Science Inventory

A MOLECULAR APPROACH TO UNDERSTAND HARMFUL ALGAL BLOOMS

Impact/Purpose:

Harmful Algal Blooms (HABs), and their relationship to societal activities (i.e. eutrophication) are a controversial and hot topic in oceanography. HABs can affect the ecosystem in a variety of ways such as through the release of toxins (some species), the creation of hypoxic or anoxic zones, or by shading benthic sea grass communities. HABs present a global problem because of their widespread effects on public health, the coastal environment, and the economy. Understanding HAB nutrient physiology is necessary for understanding bloom formation and bloom dynamics. Applying unique molecular tools to this system has the potential to greatly increase our knowledge of nutrient physiology in HABs. I am interested in using a quantitative molecular approach on a model HAB species to help answer a number of questions such as: Which nutrient species are important in stimulating and terminating blooms? To what degree is the physiology of the cells linked to nutrient concentrations in the water? How does the nutritional physiology of a single HAB species in a mixed community change over an entire bloom event? What are the anthropogenic links (if any) to bloom formation?

Description:

With the upcoming release of a fully sequenced genome, we have an unprecedented opportunity to discover how a HAB organism responds to nutrient loading and the cellular mechanisms underlying those responses. This project will provide key regulation data to help identify transcripts involved in nutrient metabolism and stress responses. The discovery of nutrient regulated transcripts, and their putative function, will provide novel targets for tracking the nutritional physiology of field populations. Using a quantitative molecular approach will allow us to track the in situ nutritional status of an individual HAB species in a mixed community over entire seasons. This will provide enormous insight in determining the links among eutrophication, HABs, and societal activities as well as increase our ability to better predict when blooms will occur.

Record Details:

Record Type:PROJECT( ABSTRACT )
Start Date:09/01/2007
Completion Date:08/01/2010
Record ID: 207924