Project Website (developed by grantee)

Synopsis: Tens of thousands of data points on environmental mercury (Hg) contamination have been collected throughout the Great Lakes region, yet these widely dispersed data have not been assembled to address ecosystem-scale questions in an integrated framework. This will be a collaborative project to develop an integrated multi-media Hg dataset for the Great Lakes region. The team assembled for this project will use the compiled data to address key scientific and policy-relevant questions regarding (i) spatial patterns and temporal trends in environmental Hg contamination, (ii) processes and factors influencing environmental Hg contamination and the accumulation of methylmercury (MeHg) in biota, and (iii) ecological and human health risks of the associated MeHg exposures. The project will build on the proven framework, experience, and tools developed in the Northern States Research Cooperative (NSRC) project in northeastern North America, expanding the existing NSRC database to the Great Lakes region. The identification of available Hg data, the integration of datasets, and the analysis and interpretation of data will be facilitated in two annual workshops and in teleconferences. This project will greatly enhance the information and benefits derived from the large prior investment of institutional resources in monitoring, surveillance, and investigations of Hg pollution in the Great Lakes region.

Chemicals Studied: Mercury

Geographic Areas: Great Lakes region

Project Duration: 2 years

Potential Results and Implications: Tangible outcomes of the project will include the database and a series of peer-reviewed publications detailing the application of the data to the questions listed above. Database and publication emphasis will be placed on our key questions that will include an analysis of (1) Hg exposure and effects in gamefish and wildlife, (2) spatial gradients of Hg including the identification of biological Hg hotspots, and (3) temporal trends of Hg. We have identified the loon Hg dataset as at least one dataset that will provide a standardized ability to identify spatial gradients and temporal trends. In addition, the proposed project will lay the groundwork for further efforts, including development and testing of models, tracking of trends, and linkages to the environmental policy community and decisionmakers.

Project Contact:
David C. Evers
BioDiversity Research Institute
19 Flaggy Meadow Road, Gorham, Maine 04038
Phone: (207) 839-7600
Email: david.evers@briloon.org