II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria
The aim of this paper is to bridge gaps between biomarker and whole organism responses related to oil based offshore discharges. These biomarker bridges will facilitate acceptance criteria for biomarker data linked to environmental risk assessment and translate biomarker results to higher order effe...
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| Veröffentlicht in: | Marine environmental research 2017-06, Vol.127, p.11-23 |
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| creator | Sanni, Steinar Lyng, Emily Pampanin, Daniela M. Smit, Mathijs G.D. |
| description | The aim of this paper is to bridge gaps between biomarker and whole organism responses related to oil based offshore discharges. These biomarker bridges will facilitate acceptance criteria for biomarker data linked to environmental risk assessment and translate biomarker results to higher order effects.
Biomarker based species sensitivity distributions (SSDbiomarkers) have been constructed for relevant groups of biomarkers based on laboratory data from oil exposures. SSD curves express the fraction of species responding to different types of biomarkers. They have been connected to SSDs for whole organism responses (WORs) constructed in order to relate the SSDbiomarkers to animal fitness parameters that are commonly used in environmental risk assessment.
The resulting SSD curves show that biomarkers and WORs can be linked through their potentially affected fraction of species (PAF) distributions, enhancing the capability to monitor field parameters with better correlation to impact and risk assessment criteria and providing improved chemical/biological integration.
•Bridging gaps between biomarker and whole organism responses for oil based discharges.•Biomarker bridges enable acceptance criteria for biomarkers in environmental risk assessment.•Translation of biomarker results to higher order effects.•Biomarker based SSDs are constructed based on laboratory data from oil exposures.•Biomarkers and whole organism responses are linked via potentially affected fraction of species. |
| doi_str_mv | 10.1016/j.marenvres.2016.12.003 |
| format | Article |
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Biomarker based species sensitivity distributions (SSDbiomarkers) have been constructed for relevant groups of biomarkers based on laboratory data from oil exposures. SSD curves express the fraction of species responding to different types of biomarkers. They have been connected to SSDs for whole organism responses (WORs) constructed in order to relate the SSDbiomarkers to animal fitness parameters that are commonly used in environmental risk assessment.
The resulting SSD curves show that biomarkers and WORs can be linked through their potentially affected fraction of species (PAF) distributions, enhancing the capability to monitor field parameters with better correlation to impact and risk assessment criteria and providing improved chemical/biological integration.
•Bridging gaps between biomarker and whole organism responses for oil based discharges.•Biomarker bridges enable acceptance criteria for biomarkers in environmental risk assessment.•Translation of biomarker results to higher order effects.•Biomarker based SSDs are constructed based on laboratory data from oil exposures.•Biomarkers and whole organism responses are linked via potentially affected fraction of species.</description><identifier>ISSN: 0141-1136</identifier><identifier>EISSN: 1879-0291</identifier><identifier>DOI: 10.1016/j.marenvres.2016.12.003</identifier><identifier>PMID: 28041674</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Acceptance criteria ; Aquatic Organisms - physiology ; Biomarker ; Biomarkers ; Biomonitoring ; Bridges ; Ecological risk assessment ; Effects ; Environmental assessment ; Environmental impact ; Environmental Monitoring - methods ; Environmental risk ; Fitness ; Integration ; Offshore ; Offshore drilling rigs ; Oil ; Organisms ; Parameters ; Petroleum - analysis ; Petroleum hydrocarbons ; Petroleum Pollution - statistics & numerical data ; Risk Assessment ; Sensitivity ; Species ; Species sensitivity distribution ; Species Specificity ; Studies ; Whole organism responses</subject><ispartof>Marine environmental research, 2017-06, Vol.127, p.11-23</ispartof><rights>2016 Elsevier Ltd</rights><rights>Copyright © 2016 Elsevier Ltd. All rights reserved.</rights><rights>Copyright Elsevier BV Jun 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c399t-c856805444998a3955f69d83745816a27341fbbeb9350b7e394ba33f3e396cec3</citedby><cites>FETCH-LOGICAL-c399t-c856805444998a3955f69d83745816a27341fbbeb9350b7e394ba33f3e396cec3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.marenvres.2016.12.003$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28041674$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Sanni, Steinar</creatorcontrib><creatorcontrib>Lyng, Emily</creatorcontrib><creatorcontrib>Pampanin, Daniela M.</creatorcontrib><creatorcontrib>Smit, Mathijs G.D.</creatorcontrib><title>II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria</title><title>Marine environmental research</title><addtitle>Mar Environ Res</addtitle><description>The aim of this paper is to bridge gaps between biomarker and whole organism responses related to oil based offshore discharges. These biomarker bridges will facilitate acceptance criteria for biomarker data linked to environmental risk assessment and translate biomarker results to higher order effects.
