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 |
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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 >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. Psychology ; Lakes ; Mercury - analysis ; Models, Theoretical ; New England ; Reproducibility of Results ; Techniques ; Water Pollutants, Chemical - analysis</subject><ispartof>Environmental science & technology, 2012-04, Vol.46 (8), p.4641-4648</ispartof><rights>Copyright © 2012 American Chemical Society</rights><rights>2014 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a345t-de068ba2a68cf6f993cef78717c65bc0337dff775928d7b3d193c8fd99eb6e683</citedby><cites>FETCH-LOGICAL-a345t-de068ba2a68cf6f993cef78717c65bc0337dff775928d7b3d193c8fd99eb6e683</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://pubs.acs.org/doi/pdf/10.1021/es300581p$$EPDF$$P50$$Gacs$$H</linktopdf><linktohtml>$$Uhttps://pubs.acs.org/doi/10.1021/es300581p$$EHTML$$P50$$Gacs$$H</linktohtml><link.rule.ids>315,781,785,2766,27081,27929,27930,56743,56793</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=25812120$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22372609$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><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><title>MERGANSER: An Empirical Model To Predict Fish and Loon Mercury in New England Lakes</title><title>Environmental science & technology</title><addtitle>Environ. Sci. Technol</addtitle><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.</description><subject>Animal, plant and microbial ecology</subject><subject>Animals</subject><subject>Applied ecology</subject><subject>Biological and medical sciences</subject><subject>Birds</subject><subject>Ecotoxicology, biological effects of pollution</subject><subject>Environmental Monitoring</subject><subject>Fishes</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Lakes</subject><subject>Mercury - analysis</subject><subject>Models, Theoretical</subject><subject>New England</subject><subject>Reproducibility of Results</subject><subject>Techniques</subject><subject>Water Pollutants, Chemical - analysis</subject><issn>0013-936X</issn><issn>1520-5851</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpt0MtOAjEUBuDGaATRhS9gujHRxWgvTqfjjpABTQANYOJu0ulFB-dmy8Tw9lZB2Ljq4nz5z-kPwDlGNxgRfKsdRSjkuDkAXRwSFIQ8xIegixCmQUzZawecOLdECBGK-DHoEEIjwlDcBfNJMhv1p_Nkdg_7FUzKJre5FAWc1EoXcFHDZ6tVLldwmLt3KCoFx3VdwYm2srVrmFdwqr9gUr0VvzPxod0pODKicPps-_bAyzBZDB6C8dPocdAfB4LehatAacR4JohgXBpm4phKbSIe4UiyMJOI0kgZE0VhTLiKMqqwF9yoONYZ04zTHrja5Da2_my1W6Vl7qQu_CW6bl2K_X9DjDmjnl5vqLS1c1abtLF5Kezao_Snw3TXobcX29g2K7Xayb_SPLjcAuF8VcaKSuZu73wKwQTtnZAuXdatrXwb_yz8BvA2gnY</recordid><startdate>20120417</startdate><enddate>20120417</enddate><creator>Shanley, James B</creator><creator>Moore, Richard</creator><creator>Smith, Richard A</creator><creator>Miller, Eric K</creator><creator>Simcox, Alison</creator><creator>Kamman, Neil</creator><creator>Nacci, Diane</creator><creator>Robinson, Keith</creator><creator>Johnston, John M</creator><creator>Hughes, Melissa M</creator><creator>Johnston, Craig</creator><creator>Evers, David</creator><creator>Williams, Kate</creator><creator>Graham, John</creator><creator>King, Susannah</creator><general>American Chemical Society</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20120417</creationdate><title>MERGANSER: An Empirical Model To Predict Fish and Loon Mercury in New England Lakes</title><author>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</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a345t-de068ba2a68cf6f993cef78717c65bc0337dff775928d7b3d193c8fd99eb6e683</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Animal, plant and microbial ecology</topic><topic>Animals</topic><topic>Applied ecology</topic><topic>Biological and medical sciences</topic><topic>Birds</topic><topic>Ecotoxicology, biological effects of pollution</topic><topic>Environmental Monitoring</topic><topic>Fishes</topic><topic>Fundamental and applied biological sciences. 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 & 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 & 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 >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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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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