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NUTRIENT RESPONSE IN GREAT LAKES WETLANDS
Citation:
Thompson, J A., J A. Morrice, AND M E. Sierszen. NUTRIENT RESPONSE IN GREAT LAKES WETLANDS. Presented at U.S. EPA Region 5 Nutrient Technical Advisory Group Meeting, Chicago, IL, November 18-19, 2003.
Description:
The U.S. EPA National Health and Environmental Effects Laboratory's Aquatic Stressor Framework and associated Nutrient Implementation Plan define scientific and regulatory needs, and lay-out research goals too for a cross divisional program to investigate stressor-response relationships between nutrient enrichment and ecological responses. Our initial research addresses three primary response endpoints, low D.O., loss of submerged vegetation, and changes in food webs, in U.S. coastal waters. The research also recognizes the need to classify systems in order to better predict their sensitivity to nutrient enrichment. Our division's research is specifically focusing on developing sutrient-response relationships in Great Lakes coastal wetlands. We used Principal Component scores derived from agriculture and chemical variables from land cover data to a priori define our nutrient gradient across all wetlands. Wetlands were then selected from this gradient within two different ecoprovinces, the Laurentian Mixed Forest (northern) and the Eastern Broadleaf Forest (southern) and within two hydrogeomorphic wetland types, riverine and protected, which representing short and long residence time. Various measures of nutrient condition and biological responses are being measured across all 5 Great Lakes. Preliminary analyses indicates that the land cover variables were a reasonable predictor of total nitrogen, total phosphorus and phytoplankton chlorophyll ll. Total and dissolved phosphorus are higher in the riverine than the protected wetlands and were higher in the southern than the northern wetlands. The southern wetlands were also higher in total nitrogen and phytoplankton chlorophyll ll. We also demonstrated that different nutrient regimes can alter the taxonomic composition of algal communities which can have implication for food web impacts. Future work will include further sampling, refinement of landscape data, completion of data analysis, and food web modeling. This abstract does not necessarily reflect EPA policy.