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应选择哪种分布来推导出物种敏感性分布?急性和慢性生态毒性数据分析的启示。

Which distribution to choose for deriving a species sensitivity distribution? Implications from analysis of acute and chronic ecotoxicity data.

机构信息

KWR Water Research Institute, Groningenhaven 7, Nieuwegein 3433 PE, the Netherlands; Center for Marine Environmental Studies, Ehime University Bunkyo-cho 3, Matsuyama, Ehime 790-8577, Japan.

Health and Environmental Risk Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.

出版信息

Ecotoxicol Environ Saf. 2024 Jun 15;278:116379. doi: 10.1016/j.ecoenv.2024.116379. Epub 2024 May 6.

Abstract

Species sensitivity distributions (SSDs) estimated by fitting a statistical distribution to ecotoxicity data are indispensable tools used to derive the hazardous concentration for 5 % of species (HC5) and thereby a predicted no-effect concentration in environmental risk assessment. Whereas various statistical distributions are available for SSD estimation, the fundamental question of which statistical distribution should be used has received limited systematic analysis. We aimed to address this knowledge gap by applying four frequently used statistical distributions (log-normal, log-logistic, Burr type III, and Weibull distributions) to acute and chronic SSD estimation using aquatic toxicity data for 191 and 31 chemicals, respectively. Based on the differences in the corrected Akaike's information criterion (AICc) as well as visual inspection of the fitting of the lower tails of SSD curves, the log-normal SSD was generally better or equally good for the majority of chemicals examined. Together with the fact that the ratios of HC5 values of other alternative SSDs to those of log-normal SSDs generally fell within the range 0.1-10, our findings indicate that the log-normal distribution can be a reasonable first candidate for SSD derivation, which does not contest the existing widespread use of log-normal SSDs.

摘要

物种敏感性分布(SSD)是通过拟合统计学分布来估算生态毒性数据的一种不可或缺的工具,可用于推导 5%物种的危险浓度(HC5),从而在环境风险评估中得出预测无影响浓度。虽然有各种统计学分布可用于 SSD 估算,但哪种统计学分布应该使用的基本问题受到的系统分析有限。我们旨在通过使用四种常用的统计学分布(对数正态分布、对数逻辑斯谛分布、Burr 型 III 分布和威布尔分布)来解决这一知识空白,分别使用 191 种和 31 种化学品的急性和慢性 SSD 估算水生毒性数据。基于校正赤池信息量准则(AICc)的差异以及 SSD 曲线下尾部拟合的直观检查,对数正态 SSD 通常对大多数检查的化学品都更好或同样适用。此外,其他替代 SSD 的 HC5 值与对数正态 SSD 的 HC5 值之比通常在 0.1-10 范围内,我们的研究结果表明,对数正态分布可以成为 SSD 推导的合理首选,这并不反对现有对数正态 SSD 的广泛使用。

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