time is of the essence! tjalling jager dept. theoretical biology
TRANSCRIPT
Time is of the essence!
Tjalling Jager
Dept. Theoretical Biology
Challenges of ecotox
Some 100,000 man-made chemicals For animals alone, >1 million species described Complex dynamic exposure situations Species interact dynamically in ecosystems
We cannot (and should not) test all permutations!
Extrapolation
“Protection goal”
Laboratory tests
time is of the essence!
concentrations over time and
space
environmental characteristics and emission pattern
Fate modelling
mechanisticfate model
physico-chemical properties under laboratory conditions
Fate modelling
oil-spill modelling
pesticide fate modelling
prediction effects in dynamic
environment
Classic ecotox
effects data over time for one (or few) set(s) of conditions
Description for:• one endpoint• one timepoint• constant exposure• one set of conditions
Description for:• one endpoint• one timepoint• constant exposure• one set of conditions
EC50NOEC
summary statistics
proper measures of
toxicity
Learn from fate modelling
effects data over time for one (or few) set(s) of conditions
that do not depend on time or conditions
prediction effects in dynamic
environment
mechanisticmodel forspecies A
model parameters for
species
test conditions
Data analysis
mechanisticmodel forspecies A
effects data over time for one (or few) set(s) of conditions
model parameters that do not depend on time or conditions
model parameters for
toxicant
life-history information of the species
prediction life-history traits
over time
model parameters for
species
model parameters for
toxicant
Educated predictions
mechanisticmodel forspecies A
dynamic environment: exposure and
conditions
only for one species ... model parameters that do not depend on time or conditions
mechanisticmodel forspecies B
model parameters
for species A
model parameters for toxicant
Community effects
mechanisticmodel for
a community
simulate community effects and recovery over time
mechanisticmodel forspecies A
dynamic environment
model parameters
for species A
model parameters for toxicant
What individual model?
mechanisticmodel forspecies A
dynamic environment
model parameters
for species A
model parameters for toxicant
externalconcentration
(in time)
toxico-kineticmodel
toxico-kineticmodel
TKTD modelling
internalconcentration
in time
process modelfor the organism
process modelfor the organism
effects onendpoints
in timetoxicokinetics
toxicodynamics
externalconcentration
(in time)
toxico-kineticmodel
toxico-kineticmodel
TKTD modelling
internalconcentration
in time
toxicokinetics
TKTD modelling
internalconcentration
in time
process modelfor the organism
process modelfor the organism
effects onendpoints
in time
toxicodynamics
Organisms are complex …
process modelfor the organism
process modelfor the organism
Learn from fate modellers
Make an idealisation of the system how much biological detail do we minimally need …
– to explain how an organism grows, develops and reproduces– to explain effects of stressors on life history– to predict effects for untested situations– without being species- or stressor-specific
internalconcentration
in time
process modelfor the organism
effects onendpoints
in time
Dynamic Energy Budget
Organisms obey mass and energy conservation– find the simplest set of rules ...– over the entire life cycle ...– for all organisms (related species follow related rules)– most appropriate DEB model depends on species and question
resources
waste products
growth
maintenance
maturation
offspring
Kooijman (2010)
The “DEBtox” concept
externalconcentration
(in time)
toxico-kinetics
toxico-kinetics internal
concentrationin time DEB
parametersin time
DEBmodel
DEBmodel
repro
growth
survival
feeding
hatching
…
The “DEBtox” concept
externalconcentration
(in time)
toxico-kinetics
toxico-kinetics internal
concentrationin time DEB
parametersin time
DEBmodel
DEBmodel
Internal concentration are often not measured …
repro
growth
survival
feeding
hatching
…DEB parameter cannot be measured …
“Standard” tests ...
mechanisticmodel forspecies A
constant exposure, ad libitum food
Many DEBtox examples, e.g.: http://www.bio.vu.nl/thb/users/tjalling
model parameters for
species
model parameters for
toxicant
Dynamic exposure
mechanisticmodel forspecies A
dynamic exposure pattern,different food levels ...
