2015 Progress Report: Dynamical Systems Models Based on Energy Budgets for Ecotoxicological Impact Assessment

EPA Grant Number: R835797
Title: Dynamical Systems Models Based on Energy Budgets for Ecotoxicological Impact Assessment
Investigators: Nisbet, Roger M. , Muller, Erik B , Whitehead, Andrew
Institution: University of California - Santa Barbara , University of California - Davis
EPA Project Officer: Lasat, Mitch
Project Period: June 1, 2015 through May 31, 2018 (Extended to May 31, 2019)
Project Period Covered by this Report: June 1, 2015 through May 31,2016
Project Amount: $799,723
RFA: Systems-Based Research for Evaluating Ecological Impacts of Manufactured Chemicals (2014) RFA Text |  Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Ecosystems , Safer Chemicals

Objective:

The overarching aim of the research is to use theoretical and experimental methods, based on that Dynamic Energy Budget (DEB) models, to inform ecological risk assessment (ERA) by determining how the effects of exposure to chemical stressors are expressed across levels of biological organization. We aim to: (1) develop new modular DEB models with explicit feedbacks representing regulatory processes in response to toxicant exposure in an organism; (2) determine how genomic data on two model organisms (the waterflea Daphnia and the estuarine fish Fundulus) experiencing combined food and chemical stress relate to parameters in DEB models; (3) predict organismal and population "tipping points" caused by failure of physiological and population regulatory processes; (4) develop models of adaptation to stress in chronically polluted environments; and (5) evaluate the applicability of our findings to non-model organisms.

Progress Summary:

During year 1, we collaborated with two other investigators, including one (Dr. C. Salice) with support from this STAR program "Systems-Based Research for Evaluating Ecological Impacts of Manufactured Chemicals," on an extensive review relating to our overarching goal. We evaluated the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. The review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals, and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected).
 
We developed new models addressing specific objectives (1) and (3). Objective (1) recognizes that biological feedbacks play a crucial role in determining effects of environmental stressors on organisms. Focusing on reactive oxygen species (ROS) that are widely recognized as a crucial mediator of many stressor effects, we investigated how feedback strength affects the ability of organisms to mitigate adverse effects of exposure. Our models account for specific positive and negative feedbacks representing production of ROS due to metabolism and the stressor, ROS reactions with cellular compounds that cause damage, and cellular control of both ROS and damage. We identified conditions that lead to two types of tipping points (objective (3)): those induced by changes in stressor intensity, and those induced by the history of exposure. The models quantify dynamics of cellular control, and could therefore be used to estimate the metabolic costs of stress and help integrate them into models that use energetic consideratiosn to model organism's response to the environment. 
 
We started work relating to objectives (1) and (3) through a working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS), co-led by PI Nisbet and Dr. C. Murphy, another STAR grantee. In spring 2016, participants in this group completed a series of experiments on Daphnia exposed to coal ash from which we anticipate data on gene expression, metal accumulation, growth and reproduction at two food levels. Through this working group, we have initiated a wide network on collaborations that aim to link DEB models to Adverse Outcome Pathways (AOPs).
 
Leveraged activities enhanced by this award included the use of DEB theory in projects performed in collaboration with investigators in the University of California Center for Environmental Implications of Nanotechnology (UC CEIN).

 

Future Activities:

Activities relating to objectives (1)-(3) will continue. Work on objective (2) will emphasize work on killifish (Fundulus spp.) that will support new theory for objective (4).


Journal Articles on this Report : 3 Displayed | Download in RIS Format

Other project views: All 38 publications 14 publications in selected types All 13 journal articles
Type Citation Project Document Sources
Journal Article Miller RJ, Muller EB, Cole B, Martin T, Nisbet R, Bielmyer-Fraser GK, Jarvis TA, Keller AA, Cherr G, Lenihan HS. Photosynthetic efficiency predicts toxic effects of metal nanomaterials in phytoplankton. Aquatic Toxicology 2017;183:85-93. R835797 (2015)
R835797 (2016)
  • Abstract from PubMed
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  • Abstract: ScienceDirect-Abstract
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  • Other: ScienceDirect-Full Text PDF
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  • Journal Article Rohr JR, Salice CJ, Nisbet RM. The pros and cons of ecological risk assessment based on data from different levels of biological organization. Critical Reviews in Toxicology 2016;46(9):756-784. R835797 (2015)
    R835797 (2016)
    R835188 (Final)
    R835800 (2016)
    R835800 (2017)
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  • Abstract from PubMed
  • Associated PubMed link
  • Full-text: University of South Florida-Full Text PDF
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  • Abstract: Taylor & Francis-Abstract
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  • Journal Article Klanjscek T, Muller EB, Nisbet RM. Feedbacks and tipping points in organismal response to oxidative stress. Journal of Theoretical Biology 2016;404:361-374. R835797 (2015)
    R835797 (2016)
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  • Abstract: ResearchGate-Abstract
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  • Supplemental Keywords:

    Individual-based model, dynamic energy budget, DEB, DEBtox, adverse outcome pathways, metabolism, ecology, ecosystem, scaling, toxics

    Progress and Final Reports:

    Original Abstract
  • 2016 Progress Report
  • 2017 Progress Report