MERGANSER: an empirical model to predict fish and loon mercury in New England lakes

Environmental Science & Technology
By: , and 



MERGANSER (MERcury Geo-spatial AssessmeNtS for the New England Region) is an empirical least-squares multiple regression model using mercury (Hg) deposition and readily obtainable lake and watershed features to predict fish (fillet) and common loon (blood) Hg in New England lakes. We modeled lakes larger than 8 ha (4404 lakes), using 3470 fish (12 species) and 253 loon Hg concentrations from 420 lakes. MERGANSER predictor variables included Hg deposition, watershed alkalinity, percent wetlands, percent forest canopy, percent agriculture, drainage area, population density, mean annual air temperature, and watershed slope. The model returns fish or loon Hg for user-entered species and fish length. MERGANSER explained 63% of the variance in fish and loon Hg concentrations. MERGANSER predicted that 32-cm smallmouth bass had a median Hg concentration of 0.53 μg g-1 (root-mean-square error 0.27 μg g-1) and exceeded EPA's recommended fish Hg criterion of 0.3 μg g-1 in 90% of New England lakes. Common loon had a median Hg concentration of 1.07 μg g-1 and was in the moderate or higher risk category of >1 μg g-1 Hg in 58% of New England lakes. MERGANSER can be applied to target fish advisories to specific unmonitored lakes, and for scenario evaluation, such as the effect of changes in Hg deposition, land use, or warmer climate on fish and loon mercury.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title MERGANSER: an empirical model to predict fish and loon mercury in New England lakes
Series title Environmental Science & Technology
DOI 10.1021/es300581p
Volume 46
Issue 8
Year Published 2012
Language English
Publisher ACS Publications
Publisher location Washington, D.C.
Contributing office(s) New Hampshire-Vermont Water Science Center
Description 8 p.
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title Environmental Science and Technology
First page 4641
Last page 4648
Country United States
Other Geospatial New England
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