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Extrapolation of available acute and chronic toxicity test data to population‐level effects for ecological risk management of chemicals
Author(s) -
Lin BinLe,
Meng Yaobin
Publication year - 2009
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1897/08-353.1
Subject(s) - extrapolation , population , chronic toxicity , acute toxicity , environmental toxicology , population model , toxicology , risk assessment , toxicity , persistence (discontinuity) , organism , oryzias , ecotoxicity , biology , environmental science , statistics , mathematics , chemistry , environmental health , medicine , fish <actinopterygii> , computer science , engineering , fishery , paleontology , organic chemistry , computer security , geotechnical engineering
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 ( C λ‐1 ), the proposed approach was then evaluated by a comparison of the C λ‐1 value derived by the extrapolation approach to those C λ‐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.