R/WQ-1

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Predicting the Restoration Trajectory and Water Quality Value of Benthic Microalgae in Shallow Water Chesapeake Sediments

Principal Investigator:

Jeffrey C. Cornwell

Start/End Year:

2005 - 2008

Institution:

Horn Point Laboratory, University of Maryland Center for Environmental Science

Co-Principal Investigator:

Todd Kana, Horn Point Laboratory, University of Maryland Center for Environmental Science

Description:

Objective: The main objective of this project is to estimate the impact of the bay restoration on shallow water sediments. Specifically, we will determine the rates of primary production and enhanced nutrient retention by benthic microalgae in the northern Chesapeake Bay, provide appropriate light-production and other data relationships to the modeling community to enhance predictive modeling of shallow water processes, and improve the techniques for making such assessments. Methodology: We will use core incubations of benthic microalgae to determine production and respiration using both oxygen and high precision carbon dioxide measurements. Nutrient cycling will be assessed by fluxes of inorganic nutrients and measurements of denitrification. Fixation will be measured using the acetylene technique and oxygen microelectrodes will be used to examine small scale variability and vertical zonation of primary production. Rationale: Restoration of the bay to an earlier state implies a return to much more of a benthic dominated system. Nutrient reduction and/or increase oyster grazing should increase the areal extent of illuminated sediments, resulting in higher rates of nutrient sequestration and benthic primary production. Currently, the role of benthic algae has not be assessed in the Chesapeake Bay; such an effort will provide modelers with the data needed to evaluate this process in a whole system context. Our data analyses will provide a good assessment of these processes relative to others in the bay. This project addresses the "critical ecosystem function", and "sustainable ecosystem function" questions in the rfp.

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