1. Dynamic energy budgets in individual based population models
Cross species test and application
A. Gergs · H. Selck · M. Hammers-Wirtz · A. Palmqvist

2. Extrapolations in risk assement of chemicals
Constant vs. time variable exposure
Extrapolation of population level effects from individual level toxicity tests
Laboratory to field extrapolation …
Mechanistic effect modelling

3. Individual-based population model (IBM)
Individual organism
Individual organism
Individual organism
life history traits
behaviours
food conditions
toxic exposure

4. Conceptual illustration of the IBM approach
newborn
Feeding
Ageing
growth
juvenile development
born juveniles
brood size
embryo development 
yes no
maximal age ?
Adult?
Birthing?
Preuss et al. (2009) Ecological Modelling 220:

5. Comparability of IBMs Kulkarni et al. (2014) Chemosphere 112: 340–347
Strauss et al. (2016) Ecological Modelling 321: 84-97

6. Dynamic energy budgets in IBMs
Abundance [#]
Time [d]
Stage dependent mortality
Figure: Martin et al (2013) American Naturalist 181:

7. Size dependent starvation resistance
Daphnia magna
Notonecta maculata
Fraction surviving [-]
Fraction surviving [-]
Time [d]
Time [d]
Assumption
scaled mobilisation flux is changed in a way that somatic maintenance costs are always paid
Scaled reserve density [-]
Time [d]
Gergs & Jager (2014) Journal of Animal Ecology 83: 758–768

8. DEB parametrization for Daphnia magna
Size dependent starvation
Filtration rate
Growth
Reproduction
Gergs et al. (2014) PlosOne 9: e91503

9. Emerging population dynamics
mean, range

10. Emerging population dynamics
data
model

11. Cross species transferability
Growth
Reproduction
Gergs et al. (in prep.)

12. Cross species test data model Food availability
Gergs et al. (in prep.)

13. Toxicokinetic-toxicodynamic effect models
internal concentration
damage
effect model
Toxicokinetics
Toxicodynamics
scaled internal concentration x
Physiological modes of action
Assimilation
Maintenance costs
Cost for structure
Cost for reproduction
Hazard during oogenesis
GUTS scheme modified from: Jager et al. (2011) ES&T 45, 2529–2540

14. Lethal effects Mortality Population dynamics Population size [#]
Survival [-]
Population size [#]
Concentration [µg/L]
Time [days]
Time [days]
Model prediction (minimum, mean, maximum)
Effect data
Range control data
Exposure

15. Internal concentration
Bioaccumulation
Bioaccumulation
Population dynamics
Internal concentration
[dpm/g]
Population size [#]
Concentration [µg/L]
Time [h]
Time [days]
Model prediction size scaling
Model prediction NO size scaling
Effect data
Range control data
Exposure
Gergs et al. (2016) Environmental Science and Technology 50, 6017−6024

16. Effect on reproduction
Sublethal effect
Effect on reproduction
Population dynamics
85µg/L
Cummulative offspring [#]
Population size [#]
Time [days]
Time [days]
Model prediction (minimum, mean, maximum)
Data
Control condition
Gergs et al. (in prep.)

17. Predatory aquatic insect
10 m

18. Conclusion DEB models allow for the standardized development of IBMs
This facilitates the analysis of life history contributions to population dynamics across species and ecological systems
When combined with process based effect models, the DEB integration with IBMs enable a straightforward propagation of population and community level effects from individual level toxicity testing

19. Thank you for your attention
ModNanoTox funded by the European Union (project no )
Long-range Research Initiative (project no. ECO28)