The Long Island Brown Tide (LIBT) threatens shellfish and sea grasses in mid-Atlantic estuaries. LIBT-specific gene expression assays are being developed and tested for enzymes and transporters that allow LIBT to use nutrient sources other algae cannot use. The new tools will be applied during natural blooms to determine which nutrient compounds are being used. The information will help predict future blooms and lead to specific nutrient reduction strategies to prevent or minimize blooms.
Why We Care
Aureococcus anophagefferens, LIBT, has plagued coastal ecosystems in the eastern U.S. from Rhode Island to Virginia. It first decimated Long Island scallop populations in 1985 and has since caused substantial loses to eel grass habitats and hard clam fisheries. In 1988 economic losses for the bay scallop fisheries were estimated to be $2 million annually (Kahn and Rockel, 1988 ).
Previous NCCOS-sponsored research has shown that high biomass LIBT blooms are linked, in part, to availability of dissolved organic nutrients rather than inorganic nutrients. Only recently have molecular tools been available to unravel the complexity of these nutrient sources and begin to make prediction and prevention possible.
What We Are Doing
LIBT is the first harmful algal bloom (HAB) for which the entire genome has been sequenced so that gene expression can be used to monitor species-specific nutrient utilization in the field. The investigators are validating and applying quantitative gene expression assays to examine how a wide array of specific nutrients influences bloom initiation, maintenance, and decline. They are linking nutrient dynamics to the genes involved in nutrient transport and metabolism using LIBT cultures, field bioassays and natural blooms.
This project is part of the NCCOS Ecology and Oceanography of Harmful Algal Blooms (ECOHAB) program, and is led by the Woods Hole Oceanographic Institution in partnership with the State University of New York at Stony Brook.
Benefits of Our Work
- We will determine whether nutrients influence blooms of LIBT and which nutrients are to blame.
- When this information is incorporated into mathematical models of LIBT growth it will be possible to test scenarios of nutrient reduction to determine new strategies to reduce or prevent blooms.
- Decision makers will be informed whether such measures as reducing loading of specific nutrients will decrease or prevent LIBT blooms.
- The use of gene expression to assess nutrient utilization in LIBT is an entirely new approach that may be applicable to determining the role of nutrients in other regions with other HAB species.