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Probabilistic injury assessment and quantification for natural resource damage assessment according to Bayesian networks: a case study of the polychlorinated biphenyl-contaminated Mississinewa River basin.

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Title: Probabilistic injury assessment and quantification for natural resource damage assessment according to Bayesian networks: a case study of the polychlorinated biphenyl-contaminated Mississinewa River basin.
Authors: Reed, April D1 (AUTHOR), Landis, Wayne G1 (AUTHOR) landis@wwu.edu
Source: Integrated Environmental Assessment & Management. Jan2026, Vol. 22 Issue 1, p214-224. 11p.
Database: Environment Complete
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Header DbId: eih
DbLabel: Environment Complete
An: 192182492
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Probabilistic injury assessment and quantification for natural resource damage assessment according to Bayesian networks: a case study of the polychlorinated biphenyl-contaminated Mississinewa River basin.
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  Data: <searchLink fieldCode="AR" term="%22Reed%2C+April+D%22">Reed, April D</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Landis%2C+Wayne+G%22">Landis, Wayne G</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> landis@wwu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Integrated+Environmental+Assessment+%26+Management%22">Integrated Environmental Assessment & Management</searchLink>. Jan2026, Vol. 22 Issue 1, p214-224. 11p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eih&AN=192182492
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      – Type: doi
        Value: 10.1093/inteam/vjaf103
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      – Code: eng
        Text: English
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        PageCount: 11
        StartPage: 214
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      – TitleFull: Probabilistic injury assessment and quantification for natural resource damage assessment according to Bayesian networks: a case study of the polychlorinated biphenyl-contaminated Mississinewa River basin.
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            – D: 01
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              Text: Jan2026
              Type: published
              Y: 2026
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