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

Abstract

Here, 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 usefulmore » 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.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6]; ORCiD logo [7];  [8];  [9];  [10];  [11];  [12];  [2];  [13]
  1. Michigan State Univ., East Lansing, MI (United States)
  2. Univ. of California, Santa Barbara, CA (United States)
  3. Univ. of Liverpool, Liverpool (United Kingdom)
  4. U.S. Army Engineer Research & Development Center, Vicksburg, MS (United States)
  5. Gaiac - Research Institute for Ecosystem Analysis and Assessment, Aachen (Germany)
  6. Univ. of Crete, Heraklion (Greece)
  7. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  8. Univ. of California, Santa Barbara, CA (United States); Univ. of Science and Technology, Trondheim (Norway)
  9. U.S. Environmental Protection Agency (EPA), Narragansett, RI (United States)
  10. Texas Tech Univ., Lubbock, TX (United States)
  11. Univ. of Idaho, Moscow, ID (United States)
  12. Pacific Northwest National Lab. (PNNL), Richland, WA (United States); National Oceanic and Atmospheric Administration, Seattle, WA (United States)
  13. Arizona State Univ., Glendale, AZ (United States)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1465049
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Integrated Environmental Assessment and Management
Additional Journal Information:
Journal Volume: 14; Journal Issue: 5; Journal ID: ISSN 1551-3777
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; adverse outcome pathways; dynamic energy budgets; ecological risk assessment; suborganismal processes; mechanistic

Citation Formats

Murphy, Cheryl A,, Nisbet, Roger M., Antczak, Philipp, Reyero, Natalia Garcia-, Gergs, Andre, Lika, Dina, Mathews, Teresa J., Muller, Eric, Nacci, Dianne, Peace, Angie, Remien, Christopher H., Schultz, Irvin R., Stevenson, Louise, and Watanabe, Karen. Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment. United States: N. p., 2018. Web. doi:10.1002/ieam.4063.
Murphy, Cheryl A,, Nisbet, Roger M., Antczak, Philipp, Reyero, Natalia Garcia-, Gergs, Andre, Lika, Dina, Mathews, Teresa J., Muller, Eric, Nacci, Dianne, Peace, Angie, Remien, Christopher H., Schultz, Irvin R., Stevenson, Louise, & Watanabe, Karen. Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment. United States. doi:10.1002/ieam.4063.
Murphy, Cheryl A,, Nisbet, Roger M., Antczak, Philipp, Reyero, Natalia Garcia-, Gergs, Andre, Lika, Dina, Mathews, Teresa J., Muller, Eric, Nacci, Dianne, Peace, Angie, Remien, Christopher H., Schultz, Irvin R., Stevenson, Louise, and Watanabe, Karen. Tue . "Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment". United States. doi:10.1002/ieam.4063. https://www.osti.gov/servlets/purl/1465049.
@article{osti_1465049,
title = {Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment},
author = {Murphy, Cheryl A, and Nisbet, Roger M. and Antczak, Philipp and Reyero, Natalia Garcia- and Gergs, Andre and Lika, Dina and Mathews, Teresa J. and Muller, Eric and Nacci, Dianne and Peace, Angie and Remien, Christopher H. and Schultz, Irvin R. and Stevenson, Louise and Watanabe, Karen},
abstractNote = {Here, 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.},
doi = {10.1002/ieam.4063},
journal = {Integrated Environmental Assessment and Management},
number = 5,
volume = 14,
place = {United States},
year = {2018},
month = {6}
}

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