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Predicting chronic lethality of chemicals to fishes from acute toxicity test data: Theory of accelerated life testing
Author(s) -
Sun Kai,
Krause Gary F.,
Mayer Foster L.,
Ellersieck Mark R.,
Basu Asit P.
Publication year - 1995
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 - 10.1002/etc.5620141015
Subject(s) - lethality , toxicant , toxicity , chronic toxicity , fish <actinopterygii> , acute toxicity , chemical toxicity , toxicology , computer science , biology , chemistry , fishery , organic chemistry
A method for modeling aquatic toxicity data based on the theory of accelerated life testing is presented, and a procedure for maximum likelihood fitting the proposed model is developed. The procedure is computerized as software, which can predict chronic lethality of chemicals using data from acute toxicity tests. A database of various chemicals and fish species was analyzed. When the calculated values of prediction were compared to the maximum acceptable toxicant concentrations obtained from actual chronic toxicity experiments, the new technique provided accurate predictions. Problems in using the “maximum acceptable toxicant concentration” and applications of the proposed method are discussed.