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首页> 外文期刊>Environmental Science & Technology >Comparison of Species Sensitivity Distributions Derived from Interspecies Correlation Models to Distributions used to Derive Water Quality Criteria
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Comparison of Species Sensitivity Distributions Derived from Interspecies Correlation Models to Distributions used to Derive Water Quality Criteria

机译：从种间相关模型得出的物种敏感度分布与用于衍生水质标准的分布的比较

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摘要

Species sensitivity distributions (SSD) require a large number of measured toxicity values to define a hazard level protective of multiple species. This investigation comprehensively evaluated the accuracy of SSDs generated from toxicity values predicted from interspecies correlation estimation (ICE) models. ICE models are log-log correlations of multiple chemical toxicity values for a pair of species that allow the toxicity of multiple species to be predicted from a single measured acute toxicity value for a surrogate species. ICE SSDs were generated using four surrogate species (fathead minnow, Pimephales promelas; rainbow trout, Oncorhynchus mykiss; sheepshead minnow, Cyprinodon varigatus, and water flea, Daphnia magna). ICE-based hazard concentrations (HC5s) from the 5th percentile of the log-logistic distribution of toxicity values were compared to HC5s determined from the acute toxicity of 55 chemicals fromthe United States Environmental Protection Agency Ambient Water Quality Criteria (AWQC). Measured fish and invertebrate acute toxicity data and HC5s from the AWQC data sets were compared to ICE-based HC5s. Surrogate species choice was found to be an important consideration in developing predictive HC5s. These results illustrated that fish predict fish betterthan invertebrates and D. magna predicted invertebrates better than most fish. For example, a mixed model of predicted fish and invertebrates from fathead minnow and D. magna as surrogate species provided predictive relationships with an average factor of 3.0 (±6.7) over 7 orders of toxic magnitude and several chemical classes (HC_(5predicted)/HC_(5measured)). The application of ICE models is recommended as a valid approach for generating SSDs and hazard concentrations for chemicals with limited toxicity data.
机译：物种敏感度分布（SSD）需要大量测得的毒性值才能确定对多种物种的危害等级。这项研究全面评估了由种间相关估计（ICE）模型预测的毒性值生成的SSD的准确性。 ICE模型是一对物种的多个化学毒性值的对数-对数相关性，可以从一个替代物种的单个测量的急性毒性值来预测多个物种的毒性。 ICE SSD是使用四种替代物种（无头（鱼，Pimephales promelas；虹鳟鱼，Oncorhynchus mykiss；有黑头min鱼，Cyprinodon varigatus和水蚤，Daphnia magna）生成的。将毒性值的对数逻辑分布的第5个百分位数中基于ICE的危害浓度（HC5）与根据美国环境保护局环境水质标准（AWQC）的55种化学品的急性毒性确定的HC5进行了比较。将来自AWQC数据集的鱼类和无脊椎动物的急性毒性数据和HC5与基于ICE的HC5进行了比较。发现替代物种的选择是开发预测性HC5的重要考虑因素。这些结果说明，鱼类比无脊椎动物预测的鱼类更好，而玛格纳鳄比大多数鱼类预测的无脊椎动物更好。例如，预测的黑头fat鱼和D. magna作为替代物种的鱼类和无脊椎动物的混合模型提供了预测关系，在7个数量级的毒性等级和几种化学类别下，平均系数为3.0（±6.7）（HC_（5predicted）/ HC_（5测量））。建议使用ICE模型作为生成SSD的有效方法和毒性数据有限的化学品的危险浓度。

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