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将亚个体过程纳入生态风险评估的动态能量预算模型中。

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment.

机构信息

Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA.

Department of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California, USA.

出版信息

Integr Environ Assess Manag. 2018 Sep;14(5):615-624. doi: 10.1002/ieam.4063. Epub 2018 Jun 30.

DOI:10.1002/ieam.4063
PMID:29870141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6643959/
Abstract

A working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide "bottom-up" mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a "top-down" approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments. Integr Environ Assess Manag 2018;14:615-624. © 2018 SETAC.

摘要

一个工作组在国家数学与生物合成研究所(NIMBioS)探索了整合两种互补方法的可行性,这些方法与生态风险评估有关。 不良结局途径(AOP)模型提供了“自下而上”的机制,可以预测可能影响个体生长,繁殖和/或生存能力的特定毒理学效应,这些效应来自分子起始事件。 动态能量预算(DEB)模型提供了一种“自上而下”的方法,该方法将胁迫对生长,繁殖和/或生存的影响反向工程为与获取和处理能源资源相关的模块化特征。 因此,AOP 模型量化了可测量的分子,细胞或器官水平事件之间的联系,但它们没有提供一种明确的方法来综合描述在更高组织水平上的胁迫效应。 虽然 DEB 模型为将个体效应与种群和生态系统水平的效应联系起来提供了内在基础,但它们使用抽象变量掩盖了与亚个体生物学的机械联系。 为了利用这两种方法,我们开发了一个概念模型,通过将 AOP 关键事件解释为影响 DEB 变量和速率的损害诱导过程的度量,将 DEB 和 AOP 模型联系起来。 我们报告了为 AOP 模型生成的数据的类型和结构,这些数据也可能对 DEB 模型有用。 我们还报告了正在开发的案例研究,这些研究将 AOP 收集的信息与 DEB 模型合并,并强调了一些挑战。 最后,我们讨论了这两种方法的联系如何改善生态风险评估,并探讨了在预测真实环境中毒物暴露对种群反应方面取得进展的可能性。 综合环境评估与管理 2018;14:615-624。 ©2018 SETAC。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/7bdcbeace05f/nihms-1533816-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/ecce49173f9d/nihms-1533816-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/d93482f7f74e/nihms-1533816-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/6acb31f56836/nihms-1533816-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/7bdcbeace05f/nihms-1533816-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/ecce49173f9d/nihms-1533816-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/d93482f7f74e/nihms-1533816-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/6acb31f56836/nihms-1533816-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0088/6643959/7bdcbeace05f/nihms-1533816-f0004.jpg

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