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

A Dynamic Stochastic Food Web model for the Barents Sea

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

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.

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 A minimal model of the variability of marine ecosystems. Fish and Fisheries, 10:

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

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

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

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

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

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

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

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

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

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.

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

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

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

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

A Dynamic Stochastic Food Web model for the Barents Sea

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

A Dynamic Stochastic Food Web model for the Barents Sea Barents Sea model coefficients Species PhytoplanktonZooplanktonEuphausiiidsCapelinCodWhales Metabolic Efficiency Ecotrophic Efficiency Life-span Satiation