1. Dynamic Energy Budgets i.r.t. population effects of toxicants Tjalling Jager Dept. Theoretical Biology

2. Contents  What DEB is not …  What is DEB?  Advantages of using DEB Example life-cycle dataset Bindesbøl et al (2007) copper in Dendrobaena octaedra size, survival, cocoons over 20 weeks here, only [Cu] > 80 mg/kg

3. What DEB is not  DEB is not a population model  DEB is not needed to estimate population effects

4. DEB-less analysis conc.hatching % 8074 12079 16074 20031 80 120 160 200 050100150 0 0.2 0.4 0.6 0.8 1 time (days) fraction survival 050100150 0 5 10 15 20 25 30 35 40 cumulative reproduction time (days) 12 hatching time: 92 days

5. DEB-less analysis conc.hatching % 8074 12079 16074 20031 80 120 160 200 050100150 0 0.2 0.4 0.6 0.8 1 time (days) fraction survival 050100150 0 5 10 15 20 25 30 35 40 time (days) cumulative reproduction hatching time: 92 days

6. Intrinsic rate of increase 2-stage model splined, Euler-Lotka 6080100120140160180200 0 0.005 0.01 0.015 0.02 0.025 concentration (mg/kg soil) population growth rate (d -1 ) 12

7. What have we achieved? longer exposure time, untested concentrations, time-varying conditions, temperature, food limitation, other species, other compounds …  Integrated effects on survival and reproduction over time …  … for test concentrations and test conditions …  Can we make educated inter- and extrapolations?

8. What is DEB? Quantitative theory; ‘first principles’ time, energy and mass balance Life-cycle of the individual links levels of organisation: molecule  ecosystems Comparison of species body-size scaling relationships; e.g., metabolic rate Fundamental to biology; many practical applications (bio)production, (eco)toxicity, climate change, … Kooijman (2000) Kooijman (in press)

9. Bookkeeping rules … growth reproduction feeding maintenance maturation

10. Toxicants in DEB external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time life-history traits one-compartment model, accounting for changes in body size

11. Toxicants in DEB external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time life-history traits ingestion rate maintenance rate coeff. egg costs etc. …

12. Toxicants in DEB external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits KM-DEB (Klok et al, 1996) DEBtox (Kooijman & Bedaux, 1996) DEB3 (Jager et al, subm.)

13. Toxicants in DEB external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time DEB parameters in time DEB model DEB model life-history traits growth, time to reproduction, reproduction rate mortality etc. …

14. DEB analysis of data Simultaneous fit size and repro data MoA: decrease in ingestion rate 050100150 1 2 3 4 5 6 7 8 9 time (days) body length 80 120 160 200 050100150 0 5 10 15 20 25 30 35 40 time (days) cumulative offspring per female 80 120 160 200

15. DEB analysis of data Assume size-dependent feeding limitation (Jager et al, 2005) 80 120 160 200 80 120 160 200

16. Parameter estimates external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars to population model …

17. Population effects 6080100120140160180200 0 0.005 0.01 0.015 0.02 0.025 concentration (mg/kg soil) population growth rate (d -1 ) 2-stage model splined, Euler-Lotka DEB, Euler-Lotka no-effects

18. What’s different? effects data individuals effects data individuals population consequences population consequences model parameters model parameters extrapolated parameters extrapolated parameters DEB-less DEB

19. Educated extrapolation external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars time-varying concentrations

20. Educated extrapolation external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars less food in environment

21. 6080100120140160180200 0 0.005 0.01 0.015 0.02 0.025 concentration (mg/kg soil) population growth rate (d -1 ) Food limitation food 100% food 90%

22. Educated extrapolation external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars size-dependent feeding limitations

23. Food limitation juveniles 80 120 160 200 80 120 160 200

24. 6080100120140160180200 0 0.005 0.01 0.015 0.02 0.025 concentration (mg/kg soil) population growth rate (d -1 ) Food limitation juveniles food 100% food 90%

25. Educated extrapolation external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars other compounds (related)

26. external concentration (in time) toxico- kinetics internal concentration in time Educated extrapolation external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars other compounds (mixtures)

27. Educated extrapolation external concentration (in time) toxico- kinetics toxico- kinetics internal concentration in time metabolic processes in time DEB model DEB model life-history traits TK parstox parsDEB pars other (related) species

28. What’s the use of DEB?  In-depth interpretation of effects on individual all endpoints over time in one framework indicates experimental ‘problems’ mechanism of action of compound  DEB is essential for inter- and extrapolation e.g., extrapolation to field conditions ‘repair’ experimental artefacts  Natural link with different population approaches simple (e.g., Euler-Lotka and matrix models) more complex (e.g., IBM’s)

29. But …  Strong (but explicit) assumptions are made on metabolic organisation on mechanisms of toxicity  Elaborate DEB models require strong data growth, repro and survival over (partial) life cycle e.g., Daphnia repro protocol extended with size  Almost every analysis raises more questions difficult to perform on routine basis Interesting point raised by DEB3 … hatching time and hatchling size can be affected by stress

30. Advertisement Vacancies PhD student, Marie Curie training network (CREAM) Courses International DEB Tele Course 2011 Symposia 2nd International DEB Symposium 2011 in Lisbon More information: http://www.bio.vu.nl/thb