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使用混合毒性模型预测除草剂混合物对多种藻类物种的影响。

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

作者信息

Nagai Takashi

机构信息

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

出版信息

Environ Toxicol Chem. 2017 Oct;36(10):2624-2630. doi: 10.1002/etc.3800. Epub 2017 Apr 19.

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.

摘要

在实验室实验中,研究了混合物毒性模型(浓度相加和独立作用)应用于物种敏感度分布(SSD)以计算多种物质潜在受影响分数的有效性。使用5种周丛藻类进行了除草剂混合物的毒性测定。设计了两个混合物实验:一个是5种作用方式相似的除草剂混合物,另一个是5种作用方式不同的除草剂混合物,分别对应浓度相加和独立作用模型的假设。将实验获得的对5种藻类的混合物效应转换为受影响(对生长率的效应>50%)物种的分数。直接应用于SSD的浓度相加和独立作用模型的预测能力取决于化学物质的作用方式。也就是说,对于作用方式相似的除草剂混合物,浓度相加模型的预测比独立作用模型更好。相反,对于作用方式不同的除草剂混合物,独立作用模型的预测比浓度相加模型更好。因此,浓度相加和独立作用模型可以与单物种效应一样应用于SSD。本研究验证浓度相加和独立作用模型应用于SSD,支持了多种物质潜在受影响分数作为生态风险指标的有用性。《环境毒理学与化学》2017年;36:2624 - 2630。© 2017 SETAC。

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