Literature DB >> 28316094

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

Takashi Nagai1.   

Abstract

The validity of the application of mixture toxicity models, concentration addition and independent action, to a species sensitivity distribution (SSD) for calculation of a multisubstance potentially affected fraction was examined in laboratory experiments. Toxicity assays of herbicide mixtures using 5 species of periphytic algae were conducted. Two mixture experiments were designed: a mixture of 5 herbicides with similar modes of action and a mixture of 5 herbicides with dissimilar modes of action, corresponding to the assumptions of the concentration addition and independent action models, respectively. Experimentally obtained mixture effects on 5 algal species were converted to the fraction of affected (>50% effect on growth rate) species. The predictive ability of the concentration addition and independent action models with direct application to SSD depended on the mode of action of chemicals. That is, prediction was better for the concentration addition model than the independent action model for the mixture of herbicides with similar modes of action. In contrast, prediction was better for the independent action model than the concentration addition model for the mixture of herbicides with dissimilar modes of action. Thus, the concentration addition and independent action models could be applied to SSD in the same manner as for a single-species effect. The present study to validate the application of the concentration addition and independent action models to SSD supports the usefulness of the multisubstance potentially affected fraction as the index of ecological risk. Environ Toxicol Chem 2017;36:2624-2630.
© 2017 SETAC. © 2017 SETAC.

Entities:  

Keywords:  Algae; Mixture toxicology; Mode of action; Pesticide; Species sensitivity distribution

Mesh:

Substances:

Year:  2017        PMID: 28316094     DOI: 10.1002/etc.3800

Source DB:  PubMed          Journal:  Environ Toxicol Chem        ISSN: 0730-7268            Impact factor:   3.742


  1 in total

1.  Temporal and regional variability of cumulative ecological risks of pesticides in Japanese river waters for 1990-2010.

Authors:  Takashi Nagai; Shunji Yachi; Keiya Inao
Journal:  J Pestic Sci       Date:  2022-02-20       Impact factor: 2.529

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.