Daphnia magna and fenvalerate– modified 21-day reproduction test– pulse exposure for 24 hours– two (more or less) constant food levels
Pieters et al (2006)
model parameters for
species
model parameters for
toxicant
Pulse exposure
0
1
2
3
4
0
1
2
3
4
0 5 10 15 200
1
2
3
4
0 5 10 15 200
1
2
3
4
0
10
20
30
40
50
60
70
0
10
20
30
40
50
60
70
0 5 10 15 200
10
20
30
40
50
60
70
0 5 10 15 200
10
20
30
40
50
60
700
0.2
0.4
0.6
0.8
1
0
0.2
0.4
0.6
0.8
1
0 5 10 15 200
0.2
0.4
0.6
0.8
1
0 5 10 15 200
0.2
0.4
0.6
0.8
1
Body length Cumulative offspring Fraction surviving
Hig
h f
oo
dL
ow
fo
od
mode of action: ‘assimilation’mode of action: ‘assimilation’
Insights• parameters independent of food• chemical effects fully reversible• reproduction rate slows down …
mechanisticmodel forspecies B
Work needed
For the individual level– select relevant species and appropriate DEB models– adapt/develop model code, allow time-variable inputs– collect and analyse relevant existing test data
Evaluate– are DEB models useful?– what are limitations?– what are major gaps in knowledge?– what test protocol is most useful?
mechanisticmodel forspecies A
Community level
What makes community different?– dynamic interactions between species– less or more sensitive to toxicants?
mechanisticmodel for
a community
mechanisticmodel forspecies A
mechanisticmodel forspecies B
Community level
Food web models can become rather complex …– results depend heavily on modelling choices– difficult to parameterise– focus on furry animals …– little general insight gained– not useful for generic RA
Canonical community
Start simple:– each species a simple DEB model– closed system (open for energy)– include nutrient recycling
Canonical community
producer
consumer
nutrients
decomposer detritus
light
predator
Start simple:– each species a simple DEB model– closed system (open for energy)– include nutrient recycling
consumer
predatordecomposer detritus
Using the DEB community
producernutrients light
previous project at VU-ThB (EU-MODELKEY)collaboration with SCK-CEN, Belgium (EU-STAR)
lightproducer
Using the DEB community
consumer
predatordecomposer
nutrients
detritus
previous collaborations, e.g., Univ. Antwerp (EU-NoMiracle, EU-OSIRIS)collaboration with UFZ, Leipzig (EU-CREAM)
detritus
consumer
lightproducer
Using the DEB community
decomposer
nutrients
collaboration with Eawag, Switzerland (EU-CREAM)collaboration with IRSN, France
predator
detritus
consumer
lightproducer
Using the DEB community
decomposer
nutrients
previous projects at VU-ThB
predator
Work needed
For the community level– specify interactions between the species– code a community with DEB populations– simulations for various scenarios
Evaluate– what’s different at the community level?– more or less effect?– correspondence to e.g., mesocosm?– identify major gaps in knowledge
mechanisticmodel for
a community
Wrapping up
Time is of the essence!– an organism is a dynamic system …– that interacts dynamically with others …– in a dynamic environment …– with dynamic exposure to chemicals
NOEC, EC50 etc. are useless …
time is of the essence!
Wrapping up
Mechanistic models essential for the individual– to extract time-independent parameters from data– to extrapolate to untested dynamic conditions– to increase efficiency of risk assessment– learn from fate and toxicokinetics modellers …
Integrate models into a simple community– study how interactions affect toxicant responses– study recovery of the community
Wrapping up
Advantages of using DEB as basis– well-tested theory for individuals– mechanistic, dynamic, yet (relatively) simple– deals with the entire life cycle– not species- or chemical-specific– small but well-connected international DEB community
resources
waste products
growth
maintenance
maturation
offspring
Wrapping up
This project tries to deliver “proof of concept”– can DEB serve as a general platform?– can simple mechanistic community models help RA?– how can we modify test protocols?– where are the major stumbling blocks?
More information
on DEB: http://www.bio.vu.nl/thb
on my work: http://www.bio.vu.nl/thb/users/tjalling
time is of the essence!
Ex.1: maintenance costs
time
cum
ula
tive
off
spri
ng
time
bo
dy
len
gth
TPT
Jager et al. (2004)
Ex.2: growth costs
time
bo
dy
len
gth
time
cum
ula
tive
off
spri
ng Pentachlorobenzene
Alda Álvarez et al. (2006)
Ex.3: egg costs
time
cum
ula
tive
off
spri
ng
time
bo
dy
len
gth
Chlorpyrifos
Jager et al. (2007)