Northeastern Section (45th Annual) and Southeastern Section (59th Annual) Joint Meeting (13-16 March 2010)

Paper No. 8
Presentation Time: 4:15 PM


SIMCOX, Alison C.1, EVERS, David C.2, FAHEY, Kathleen3, GRAHAM, John3, JOHNSTON, Craig4, JOHNSTON, John M.5, KAMMAN, Neil C.6, KING, Susannah7, MILLER, Eric K.8, MOORE, Richard B.9, NACCI, Diane10, ROBINSON, Keith9, SMITH, Richard A.11 and SHANLEY, James B.12, (1)US EPA, McCormack Building, 5 Post Office Square, Boston, MA 02109, (2)Biodiversity Research Institute, 19 Flaggy Meadow Road, Gorham, ME 04038, (3)89 South Street, Suite 602, Boston, MA 02111, (4)U.S. Geological Survey, New England Water Science Center, 331 Commerce Way, Suite #2, Pembroke, NH 03275, (5)US EPA, 960 College Station Road, Athens, GA 30605, (6)VT Department of Environmental Conservation, Waterbury, VT 05671, (7)NEIWPCC, 116 John Street, Lowell, MA 01852, (8)Ecosystems Research Group Ltd, PO Box 1227, Norwich, VT 05055, (9)USGS, 331 Commerce Way, Pembroke, NH 03275, (10)US EPA, 27 Tarzwell Drive, Narragansett, RI 02882, (11)USGS, 12201 Sunrise Valley Drive, Reston, VA 20192, (12)U.S. Geological Survey, P.O. Box 628, Montpelier, VT 05601,

EPA is leading a team of mercury researchers in the northeast US in developing a GIS-based mercury model called MERGANSER (Mercury Geospatial Assessments for the New England Region). This model will identify aquatic ecosystems where fish and piscivores and, ultimately, humans (via fish comsumption) are at risk for contamination by mercury.

Over a decade, the team, including EPA, NESCAUM, USGS, BioDiversity Research Institute, Ecosystems Research Group and others, has gathered data on mercury, including sources, transport and deposition, and environmental responses. EPA and USGS scientists realized that this data could be integrated into an empirical, regression-based model for assessing risk of mercury contamination in aquatic ecosystems throughout New England.

In 2006, EPA Region 1 received a grant to complete MERGANSER through EPA's Advanced Monitoring Initiative. The model, to be completed in 2010, will link a large body of data on mercury levels in fish and piscivores (especially loons) throughout New England to mercury-deposition models and data on mercury sources and ecosystem features. The model will identify variables (e.g., wetlands in contact with lakes, forest type, pH) correlated with mercury levels in biota and use this information to predict contaminant levels in fish and piscivores in unsampled lakes and lake breeding areas. An empirical linkage will be developed between mercury levels in biota and species population effects, such as reproductive impairment.

Powerful features of MERGANSER will be its ability to predict changes in mercury levels in fish and piscivores resulting from implementing various policy options, and to identify optimal locations for monitoring. Additionally, the model will be useful for developing mercury models elsewhere where this high level of mercury data is not available.