MERGANSER: An Empirical Model To Predict Fish and Loon Mercury in New England Lakes

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 l...

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Veröffentlicht in:Environmental science & technology 2012-04, Vol.46 (8), p.4641-4648
Hauptverfasser: Shanley, James B, Moore, Richard, Smith, Richard A, Miller, Eric K, Simcox, Alison, Kamman, Neil, Nacci, Diane, Robinson, Keith, Johnston, John M, Hughes, Melissa M, Johnston, Craig, Evers, David, Williams, Kate, Graham, John, King, Susannah
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container_end_page 4648
container_issue 8
container_start_page 4641
container_title Environmental science & technology
container_volume 46
creator Shanley, James B
Moore, Richard
Smith, Richard A
Miller, Eric K
Simcox, Alison
Kamman, Neil
Nacci, Diane
Robinson, Keith
Johnston, John M
Hughes, Melissa M
Johnston, Craig
Evers, David
Williams, Kate
Graham, John
King, Susannah
description 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.
doi_str_mv 10.1021/es300581p
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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 &gt;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.</description><identifier>ISSN: 0013-936X</identifier><identifier>EISSN: 1520-5851</identifier><identifier>DOI: 10.1021/es300581p</identifier><identifier>PMID: 22372609</identifier><identifier>CODEN: ESTHAG</identifier><language>eng</language><publisher>Washington, DC: American Chemical Society</publisher><subject>Animal, plant and microbial ecology ; Animals ; Applied ecology ; Biological and medical sciences ; Birds ; Ecotoxicology, biological effects of pollution ; Environmental Monitoring ; Fishes ; Fundamental and applied biological sciences. 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Psychology</topic><topic>Lakes</topic><topic>Mercury - analysis</topic><topic>Models, Theoretical</topic><topic>New England</topic><topic>Reproducibility of Results</topic><topic>Techniques</topic><topic>Water Pollutants, Chemical - analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shanley, James B</creatorcontrib><creatorcontrib>Moore, Richard</creatorcontrib><creatorcontrib>Smith, Richard A</creatorcontrib><creatorcontrib>Miller, Eric K</creatorcontrib><creatorcontrib>Simcox, Alison</creatorcontrib><creatorcontrib>Kamman, Neil</creatorcontrib><creatorcontrib>Nacci, Diane</creatorcontrib><creatorcontrib>Robinson, Keith</creatorcontrib><creatorcontrib>Johnston, John M</creatorcontrib><creatorcontrib>Hughes, Melissa M</creatorcontrib><creatorcontrib>Johnston, Craig</creatorcontrib><creatorcontrib>Evers, David</creatorcontrib><creatorcontrib>Williams, Kate</creatorcontrib><creatorcontrib>Graham, John</creatorcontrib><creatorcontrib>King, Susannah</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Environmental science &amp; technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shanley, James B</au><au>Moore, Richard</au><au>Smith, Richard A</au><au>Miller, Eric K</au><au>Simcox, Alison</au><au>Kamman, Neil</au><au>Nacci, Diane</au><au>Robinson, Keith</au><au>Johnston, John M</au><au>Hughes, Melissa M</au><au>Johnston, Craig</au><au>Evers, David</au><au>Williams, Kate</au><au>Graham, John</au><au>King, Susannah</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>MERGANSER: An Empirical Model To Predict Fish and Loon Mercury in New England Lakes</atitle><jtitle>Environmental science &amp; technology</jtitle><addtitle>Environ. Sci. Technol</addtitle><date>2012-04-17</date><risdate>2012</risdate><volume>46</volume><issue>8</issue><spage>4641</spage><epage>4648</epage><pages>4641-4648</pages><issn>0013-936X</issn><eissn>1520-5851</eissn><coden>ESTHAG</coden><abstract>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 &gt;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.</abstract><cop>Washington, DC</cop><pub>American Chemical Society</pub><pmid>22372609</pmid><doi>10.1021/es300581p</doi><tpages>8</tpages></addata></record>
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ispartof Environmental science & technology, 2012-04, Vol.46 (8), p.4641-4648
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subjects Animal, plant and microbial ecology
Animals
Applied ecology
Biological and medical sciences
Birds
Ecotoxicology, biological effects of pollution
Environmental Monitoring
Fishes
Fundamental and applied biological sciences. Psychology
Lakes
Mercury - analysis
Models, Theoretical
New England
Reproducibility of Results
Techniques
Water Pollutants, Chemical - analysis
title MERGANSER: An Empirical Model To Predict Fish and Loon Mercury in New England Lakes
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