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Predicting herbicide mixture effects on multiple algal species using mixture toxicity models.

Takashi Nagai1

  • 1Institute for Agro-Environmental Sciences, NARO, Tsukuba, Ibaraki, Japan.

Environmental Toxicology and Chemistry
|March 20, 2017
PubMed
Summary

This study validated mixture toxicity models for ecological risk assessment. The models accurately predicted effects of herbicide mixtures on algae, supporting their use in ecological risk assessments.

Keywords:
AlgaeMixture toxicologyMode of actionPesticideSpecies sensitivity distribution

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Area of Science:

  • Environmental Toxicology
  • Ecotoxicology
  • Aquatic Ecology

Background:

  • Assessing ecological risk from chemical mixtures is challenging.
  • Mixture toxicity models like concentration addition and independent action are used.
  • Species sensitivity distributions (SSD) are crucial for risk assessment.

Purpose of the Study:

  • To examine the validity of applying mixture toxicity models (concentration addition and independent action) to SSDs.
  • To calculate a multisubstance potentially affected fraction (MPAF) for ecological risk assessment.
  • To compare the predictive accuracy of these models based on herbicide mode of action.

Main Methods:

  • Laboratory toxicity assays were performed on five periphytic algal species.
  • Two herbicide mixtures were tested: one with similar modes of action and one with dissimilar modes of action.
  • Experimental mixture effects were used to calculate the fraction of affected species and validate model predictions.

Main Results:

  • The predictive accuracy of concentration addition and independent action models applied to SSDs was dependent on the mode of action of the mixture components.
  • Concentration addition performed better for mixtures with similar modes of action.
  • Independent action performed better for mixtures with dissimilar modes of action.

Conclusions:

  • Both concentration addition and independent action models can be applied to SSDs similarly to single-species effects.
  • The study validates the application of these models to SSDs for calculating MPAF.
  • The multisubstance potentially affected fraction is a useful index for ecological risk assessment of chemical mixtures.