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Predicting chronic lethality of chemicals to fishes from acute toxicity test data: Multifactor probit analysis
Author(s) -
Lee Gunhee,
Ellersieck Mark R.,
Mayer Foster L.,
Krause Gary F.
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.5620140221
Subject(s) - lethality , toxicant , acute toxicity , chronic toxicity , probit model , toxicity , toxicology , biology , statistics , medicine , mathematics
Abstract New methods for predicting chronic toxicity (lethality) from acute lethality data with fishes was developed and assessed. Typically, acute toxicity tests with aquatic organisms provide lethality estimates for a series of toxicant concentrations at 24, 48, 72, and 96 h of exposure. Statistical models (multiple regression) were developed that utilize acute toxicity data to establish the relation of lethality to toxicant concentration and exposure time for predicting chronic lethality. The models provide estimates of toxicant concentrations that result in a low probability of death as a function of extended exposure times. Results from 28 data sets having lethality data for both acute and chronic exposures were used to evaluate the method. It is posited that the proposed methods are highly accurate when acute lethality data meeting stated quality requirements are available.