Biomarker based species sensitivity distributions (SSDbiomarkers) have been constructed for relevant groups of biomarkers based on laboratory data from oil exposures. SSD curves express the fraction of species responding to different types of biomarkers. They have been connected to SSDs for whole organism responses (WORs) constructed in order to relate the SSDbiomarkers to animal fitness parameters that are commonly used in environmental risk assessment.
The resulting SSD curves show that biomarkers and WORs can be linked through their potentially affected fraction of species (PAF) distributions, enhancing the capability to monitor field parameters with better correlation to impact and risk assessment criteria and providing improved chemical/biological integration.
•Bridging gaps between biomarker and whole organism responses for oil based discharges.•Biomarker bridges enable acceptance criteria for biomarkers in environmental risk assessment.•Translation of biomarker results to higher order effects.•Biomarker based SSDs are constructed based on laboratory data from oil exposures.•Biomarkers and whole organism responses are linked via potentially affected fraction of species.</description><subject>Acceptance criteria</subject><subject>Aquatic Organisms - physiology</subject><subject>Biomarker</subject><subject>Biomarkers</subject><subject>Biomonitoring</subject><subject>Bridges</subject><subject>Ecological risk assessment</subject><subject>Effects</subject><subject>Environmental assessment</subject><subject>Environmental impact</subject><subject>Environmental Monitoring - methods</subject><subject>Environmental risk</subject><subject>Fitness</subject><subject>Integration</subject><subject>Offshore</subject><subject>Offshore drilling rigs</subject><subject>Oil</subject><subject>Organisms</subject><subject>Parameters</subject><subject>Petroleum - analysis</subject><subject>Petroleum hydrocarbons</subject><subject>Petroleum Pollution - statistics & numerical data</subject><subject>Risk Assessment</subject><subject>Sensitivity</subject><subject>Species</subject><subject>Species sensitivity distribution</subject><subject>Species Specificity</subject><subject>Studies</subject><subject>Whole organism responses</subject><issn>0141-1136</issn><issn>1879-0291</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkc9u1DAQhy1ERZfCK4AlLlyS2rGdxMeq4s9KlTjQni3HmRRvN3bwOFv1EXhrXLb0wIWTR9b3mxnNR8h7zmrOeHu-q2ebIBwSYN2Uj5o3NWPiBdnwvtMVazR_STaMS15xLtpT8hpxxxhTHVevyGnTM8nbTm7Ir-22pt8XcB6QIgT02R98fqCjx5z8sGYfA9LBIow0Bjr4WCbfQUJqw0jvf8Q90JhubfA407LOUvDSaoqJ-pDhNtlckn5erMt_IsnjHbVYIJwhZOqSz5C8fUNOJrtHePv0npGbz5-uL79WV9--bC8vriontM6V61XbMyWl1Lq3Qis1tXrsRSdVz1vbdELyaRhg0EKxoQOh5WCFmESpWgdOnJGPx75Lij9XwGxmjw72exsgrmh4r2TPSqwt6Id_0F1cUyjbGa4lU4xxrQvVHSmXImKCySzJlyM9GM7Moy2zM8-2zKMtwxtTbJXku6f-6zDD-Jz7q6cAF0cAykEOHpLBIio4GH0Cl80Y_X-H_AZhxaxl</recordid><startdate>20170601</startdate><enddate>20170601</enddate><creator>Sanni, Steinar</creator><creator>Lyng, Emily</creator><creator>Pampanin, Daniela M.</creator><creator>Smit, Mathijs G.D.</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><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>7SN</scope><scope>7ST</scope><scope>7T5</scope><scope>7TN</scope><scope>7U7</scope><scope>C1K</scope><scope>F1W</scope><scope>H94</scope><scope>M7N</scope><scope>SOI</scope><scope>7X8</scope></search><sort><creationdate>20170601</creationdate><title>II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria</title><author>Sanni, Steinar ; Lyng, Emily ; Pampanin, Daniela M. ; Smit, Mathijs G.D.