Phyconet: Biscayne Bay

Phyconet: Biscayne Bay (NOAA-NCCOS)

Biscayne Bay has diverse nutrient inputs and different circulation patterns along the length of the system making certain areas, particularly the northern bay, more prone to algal blooms and related events, e.g., fish kills and anoxia. Of note, Biscayne Bay has different nitrogen sources at the northern and southern regions of the lagoon, reflecting urban and agricultural influences, respectively. This project will monitor phytoplankton communities using traditional microscopy and taxonomy in combination with environmental DNA (eDNA) and next-generation sequencing to determine the composition of the algal community. Cutting-edge real-time flow cytometry technologies will allow the comparison of phytoplankton communities and relate these to water quality parameters. And metabolomics will analyze the biochemical profiles of phytoplankton and the detection of various algal toxins adsorbed from the water column.  

Over the 3-year project, we will examine the differences in phytoplankton communities along this North-South transect to identify bioindicators of ecosystem health. Further, conditions that promote the enhanced growth of target phytoplankton species and lead to the formation of harmful algal blooms will be defined and tested. And while not currently a problem, Biscayne Bay could be impacted by Florida Red Tides that get transported from the Florida west coast to the east coast via the Loop Current and Gulfstream. Early detection of such events will be accomplished by real-time imaging of Karenia brevis cells using field-deployed flow cytometry and metabolomic analyses to detect the presence of potent brevetoxins. Similarly, related toxin-producing taxa will be integrated for real-time detection to develop an early warning system for harmful algae.

Outcomes of the project will include a publicly-available dataset replete with climactic and water quality data, a curated set of micrographs representing phytoplankton from Biscayne Bay, molecular analysis of phytoplankton communities using metagenomics, and chemical characterization of the phytoplankton and water, including toxin detection. Collectively, these data can be utilized by researchers to examine water quality characteristics with taxon abundance and toxin presence, and factors that impact phytoplankton communities leading to blooms. Ultimately, this monitoring system will permit the early detection of potentially toxin-producing taxa such that mitigation (and prevention) strategies may be developed as the biotic and abiotic drivers of these phytoplankton communities are better understood.