Time-varying effects of aromatic oil constituents on the survival of aquatic species: Deviations between model estimates and observations

Lisette De Hoop, Karel P J Viaene, Aafke M. Schipper, Mark A J Huijbregts, Frederik De Laender, A. Jan Hendriks

Résultats de recherche: Contribution à un journal/une revueArticleRevue par des pairs

Résumé

There is a need to study the time course of toxic chemical effects on organisms because there might be a time lag between the onset of chemical exposure and the corresponding adverse effects. For aquatic organisms, crude oil and oil constituents originating from either natural seeps or human activities can be relevant case studies. In the present study the authors tested a generic toxicokinetic model to quantify the time-varying effects of various oil constituents on the survival of aquatic organisms. The model is based on key parameters applicable to an array of species and compounds with baseline toxicity reflected by a generic, internal toxicity threshold or critical body burden (CBB). They compared model estimates with experimental data on the effects of 8 aromatic oil constituents on the survival of aquatic species including crustaceans and fish. The average model uncertainty, expressed as the root mean square error, was 0.25 (minimum–maximum, 0.04–0.67) on a scale between 0 and 1. The estimated survival was generally lower than the measured survival right after the onset of oil constituent exposure. In contrast, the model underestimated the maximum mortality for crustaceans and fish observed in the laboratory. Thus, the model based on the CBB concept failed to adequately predict the lethal effects of the oil constituents on crustaceans and fish. Possible explanations for the deviations between model estimates and observations may include incorrect assumptions regarding a constant lethal body burden, the absence of biotransformation products, and the steady state of aromatic hydrocarbon concentrations in organisms. Clearly, a more complex model approach than the generic model used in the present study is needed to predict toxicity dynamics of narcotic chemicals. Environ Toxicol Chem 2017;36:128–136.

langue originaleAnglais
Pages (de - à)128-136
Nombre de pages9
journalEnvironmental Toxicology & Chemistry
Volume36
Numéro de publication1
Les DOIs
Etat de la publicationPublié - 19 juil. 2016

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