Dynamic energy budgets in individual based population models Cross species test and application

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-basedpopulationmodel (IBM) Individual organism Individual organism • Individual organism • life history traits • behaviours • food conditions • toxic exposure

4. newborn Feeding embryo development Ageing brood size maximal age ? yes  no growth born juveniles no Adult? Birthing? no yes yes juvenile development Conceptual illustration of the IBM approach Preuss et al. (2009) Ecological Modelling 220: 310-329

5. Comparabilityof IBMs Strauss et al. (2016) EcologicalModelling 321: 84-97 Kulkarni et al. (2014) Chemosphere 112: 340–347

6. Dynamic energy budgets in IBMs Abundance [#] Time [d] Stage dependent mortality Figure: Martin et al (2013) American Naturalist 181: 506-519

7. Size dependentstarvationresistance Notonecta maculata Daphnia magna 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 parametrizationforDaphnia magna Filtration rate Size dependent starvation Growth Reproduction Gergs et al. (2014) PlosOne 9: e91503

9. Emerging populationdynamics mean, range

10. Emerging populationdynamics data model

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

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

13. Toxicokinetic-toxicodynamic effectmodels Toxicodynamics Toxicokinetics scaled internal concentration x internal concentration damage effect model • Physiological modes ofaction • Assimilation • Maintenance costs • Cost forstructure • Cost for reproduction • Hazardduringoogenesis GUTS schememodifiedfrom: Jager et al. (2011) ES&T 45, 2529–2540

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

15. Bioaccumulation Bioaccumulation Population dynamics Internal concentration [dpm/g] Population size [#] Concentration [µg/L] Time [days] Time [h] 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. Sublethaleffect 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. Predatoryaquaticinsect 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 Long-range Research Initiative (project no. ECO28) ModNanoTox funded by the European Union (project no. 266712)