Published on the Web 2/24/2009.
Hazard/Risk Assessment
Extrapolation of available acute and chronic toxicity test data to population-level effects for ecological risk management of chemicals†
Article first published online: 9 DEC 2009
DOI: 10.1897/08-353.1
Copyright © 2009 SETAC
Additional Information
How to Cite
Lin, B.-L. and Meng, Y. (2009), Extrapolation of available acute and chronic toxicity test data to population-level effects for ecological risk management of chemicals. Environmental Toxicology and Chemistry, 28: 1557–1566. doi: 10.1897/08-353.1
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Publication History
- Issue published online: 9 DEC 2009
- Article first published online: 9 DEC 2009
- Manuscript Accepted: 7 JAN 2009
- Manuscript Received: 30 JUL 2008
Keywords:
- Population-level ecological risk assessment;
- Chemical substances;
- Acute/chronic toxicity test data;
- Predicted-no-effect concentration;
- Population growth rate (λ)
Abstract
An extrapolation approach is proposed using available acute (median lethal or effect concentration) and chronic (no-observed-effect concentration) toxicity test data at the organism level to derive a reference value contributing to the development of predicted-no-effect concentration on population persistence for population-level ecological risk assessment of chemicals. A matrix population model of wild medaka (Oryzias latipes) was employed as the tool to integrate the available organism-level toxicity test data on reproduction and survival into a finite population growth rate (λ) that provides information regarding the status of the population persistence. After demonstrating the approach using the acute and chronic toxicity test data of alcohol ethyxolate on fish to calculate the reference value defined as the concentration at λ = 1 (Cλ-1), the proposed approach was then evaluated by a comparison of the Cλ-1 value derived by the extrapolation approach to those Cλ-1 values calculated by two other approaches, in which different amounts of toxicity information contained in the same full life-cycle toxicity test data set on 4-nonylphenol were employed. It was concluded that this extrapolation approach is widely applicable and is promising for performing population-level ecological risk assessment on a more general basis that can support reasonable chemical management.

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