1. A dynamic stochastic food web model for the Barents Sea Benjamin Planque and Ulf Lindstrøm

2. A Dynamic Stochastic Food Web model for the Barents Sea

3. Food Web Stochastic A dynamic stochastic food web model ? ? ? ? ? ? ? ? ?

4. A Dynamic Stochastic Food Web model for the Barents Sea Stochasticity in prey-predator functional relationships? Prey consumption (g/day) Prey biomass (g/nm2) Edda Johannesen. Pers. com.

5. A Dynamic Stochastic Food Web model for the Barents Sea Food Web Stochastic Constrained –Mass Balanced –Satiety and inertia A dynamic stochastic food web model ? ? ? ? ? ? ? ? ? Mullon et al. 2009. A minimal model of the variability of marine ecosystems. Fish and Fisheries, 10: 115-131.

6. A Dynamic Stochastic Food Web model for the Barents Sea Model Principles: Mass-balance Sp 1Sp 2 Import Trophic flowExport Metabolic losses Other losses

7. A Dynamic Stochastic Food Web model for the Barents Sea Model Principles 2. Mass-balance Sp 1Sp 2 Import Trophic flowExport Metabolic losses Other losses I1I1 F 1,2 E2E2 B1B1 B2B2 (1-γ 1 ) (1-γ 2 ) (1-EE 1 ) (1-EE 2 ) F 2,2

8. A Dynamic Stochastic Food Web model for the Barents Sea Satiety Inertia Model Principles: Additional Constraints time abundance Too high Too low

9. A Dynamic Stochastic Food Web model for the Barents Sea 6 trophospecies 12 fluxes 1 import Initial biomasse 4 coeficients For each species The minimal Barents Sea model Cop. Euph. Phytopl. Cod Minke whales Capelin

10. A Dynamic Stochastic Food Web model for the Barents Sea Results 1. Diet fractions

11. A Dynamic Stochastic Food Web model for the Barents Sea Results 2 trophic functional relationships

12. A Dynamic Stochastic Food Web model for the Barents Sea Results 3. Biomass time series Key graphs for the results (3 slides)

13. A Dynamic Stochastic Food Web model for the Barents Sea Johannesen et al. In prep.

14. A Dynamic Stochastic Food Web model for the Barents Sea Results 4. bottom up & top –down controls ?

15. A Dynamic Stochastic Food Web model for the Barents Sea decadal fluctuations in top-down/bottom-up control Bottom-up Top-down Johannesen et al.

16. A Dynamic Stochastic Food Web model for the Barents Sea decadal fluctuations in top-down/bottom-up control Bottom-up Top-down

17. A Dynamic Stochastic Food Web model for the Barents Sea Conclusions Stochastic model with a few constraints… Mass-balance, satiation, inertia …and few parameters EE, Metabolic efficiency, Lifespan, Satiation, import, Export Simple, Fast and Transparent Simulates realistic ecosystem features Set a reference for expected ecosystem properties under a minimal set of assumptions

18. A Dynamic Stochastic Food Web model for the Barents Sea On going work In-depth testing Spatial compartments Age-structured populations Known functional relationships

19. A Dynamic Stochastic Food Web model for the Barents Sea Challenges and future work Linear programing & random solutions Model complexity and lack of solutions Model evaluation using summary statistics Model optimisation using summary statistics Data assimilation

20. A Dynamic Stochastic Food Web model for the Barents Sea

21. The Master equation Ecotrophic efficiency Transition Matrix Import Metabolic efficiency Biomass at t-1 Influx of preys Export Outflux to predators

22. A Dynamic Stochastic Food Web model for the Barents Sea Barents Sea model coefficients Species PhytoplanktonZooplanktonEuphausiiidsCapelinCodWhales Metabolic Efficiency 1.000.360.400.210.350.002 Ecotrophic Efficiency 0.550.500.900.750.990.97 Life-span 0.020.651.003.0015.0040.00 Satiation 54.0050.0040.0020.007.0025.60