Abstract Title
Plenary: Exploring toxic cyanobacteria blooms using emerging technologies: From space to the benthos
Start Date
23-5-2022 1:45 PM
End Date
23-5-2022 2:30 PM
Abstract
Traditionally coastal systems have been monitored using ship-based sampling methods, which provide a discrete spatial and temporal snapshot of current conditions. These discrete sampling strategies often miss key environmental shifts that lead to high variability in bloom biomass and toxin concentrations (e.g. 2014 Toledo Water Crisis). Understanding and interpreting the complex interactions between biological, chemical, and physical variables in coastal systems require versatile monitoring approaches. To enhance our spatio-temporal resolution, NOAA is developing a monitoring network in Lake Erie to study and track cyanobacteria harmful algal blooms using traditional methods and emerging technologies. Weekly monitoring at fixed sampling sites provides baseline environmental conditions. The extent of bloom biomass and phytoplankton community composition is determined through daily satellite and weekly hyperspectral imaging. Paired with physical observations and modeling, bloom biomass and toxin concentration trajectories are forecasted up to 5 days in the future. Within the water column, real-time nutrient buoys and second generation (2G) Environmental Sample Processors (ESP) provided near real-time relevant water quality data and particulate microcystin concentrations, respectively. With colleagues at the Monterey Bay Aquarium Research Institute (MBARI) we have tested a 3rd Generation (3G) ESP, an autonomous molecular diagnostic device integrated with an uncrewed underwater vehicle, capable of collecting eDNA and conducting near real-time toxin (e.g., microcystin) analysis using an embedded Surface Plasmon Resonance (SPR) module. Finally, field-based experiments evaluate the role of resuspension events, cell buoyancy, resting cells, and community dynamics on bloom development. This collection of actionable temporal and spatial environmental data is provided to the scientific community, managers, and public stakeholders to support decision making and enhance our understanding of bloom succession.
Plenary: Exploring toxic cyanobacteria blooms using emerging technologies: From space to the benthos
Traditionally coastal systems have been monitored using ship-based sampling methods, which provide a discrete spatial and temporal snapshot of current conditions. These discrete sampling strategies often miss key environmental shifts that lead to high variability in bloom biomass and toxin concentrations (e.g. 2014 Toledo Water Crisis). Understanding and interpreting the complex interactions between biological, chemical, and physical variables in coastal systems require versatile monitoring approaches. To enhance our spatio-temporal resolution, NOAA is developing a monitoring network in Lake Erie to study and track cyanobacteria harmful algal blooms using traditional methods and emerging technologies. Weekly monitoring at fixed sampling sites provides baseline environmental conditions. The extent of bloom biomass and phytoplankton community composition is determined through daily satellite and weekly hyperspectral imaging. Paired with physical observations and modeling, bloom biomass and toxin concentration trajectories are forecasted up to 5 days in the future. Within the water column, real-time nutrient buoys and second generation (2G) Environmental Sample Processors (ESP) provided near real-time relevant water quality data and particulate microcystin concentrations, respectively. With colleagues at the Monterey Bay Aquarium Research Institute (MBARI) we have tested a 3rd Generation (3G) ESP, an autonomous molecular diagnostic device integrated with an uncrewed underwater vehicle, capable of collecting eDNA and conducting near real-time toxin (e.g., microcystin) analysis using an embedded Surface Plasmon Resonance (SPR) module. Finally, field-based experiments evaluate the role of resuspension events, cell buoyancy, resting cells, and community dynamics on bloom development. This collection of actionable temporal and spatial environmental data is provided to the scientific community, managers, and public stakeholders to support decision making and enhance our understanding of bloom succession.