物种敏感度分布的非参数核密度估计模型

Non-Parametric Kernel Density Estimation of Developing Species Sensitivity Distributions

针对目前物种敏感度分布参数方法建模所存在的缺点,首次提出基于非参数核密度估计方法的物种敏感度分布模型,并提出相应的最优窗宽和检验方法。选用无机汞作为案例研究对象,利用非参数核密度估计方法和3种传统参数模型分别推导了保护我国水生生物的无机汞的急性水质基准值。结果表明,非参数核密度估计方法在推导无机汞水质基准中的稳健性和精确度都大大优于传统参数模型,能够更好地构建物种敏感度分布曲线。该方法的提出丰富了水质基准的理论方法学,为更好地保护水生生物提供了有力的支撑。

To address the inadequacies associated with parametric density estimations for species sensitivity distributions, we developed a new probabilistic model based on non-parametric kernel density estimation and proposed related optimal bandwidths and testing methods as well. With inorganic mercury as the target compound, the non-parametric kernel density estimation method and three conventional parametric density estimation methods were used to derive acute water quality criteria for protection of aquatic species in China. The results demonstrated that the new probabilistic model was superior over the conventional parametric density estimations in deriving water quality criteria for inorganic mercury, as well as in constructing species sensitivi- ty distribution. The proposed method has enriched the methodological foundation for water quality criteria and provided solid support for protection of aquatic organisms.