in Lake Ontario as well as from western Lake Erie. The contribution of heterotrophs during bloom events can be similar to or even larger than that of phytoplankton. In the Bay of Quinte (2018), for example, heterotrophs accounted for 38 - 63% of the total planktonic biomass during bloom events with varying contributions from bacteria (17 - 22%), heterotrophic nanoflagellates (4 - 38%) and zooplankton (2 - 20%). Preliminary results suggest that all types of algal blooms, not just ones exhibiting toxicity, can have a significant ecological impact. The current paper will explore the taxonomic structure of the phytoplankton community during bloom events and consider the heterotrophic contributions in order to promote a better understanding of the ecological implications of algal blooms. [ABSTRACT FROM AUTHOR]

Algal bloom phenomena are increasingly occurring in many urban lakes worldwide. To enhance understanding of how environmental factors influence the development of harmful algal bloom (HAB), a preliminary study was carried out at one of the inlets in Putrajaya Lake. Physicochemical variables, nutrients, weather conditions, chlorophyll-a, and phycocyanin were measured over two weeks. Algal indicators, namely chlorophyll-a values, were strongly correlated to dissolved oxygen (DO), pH, conductivity, turbidity and nitrate. There is no correlation recorded between chlorophyll-a with phosphate and total phosphorus. This preliminary study showed the complex relationship influencing algal development and bloom formation. Blue-green algae (BGA) was the most dominant phytoplankton assemblages during the study. A positive correlation was also observed between chlorophyll-a and solar radiation, temperature, and wind speed. Despite no strong correlation between chlorophyll-a and rainfall amount, a strong relationship between chlorophyll-a and turbidity indicated other environmental factors contributing to algal bloom occurrence. BGA density was correlated to DO, pH, turbidity, air temperature and nitrate. Management measures recommended to reduce algal bloom development include external nutrient reduction through the constructed wetland. Artificial mixing is also recommended to improve vertical mixing and circulation pattern. [ABSTRACT FROM AUTHOR]

To further investigate our understanding of biological processes in mathematical terms, we study the full original model of prey and predator interactions studied previously. We consider three species populations: phytoplankton (P); microzooplankton (M); and the volatile chemical released (C).We previously considered C as constant, due to the fact that we used a short time-scale experimentally to explore the effect of the signaling chemical released, DMS (C). To further elucidate the function of Infochemical-mediated plankton interaction and phytoplankton bloom formation, we explored the dynamics of the model across the full range of a few parameters, both numerically and analytically. All current result are compared to the results in our previous publications. [ABSTRACT FROM AUTHOR]

Harmful Algal Blooms (HABs) are an annual threat to millions of people living along the coast of Lake Erie; the toxins produced by these cyanobacterial blooms pose a risk to drinking water and negatively impact industries such as fisheries and tourism. Starting in 2016, the NWS Ohio River Forecast Center (OHRFC) has supported NOAA's National Centers for Coastal Ocean Science (NOAA/NOS/NCCOS) by providing daily Climate Forecasting System (CFS) 60-day flow forecasts. These forecasts for the Maumee River are used to improve predictions of phosphorus loading in their Lake Erie HAB forecast products. Recent introduction of the Hydrologic Ensemble Forecasting System, which can provide bias-correction for these hydrologic forecasts as well as give a longer lead time (90+ days), holds potential to further enhance these HAB products. In addition to describing these long-term flow forecasts and guidance products, this presentation will discuss how the OHRFC plays a role in helping with post-event analysis and the collaboration with NCCOS to improve the Lake Erie HAB forecasting process. [ABSTRACT FROM AUTHOR]