1. Modelling Vertebrates Beth Fulton 2012

2. End to End Model

3. Difference equation time step assumed (agreed upon) Differential equation instantaneous (or really tiny time slices) D.E.

4. Life history ReprodGrowthMetab.MoveAgingMortality

5. Biomass Aggregate Biomass Recruitment, Migration & Growth Mortality & metabolism e.g. Ecopath

6. Numbers Abundance Recruitment & Migration Mortality

7. Age Structure Aging & Growth Recruitment Mortality Stock assessments

8. Can be simple (just age structure) Can be complex (spatial, genetic stocks etc) Age Structure

9. Disease/Oxygen limitation Vertebrate Reserve Structure Nutrients Detritus Pred C Pred B Pred A Prey C Prey B Prey A Prey availability Gape limitation Reproduction Age structure & Condition

10. Basic form: Senescence and disease considered Age structured (age phases; distribution within phases) computationally efficient allows ontogenetic shifts, recovery delay, overfishing effects Gape limited & can starve (condition impacts survival and reproduction) oxygen deficient, starvation or quadratic Atlantis

11. Transition matrices Explicit formulations (density & food dependent; sedentary; forced; mixed) Weighting for seasonal migrations (can migrate in & out of model domain) Smooth and interpolate old to new based on cruising speed Kalman filter Vertical movements Movement

12. Stock-recruitment relationships Adults Recruits Beverton Holt Fixed # offspring / adult Ricker Reproduction Others = lognormal, plankton-based…

13. Stock-recruitment relationships Based on parental condition and environmental characteristics (e.g. temp or salinity) Live birth and parental care Reproduction

14. Maternal Care

15. Stock-recruitment relationships Based on parental condition and environmental characteristics (e.g. temp or salinity) Live birth and maternal care Young of year recruits no explicit larval phase (miss predator-prey switch unless use plankton-based recruitment) Explicit larvae (advection or connectivity matrices) Reproduction

16. Forced distributions Movement

17. Forced (seasonal) distributions Density or forage dependent Sedentary Mixed Seasonal migrations must intersect with prey or starve spawn near rearing habitat or juveniles eaten Movement

18. Forced (seasonal) distributions Density or forage dependent Sedentary Mixed Seasonal migrations must intersect with prey or starve spawn near rearing habitat or juveniles eaten Include if needed to represent ecology of interest vertical (access prey, benthopelagic coupling), seasonal (within model), migration (out of domain) Movement

19. Non-zero values = commitment interaction that seems unimportant may become critical Connections can have non-symmetric impacts Use local (cogener) data preferentially Size-relationships predator-prey are consistent across systems Stomach content problems (soft bodies digest rapidly, patchy data, too few links can impact predictions) Isotopes Diets

20. Diet Time Series

21. e.g. seabirds (ontogeny, seasonal migrations) Quillfeldt et al 2010 Diet & Migration

22. Bowhead whales – Northern Pacific Hobson et al 2010 Diet & Migration

23. Ontogenetic shifts Flexible in space and time Model vs Obs

24. Modelling theory System dynamics Impacts of perturbation Form of effective management vision statements vs realised outcomes effective monitoring ecosystem-based management multiple use management Questions tackled

25. Atlantis – What, How, Why small pelagics squid zooplankton baleen whales birds pelagic sharks toothed whales pelagic fish demersal fish demersal sharks infauna macrophytes filter feeders zoobenthos detritus jellies phytoplankton 1910

26. Community Structure

27. Atlantis – What, How, Why 1910

28. Atlantis – What, How, Why 2000

29. Primary Producers ZooplanktonJelliesSquidBenthos Forage Fish Demersal FishTop Predators 2 -6 Index of effect size Temperature + Acidification Griffiths et al (in review) Antagonistic interaction Synergistic interaction All human pressures together Interacting Stressors

30. Audzjionyte et al (in review) > 20% fishing mortality per year = selecting for smaller fish FECUNDITY 10-50% 50-90% Evolution

31. Audzjionyte et al (in review) Mortality implications

32. Evolution Audzjionyte et al (in review) Biomass implications Predator-prey implications Distribution implications

33. Possible, but heterogeneity hard… better to use ABM Behaviour

34. Thank you