淡水水生态基准方法学研究:数据筛选与模型计算
Methodologies for Deriving Aquatic Life Criteria (ALC): Data Screening and Model Calculating
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摘要: 水生态基准研究的核心是水生态基准方法学,如何鉴于现有的生态毒理学数据推导出科学合理的基准值,并达到切实保护水生生物的目的,是水生态基准研究的重点。论文从淡水水生态基准方法学中数据筛选和模型计算出发,系统地阐述和比较了现有方法学中关于数据的数量和质量、本土物种数据和非本土物种数据、实验室试验数据和野外现场试验数据、常规测试指标和非常规测试指标以及数据的整理等数据筛选原则,并对评估因子法、物种敏感度分布曲线、种间关联预测以及生态毒理模型等水生态基准的计算模型进行比较。参照国外水质基准推导的过程及我国水生态系统的特征,发展我国水生态基准研究中数据的筛选原则以及科学合理的基准计算方法,以期为建立我国淡水水生态基准推导方法学提供研究基础和科学依据。Abstract: Aquatic life criteria (ALC) should be based on scientific and existing data and models in order to ensure the most effective aquatic life methodology. This review was undertaken to identify key outstanding issues of data screening and model calculating regarding the establishment of ALC, including data quantity and data quality, native species vs. non-native species, laboratory test vs. field test, traditional vs. non-traditional endpoints and data reduction, as well as ALC estimated models of assessment factors (AFs), species sensitivity distribution (SSDs), interspecies correlation estimates (ICEs). A proposed approach focused on data screening and model calculating for developing ALC in China were also discussed, based on modification of existing methodologies and specified taxonomic diversity in China.
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