Evidence map›Paper›PMID 29870141›Full record

ArticleIntegrated environmental assessment and management2018

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

Cheryl A Murphy, Roger M Nisbet, Philipp Antczak, Natàlia Garcia-Reyero, Andre Gergs, Konstadia Lika, Teresa Mathews, Erik B Muller, Diane Nacci, Angela Peace and 4 more

Abstract read
In one paragraph

Article in Integrated environmental assessment and management, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Article
  2. Integrating Time-ResolvedEnvironmental science & technology · 2024
    Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Assessing Fish Immunotoxicity by Means ofFrontiers in immunology · 2022
    Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Ecotoxico-lipidomics: An emerging concept to understand chemical-metabolic relationships in comparative fish models.Comparative biochemistry and physiology. Part D, Genomics & proteomics · 2020
    Review
  16. Review
  17. Review
  18. Article
  19. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Cheryl A MurphyDepartment of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA.
Roger M NisbetDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California, USA.
Philipp AntczakInstitute for Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Natàlia Garcia-ReyeroEnvironmental Laboratory, US Army Engineer Research & Development Center, Vicksburg, Mississippi.
Andre Gergsgaiac-Research Institute for Ecosystem Analysis and Assessment, Aachen, Germany.
Konstadia LikaDepartment of Biology, University of Crete, Voutes University Campus, Heraklion, Greece.
Teresa MathewsEnvironmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.
Erik B MullerDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California, USA.
Diane NacciUS Environmental Protection Agency, Office of Research and Development, Narragansett, Rhode Island.
Angela PeaceDepartment of Mathematics and Statistics, Texas Tech University, Lubbock, Texas, USA.
Christopher H RemienDepartment of Mathematics, University of Idaho, Moscow, Idaho, USA.
Irvin R SchultzMarine Sciences Lab, Pacific NW National Laboratory, Sequim, Washington, USA.
Louise M StevensonDepartment of Ecology, Evolution and Marine Biology, University of California, Santa Barbara, California, USA.
Karen H WatanabeSchool of Mathematical and Natural Sciences, Arizona State University, Glendale, Arizona, USA.

Funding

EPA R835797EPA R835798Intramural EPA EPA999999US Environmental Protection Agency's Science R835797, R835798, and R835167
6 · The paper itself

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.

Indexed as

EcosystemEcologyEnvironmental MonitoringModels, TheoreticalRisk AssessmentAdverse outcome pathwaysDynamic energy budgetsEcological risk assessmentMechanisticSuborganismal processes

Identifiers

PMID29870141
PMCPMC6643959

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.