State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, 210046, China.
Environ Sci Pollut Res Int. 2014 Jan;21(1):159-67. doi: 10.1007/s11356-013-1462-y. Epub 2013 Jan 15.
Species sensitivity distributions (SSDs) are increasingly used in both ecological risk assessment and derivation of water quality criteria. However, there has been debate about the choice of an appropriate approach for derivation of water quality criteria based on SSDs because the various methods can generate different values. The objective of this study was to compare the differences among various methods. Data sets of acute toxicities of 12 substances to aquatic organisms, representing a range of classes with different modes of action, were studied. Nine typical statistical approaches, including parametric and nonparametric methods, were used to construct SSDs for 12 chemicals. Water quality criteria, expressed as hazardous concentration for 5% of species (HC5), were derived by use of several approaches. All approaches produced comparable results, and the data generated by the different approaches were significantly correlated. Variability among estimates of HC5 of all inclusive species decreased with increasing sample size, and variability was similar among the statistical methods applied. Of the statistical methods selected, the bootstrap method represented the best-fitting model for all chemicals, while log-triangle and Weibull were the best models among the parametric methods evaluated. The bootstrap method was the primary choice to derive water quality criteria when data points are sufficient (more than 20). If the available data are few, all other methods should be constructed, and that which best describes the distribution of the data was selected.
物种敏感性分布(SSD)越来越多地用于生态风险评估和水质标准的推导。然而,基于 SSD 推导水质标准的适当方法的选择一直存在争议,因为各种方法可能会产生不同的数值。本研究的目的是比较各种方法之间的差异。研究了代表不同作用模式的多种类别的 12 种物质对水生生物的急性毒性数据集。使用了 9 种典型的统计方法,包括参数和非参数方法,为 12 种化学物质构建了 SSD。使用多种方法推导了表示 5%物种有害浓度(HC5)的水质标准。所有方法都产生了可比的结果,并且不同方法生成的数据显著相关。所有包容性物种的 HC5 估计值的变异性随着样本量的增加而减小,并且应用的统计方法之间的变异性相似。在所选择的统计方法中,bootstrap 方法是所有化学物质的最佳拟合模型,而 log-triangle 和 Weibull 是评估的参数方法中的最佳模型。当数据点充足(超过 20 个)时,bootstrap 方法是推导水质标准的主要选择。如果可用数据很少,则应构建所有其他方法,并选择最能描述数据分布的方法。