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首页> 外文期刊>Environmental Science & Technology >Development and Practical Application of Petroleum and Dispersant Interspecies Correlation Models for Aquatic Species
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Development and Practical Application of Petroleum and Dispersant Interspecies Correlation Models for Aquatic Species

机译：水生物种的石油和分散种间相关模型的开发和实际应用

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摘要

Assessing the acute toxicity of oil has generally relied on existing toxicological data for a relatively few standard test species, which has limited the ability to estimate the impacts of spilled oil on aquatic communities. Interspecies correlation estimation (ICE) models were developed for petroleum and dispersant products to facilitate the prediction of toxicity values to a broader range of species and to better understand taxonomic differences in species sensitivity. ICE models are log linear regressions that can be used to estimate toxicity to a diversity of taxa based on the known toxicity value for a surrogate tested species. ICE models have only previously been developed for nonpetroleum chemicals. Petroleum and dispersant ICE models were statistically significant for 93 and 16 unique surrogate-predicted species pairs, respectively. These models had adjusted coefficient of determinations (adj-R~2), square errors (MSE) and positive slope ranging from 0.29 to 0.99, 0.0002 to 0.311, and 0.187 to 2.665, respectively. Based on model cross-validation, predicted toxicity values for most ICE models (＞90%) were within 5-fold of the measured values, with no influence of taxonomic relatedness on prediction accuracy. A comparison between hazard concentrations (HC) derived from empirical and ICE-based species sensitivity distributions (SSDs) showed that HC values were within the same order of magnitude of each other. These results show that ICE-based SSDs provide a statistically valid approach to estimating toxicity to a range of petroleum and dispersant products with applicability to oil spill assessment.
机译：评估油类的急性毒性通常依赖于相对较少的标准测试物种的现有毒理学数据，这限制了估计溢油对水生生物影响的能力。为石油和分散剂产品开发了种间相关估计（ICE）模型，以促进对更广泛物种的毒性值的预测，并更好地理解物种敏感性的分类学差异。 ICE模型是对数线性回归，可用于基于替代测试物种的已知毒性值来估计对分类单元多样性的毒性。 ICE模型以前仅针对非石油化学品开发。石油和分散剂ICE模型分别对93和16个唯一的替代物预测物种对具有统计学意义。这些模型的调整后的确定系数（adj-R〜2），平方误差（MSE）和正斜率分别为0.29至0.99、0.0002至0.311和0.187至2.665。基于模型交叉验证，大多数ICE模型的预测毒性值（＞ 90％）在测量值的5倍以内，而分类学相关性对预测准确性没有影响。根据经验和基于ICE的物种敏感性分布（SSD）得出的危害浓度（HC）之间的比较显示，HC值彼此之间在同一数量级内。这些结果表明，基于ICE的SSD提供了一种统计上有效的方法，可以评估对一系列石油和分散剂产品的毒性，并且适用于漏油评估。

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  • 来源
    《Environmental Science & Technology》 |2014年第8期|4564-4572|共9页
  • 作者

    Adriana C. Bejarano; Mace G. Barron;

  • 作者单位

    Research Planning, Inc., 1121 Park Street, Columbia, South Carolina 29201, United States;

    U.S. Environmental Protection Agency, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, Florida 32561, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
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  • 正文语种 eng
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