Tjalling Jager

1
Assessing ecotoxicological effects on a
mechanistic basis the central role of the
individual

• Tjalling Jager
• Dept. Theoretical Biology

2
Predicting environmental risk A road map for
the future

• Tjalling Jager
• Dept. Theoretical Biology

3
Contents

• Whats wrong in risk assessment?
• Use molecule-to-ecosystem to fix it?
• What is the role of the individual?
• A new paradigm

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Contents

• Whats wrong in risk assessment?

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Exposure assessment
mechanistic fate model
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Effects assessment

• Standardised
• exposure time
• test conditions
• species/endpoint
• constant exposure

toxicity test
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Risk assessment?
standard test protocols
mechanistic fate model
time-varying concentrations
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Risk assessment?
mechanistic fate model
mechanistic effects model
time-varying concentrations
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Levels of organisation

• RA is concerned with impacts on systems

mechanistic effects model
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Levels of organisation
Practical advantages amenable to testing
direct ecological relevance
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Levels of organisation
Clear boundaries mass/energy conservation
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Levels of organisation
Clear boundaries mass/energy conservation
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How to build models?
reproduction
growth
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How to build models?
food
Dynamic Energy Budget mass/energy conservation
over entire life cycle
storage
development
maintenance
reproduction
growth
www.debtox.info
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Standard DEB animal
food
faeces
assimilation
reserve
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Standard DEB animal
food
faeces
assimilation
reserve
mobilisation
somatic maintenance
?
1-?
growth
structure
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Standard DEB animal
food
faeces
assimilation
reserve
mobilisation
maturity maintenance
somatic maintenance
?
1-?
growth
reproduction
maturation
p
structure
maturity
buffer
eggs
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Example

• Dendrobaena octaedra and Cu

Jager Klok (2010) Effect on assimilation
80 mg/kg
120 mg/kg
160 mg/kg
200 mg/kg
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Extrapolate up

• Energy budget provides
• consistent life-history traits
• as function of the environment
• Simple link to existing population models

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Extrapolate up

• Euler-Lotka equation
• in a constant environment, all populations grow
  exponentially

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Extrapolate up

• Using the calibrated earthworm model

Jager Klok (2010)
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Extrapolate up

• Using the calibrated earthworm model
• predict growth in other constant environments

0.025
0.02
food 100
0.015
population growth rate (d-1)
0.01
food 90
0.005
0
60
80
100
120
140
160
180
200
concentration (mg/kg soil)
Jager Klok (2010)
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Individual-based models

• DEB-IBM, Martin et al. (2012)
• Every individual is a DEB individual
• stochasticity through mortality and feeding
• Advantages
• interaction with food, time-varying conditions
• species differ mainly in parameter values

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DEB meets IBM

• Calibrate model for Daphnia magna
• performance at different constant food levels

Martin et al. (2013a)
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DEB meets IBM

• Good prediction of control dynamics
• starvation and recovery model essential

Total
Neonates
Juveniles
Adults
Martin et al. (2013a)
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DEB meets IBM

• Using standard toxtest to predict population
  effects

Martin et al. (2013b)
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Extrapolate up

• Energy budget provides link to population models
• Euler-Lotka and IBMs are suitable candidate
• Can we continue this to ecosystem level?
• How to utilise down?

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Adverse outcome pathway
external toxicant
effects on traits
Human toxicology one species lots of
funding focus on individual health
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Adverse outcome pathway
toxicokinetics
energy budget
internal toxicant
external toxicant
effects on traits
physiological processes
life-cycle testing
maintenance
assimilation
?

• In the meantime
• knowledge to reduce animal testing
• quantify model parameters in vitro
• extrapolate between species/chemicals
• To what extent can we simplify?

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Old paradigm
exposure assessment
effects assessment
risk
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New paradigm
exposure assessment
effects assessment
risk
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New paradigm
mechanistic fate model
mechanistic individual model(s)
predicted impacts over time
population ecosystem models
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Final words

• We need mechanistic models for effects
• to link fate models to environmental impacts
• move away from descriptive statistics
• Individual as central level of organisation
• energy budget is an essential element
• interaction between traits and with environment
• Much more work is needed .
• collaboration across disciplines
• focus on simplified mechanisms
• focus on generality

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• Thanks for funding
• IMS (204023/E40)
• OAPPI (215589)
• ENERGYBAR (225314/E40)
• CREAM (PITN-GA-2009-238148)
• More info
• on DEB www.bio.vu.nl/thb (2015 course,
  Marseille, FR)
• on DEBtox www.debtox.info (2016 summercourse,
  DK)

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Caenorhabditis elegans

• Exposed to various chemicals
• life-history traits
• gene expression (transcriptional profiling)

affected process
Swain et al (2010), Wren et al (2011)
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Caenorhabditis elegans
enrichment of genes associated with DNA integrity
and repair
maintenance costs
Swain et al (2010), Wren et al (2011)
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Calanus finmarchicus

• Exposed to marine diesel
• TKTD model for survival (GUTS)
• link biomarker response (GST)

exposure pattern
toxico-kinetic model
toxico-dynamic model
survival over time
Jager Hansen (2013)
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Calanus finmarchicus
exposure pattern
toxico-kinetic model
toxico-dynamic model
survival over time
biomarker over time
Jager Hansen (2013)