II. Species sensitivity distributions based on biomarkers and whole organism responses for integrated impact and risk assessment criteria

• Published in: Marine environmental research Vol. 127; pp. 11 - 23
• Main Authors: Sanni, Steinar, Lyng, Emily, Pampanin, Daniela M., Smit, Mathijs G.D.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01-06-2017; Elsevier BV
• 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; Petroleum hydrocarbons; Species sensitivity distribution; Biomarker; Biomonitoring; Risk assessment; Whole organism responses; Environmental impact
• ISSN: 0141-1136; 1879-0291
• DOI: 10.1016/j.marenvres.2016.12.003

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.