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Title: Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model

Abstract

Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) that link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstractmore » variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.« less

Authors:
 [1];  [2];  [3];  [4];  [5];  [6]; ORCiD logo [7];  [8];  [9];  [7];  [10];  [11];  [12]
  1. Michigan State University, East Lansing
  2. University of California Santa Barbara
  3. University of Liverpool, UK
  4. Army Corps of Engineers, Vicksburg
  5. Gaiac
  6. University of Crete
  7. ORNL
  8. University of California, Santa Barbara
  9. U.S. Environmental Protection Agency (EPA)
  10. University of Idaho
  11. Pacific Northwest National Laboratory (PNNL)
  12. Arizona State University
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1423112
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Book
Country of Publication:
United States
Language:
English

Citation Formats

Murphy, Cheryl, Nisbet, Roger, Antczak, Philipp, Reyero, Natalia, Gergs, Andre, Lika, Dina, Mathews, Teresa J., Muller, Eric, Nacci, Dianne, Peace, Angela L., Remien, Chris, Schulz, Irv, and Watanabe, Karen. Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model. United States: N. p., 2018. Web.
Murphy, Cheryl, Nisbet, Roger, Antczak, Philipp, Reyero, Natalia, Gergs, Andre, Lika, Dina, Mathews, Teresa J., Muller, Eric, Nacci, Dianne, Peace, Angela L., Remien, Chris, Schulz, Irv, & Watanabe, Karen. Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model. United States.
Murphy, Cheryl, Nisbet, Roger, Antczak, Philipp, Reyero, Natalia, Gergs, Andre, Lika, Dina, Mathews, Teresa J., Muller, Eric, Nacci, Dianne, Peace, Angela L., Remien, Chris, Schulz, Irv, and Watanabe, Karen. Thu . "Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model". United States. doi:.
@article{osti_1423112,
title = {Linking Adverse Outcome Pathways to Dynamic Energy Budgets: A Conceptual Model},
author = {Murphy, Cheryl and Nisbet, Roger and Antczak, Philipp and Reyero, Natalia and Gergs, Andre and Lika, Dina and Mathews, Teresa J. and Muller, Eric and Nacci, Dianne and Peace, Angela L. and Remien, Chris and Schulz, Irv and Watanabe, Karen},
abstractNote = {Ecological risk assessment quantifies the likelihood of undesirable impacts of stressors, primarily at high levels of biological organization. Data used to inform ecological risk assessments come primarily from tests on individual organisms or from suborganismal studies, indicating a disconnect between primary data and protection goals. We know how to relate individual responses to population dynamics using individual-based models, and there are emerging ideas on how to make connections to ecosystem services. However, there is no established methodology to connect effects seen at higher levels of biological organization with suborganismal dynamics, despite progress made in identifying Adverse Outcome Pathways (AOPs) that link molecular initiating events to ecologically relevant key events. This chapter is a product of a working group at the National Center for Mathematical and Biological Synthesis (NIMBioS) that assessed the feasibility of using dynamic energy budget (DEB) models of individual organisms as a “pivot” connecting suborganismal processes to higher level ecological processes. AOP models quantify explicit molecular, cellular or organ-level processes, but do not offer a route to linking sub-organismal damage to adverse effects on individual growth, reproduction, and survival, which can be propagated to the population level through individual-based models. DEB models describe these processes, but use abstract variables with undetermined connections to suborganismal biology. We propose linking DEB and quantitative AOP models by interpreting AOP key events as measures of damage-inducing processes in a DEB model. Here, we present a conceptual model for linking AOPs to DEB models and review existing modeling tools available for both AOP and DEB.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Feb 01 00:00:00 EST 2018},
month = {Thu Feb 01 00:00:00 EST 2018}
}

Book:
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