Interaction patterns and toxicities of binary and ternary pesticide mixtures to Daphnia magna estimated by an accelerated failure time model

Xuchun Qiu, Wataru Tanoue, Atsushi Kawaguchi, Takashi Yanagawa, Masanori Seki, Yohei Shimasaki, Tsuneo Honjo, Yuji Oshima

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Organisms in natural environments are often exposed to a broad variety of chemicals, and the multi-chemical mixtures exposure may produce significant toxic effects, even though the individual chemicals are present at concentrations below their no-observed-effect concentrations. This study represents the first attempt that uses the accelerated failure time (AFT) model to quantify the interaction and toxicity of multi-chemical mixtures in environmental toxicology. We firstly conducted the acute immobilization tests with Daphnia magna exposed to mixtures of diazinon (DZN), fenitrothion (MEP); and thiobencarb (TB) in single, binary, and ternary formulations, and then fitted the results to the AFT model. The 48-h EC50 (concentration required to immobilize 50% of the daphnids at 48 h) values for each pesticide obtained from the AFT model are within a factor of 2 of the corresponding values calculated from the single pesticide exposure tests, indicating the methodology is able to provide credible toxicity values. The AFT model revealed either significant synergistic (DZN and MEP; DZN and TB) or antagonistic (MEP and TB) interactions in binary mixtures, while the interaction pattern of ternary mixture depended on both the concentration levels and concentration ratios of pesticides. With a factor of 2, the AFT model accurately estimated the toxicities for 78% of binary mixture formulations that exhibited significant synergistic effects, and the toxicities for all the ternary formulations. Our results showed that the AFT model can provide a simple and efficient way to quantify the interactions between pesticides and to assess the toxicity of their mixtures. This ability may greatly facilitate the ecotoxicological risk assessment of exposure to multi-chemical mixtures.

Original languageEnglish
Pages (from-to)367-374
Number of pages8
JournalScience of the Total Environment
Volume607-608
DOIs
Publication statusPublished - Dec 31 2017

All Science Journal Classification (ASJC) codes

  • Environmental Engineering
  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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