Quantitative estimates of phytoplankton abundance from eDNA

Harmful algal blooms (HABs) are accumulations of toxic phytoplankton that can have devastating impacts on human health and the economy. Data from environmental DNA (eDNA) and metabarcoding can be used to detect the presence of harmful species, but cannot detect when species are reaching bloom levels. I am developing a novel statistical modeling framework to get quantitative estimates of phytoplankton abundance from eDNA data. This will be used to improve methods to forecast future HABs.

It is not yet possible to identify Washington’s HAB species from satellite data; instead, we must characterize phytoplankton communities from water samples, the manual collection and analysis of which, using classical techniques, is labor intensive. Therefore, I am developing and implementing a statistical modeling framework to get quantitative estimates of phytoplankton abundance, including HAB species, from eDNA samples. This work is being conducted in collaboration with scientists from the National Oceanographic and Atmospheric Administration (NOAA), the University of Washington (UW), and Oregon State University (OSU). It is funded by the Washington Research Foundation.