Group 4: Session 1
Criteria: transparent, standardization; communicable; standard test species; matrix models for
screening, IBMs for more detailed assessment; 5 parameter honey bee model vs 120 parameter
honey bee model
 How to put it into practice? Incentives.
 Who needs to understand how the model works?
 Adaptive management
 Repository of models
 Parameterize is not the same as validate
 Is the hitch between the modelers or the link between modelers and decision makers?
Goals: standard ecorisk; awareness of cost/benefit of complexity; reduce redundancy; capture
synergy and feedback loops; ideally all levels of biological organization; one model fit for
purpose.
Challenges: Jargon; time needed to get population-level data; how to model ecosystem services;
registrants are going to submit the fewest data points possible; too many models – don’t want to
look at it; momentum vs resistance to change; conflict of interest – people doing research are the
people who profit from product; cost-benefit between first principles and one based on a specific
site/data.
Integration: Weighting – site-specific results should weigh more than literature; mechanisms are
conserved (multispecies); tradeoff between accuracy of data and generalizability; mismatch
between measurement and assessment endpoints; T&E species – endpoint is known; endpoint of
ecosystem services?; deciding what matters – top down vs bottom up; resources for each
problem; compensatory mechanisms; indicators/proxies – Eguidance from Australia; What is it
all about? Theoretical endpoints: lowest observed effect, percent lambda, extinction; goal is to be
protective – but what does that mean? FIFRA: always have cost/benefit analysis; ESA: not
allowed cost/benefit analysis; Is there agreement in the US on protection goals?
Group 4: Session 2
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What can AOP do for the diversity of contaminants? Mechanism is less clear; AOP Wiki;
QSAR
How do AOPs handle multiple stressors? Limitation – links to one thing; life-history
tradeoffs require feedback, more tractable
Is the AOP community diverse enough?
Vitellogenin AOP (e.g., Irv’s model) is one of few mechanisms that link across scales;
standardization in AOP framework; Vitellogenin correlates with egg production (Miller
paper), but not mechanistic.
Can we use the same framework to model across levels of biological organization?
Is the goal of AOP to be a platform for screening thousands of chemicals? Toxcast
Why this workshop now? If it is not moving quickly now, it will be. Merging between
biomed and ecotox resources.
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Why not use animals more widely? Cost of subcellular vs organismal tests. How does
cost scale across levels of biological organization?
Mitigate organismal level is hitched to correlative; starvation? Interactions?
Semi-empirical/virtual model could be a proof of concept to demonstrate added value
Not every model should be individual based
Group 4: Session 3
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Network analysis
Individual-based movement models
Trait-based approach; how often do functional groups exhibit similar toxicities?
Null model
Linking biodiversity management – ecosystem services
Feasible to do demo model virtual case study; proof of concept; determine added value or
is it ok that groups carry on
Demo models
Trace documents – standardization
Textbook on modeling
If regulators are skeptical, get them to see the population model first
Molecule to population
Population to community & ecosystem?
ODEs can represent space
Fate models are not validated
Biodiversity – ecosystem services literature
Null model with course predictions
What are standards for when the model works well enough?
Structured decision making
Ecosystem-based management decisions
Interaction strengths
Network analysis – cross-pollinate general principles
Complexity or missing data? More complicated output to explain