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优化种间相关性估计模型选择的框架,以解决水生数据库中的物种多样性和毒性差距问题

Framework for Optimizing Selection of Interspecies Correlation Estimation Models to Address Species Diversity and Toxicity Gaps in an Aquatic Database.

作者信息

Bejarano Adriana C, Raimondo Sandy, Barron Mace G

机构信息

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

USEPA, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, Florida 32561, United States.

出版信息

Environ Sci Technol. 2017 Jul 18;51(14):8158-8165. doi: 10.1021/acs.est.7b01493. Epub 2017 Jul 6.

Abstract

The Chemical Aquatic Fate and Effects (CAFE) database is a tool that facilitates assessments of accidental chemical releases into aquatic environments. CAFE contains aquatic toxicity data used in the development of species sensitivity distributions (SSDs) and the estimation of hazard concentrations (HCs). For many chemicals, gaps in species diversity and toxicity data limit the development of SSDs, which may be filled with Interspecies Correlation Estimation (ICE) models. Optimization of ICE model selection and integration ICE-predicted values into CAFE required a multistep process that involved the use of different types of data to assess their influence on SSDs and HC estimates. Results from multiple analyses showed that SSDs supplemented with ICE-predicted values generally produced HC5 estimates that were within a 3-fold difference of estimates from measured SSDs (58%-82% of comparisons), but that were often more conservative (63%-76% of comparisons) and had lower uncertainty (90% of comparisons). ICE SSDs did not substantially underpredict toxicity (<10% of comparisons) when compared to estimates from measured SSD. The incorporation of ICE-predicted values into CAFE allowed the development of >800 new SSDs, increased diversity in SSDs by an average of 34 species, and augmented data for priority chemicals involved in accidental chemical releases.

摘要

化学物质的水生归宿与效应(CAFE)数据库是一种有助于评估化学物质意外释放到水生环境中的工具。CAFE包含用于物种敏感度分布(SSD)开发和危害浓度(HC)估算的水生毒性数据。对于许多化学物质而言,物种多样性和毒性数据方面的差距限制了SSD的开发,而种间相关性估算(ICE)模型或许可以填补这些差距。ICE模型选择的优化以及将ICE预测值整合到CAFE中需要一个多步骤过程,该过程涉及使用不同类型的数据来评估它们对SSD和HC估算的影响。多项分析结果表明,补充了ICE预测值的SSD通常得出的HC5估算值与实测SSD估算值相差在3倍以内(58% - 82%的比较结果),但往往更为保守(63% - 76%的比较结果)且不确定性更低(90%的比较结果)。与实测SSD估算值相比,ICE SSD在毒性预测方面并没有显著低估(<10%的比较结果)。将ICE预测值纳入CAFE使得能够开发出800多个新的SSD,SSD中的物种多样性平均增加了34种,并增加了意外化学物质释放所涉及的优先化学品的数据。

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