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c399t-c856805444998a3955f69d83745816a27341fbbeb9350b7e394ba33f3e396cec3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Acceptance criteria</topic><topic>Aquatic Organisms - physiology</topic><topic>Biomarker</topic><topic>Biomarkers</topic><topic>Biomonitoring</topic><topic>Bridges</topic><topic>Ecological risk assessment</topic><topic>Effects</topic><topic>Environmental assessment</topic><topic>Environmental impact</topic><topic>Environmental Monitoring - methods</topic><topic>Environmental risk</topic><topic>Fitness</topic><topic>Integration</topic><topic>Offshore</topic><topic>Offshore drilling rigs</topic><topic>Oil</topic><topic>Organisms</topic><topic>Parameters</topic><topic>Petroleum - analysis</topic><topic>Petroleum hydrocarbons</topic><topic>Petroleum Pollution - statistics & numerical data</topic><topic>Risk Assessment</topic><topic>Sensitivity</topic><topic>Species</topic><topic>Species sensitivity distribution</topic><topic>Species Specificity</topic><topic>Studies</topic><topic>Whole organism responses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sanni, Steinar</creatorcontrib><creatorcontrib>Lyng, Emily</creatorcontrib><creatorcontrib>Pampanin, Daniela M.</creatorcontrib><creatorcontrib>Smit, Mathijs G.D.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Immunology Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Environment Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Marine environmental research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sanni, Steinar</au><au>Lyng, Emily</au><au>Pampanin, Daniela M.</au><au>Smit, Mathijs G.D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria</atitle><jtitle>Marine environmental research</jtitle><addtitle>Mar Environ Res</addtitle><date>2017-06-01</date><risdate>2017</risdate><volume>127</volume><spage>11</spage><epage>23</epage><pages>11-23</pages><issn>0141-1136</issn><eissn>1879-0291</eissn><abstract>The aim of this paper is to bridge gaps between biomarker and whole organism responses related to oil based offshore discharges. These biomarker bridges will facilitate acceptance criteria for biomarker data linked to environmental risk assessment and translate biomarker results to higher order effects.
Biomarker based species sensitivity distributions (SSDbiomarkers) have been constructed for relevant groups of biomarkers based on laboratory data from oil exposures. SSD curves express the fraction of species responding to different types of biomarkers. They have been connected to SSDs for whole organism responses (WORs) constructed in order to relate the SSDbiomarkers to animal fitness parameters that are commonly used in environmental risk assessment.
The resulting SSD curves show that biomarkers and WORs can be linked through their potentially affected fraction of species (PAF) distributions, enhancing the capability to monitor field parameters with better correlation to impact and risk assessment criteria and providing improved chemical/biological integration.
•Bridging gaps between biomarker and whole organism responses for oil based discharges.•Biomarker bridges enable acceptance criteria for biomarkers in environmental risk assessment.•Translation of biomarker results to higher order effects.•Biomarker based SSDs are constructed based on laboratory data from oil exposures.•Biomarkers and whole organism responses are linked via potentially affected fraction of species.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>28041674</pmid><doi>10.1016/j.marenvres.2016.12.003</doi><tpages>13</tpages></addata></record> |
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| ispartof | Marine environmental research, 2017-06, Vol.127, p.11-23 |
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| source | MEDLINE; Access via ScienceDirect (Elsevier) |
| subjects | Acceptance criteria Aquatic Organisms - physiology Biomarker Biomarkers Biomonitoring Bridges Ecological risk assessment Effects Environmental assessment Environmental impact Environmental Monitoring - methods Environmental risk Fitness Integration Offshore Offshore drilling rigs Oil Organisms Parameters Petroleum - analysis Petroleum hydrocarbons Petroleum Pollution - statistics & numerical data Risk Assessment Sensitivity Species Species sensitivity distribution Species Specificity Studies Whole organism responses |
| title | II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria |
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