1. Arctic Operational Oceanography at IMR Einar Svendsen Arctic GOOS planning meeting, 12-13 September 2006 at NERSC, Bergen

2. An approach to marine ecosystem research and management advice (with respect to science) is: To consider the most important driving forces on, and the processes within the ecosystems Driving forces: Climate-physics (directly on all trophic levels and indirectly bottom-up through the lower trophic levels Fisherman-fisheries management (top-down) Fertilization? Pollution? Introduction of new species? Habitat disturbance?

3. Climate-physics Fishing Climate-physics

4. Climate

5. Svalbard N o r w a y Russia Greenland The Nordic seas The Barents sea GB Iceland Observations (from ships satellites and buoys) are important for validation of and assimilation into the models

7. Hindcast (50 year), nowcast and forecast (week (or 100 years) ) of: Relevant physics - Circulation, temperature, salinity, turbulence Phytoplankton - Concentration of functional groups (or specific (harmful) species), nutrients, detritus, oxygen, sedimentation, light Zooplankton - Individual species (or functional group(s)? (IBM or Eulerian) Fish larvae - growth and distribution (and mortality?) (IBM) Fish migration - growth and distribution (overlap between species)

8. The operational needs From the above variables, only physics is operationally available in hindcast, nowcast and forecast (and still the quality can be questioned, partly due to lack of resolution due to lack of computer resources. Phytoplankton is starting to be operational (eg. MONCOZE, Liverpool Bay….) We need zooplankton to realistically model larval growth and planktivour fish migration, because this we need to more realistically address the key challenges for the fisheries research, namely quantifying and predicting: Recruitment, growth, mortality and distribution Since we (mathematically) do not know all the processes leading up to these states/processes, we need to make statistically shortcuts between smart INDICATORS (derived from our modelled state variables) and recruitment, growth, mortality and distribution, including observations where necessary. NB! Overlap between pray and predators determines natural motality

9. Ideas for new operational indicators - Position of fronts - Extent and area of melting sea ice (if relevant) - Area and volume of specific water masses - Upwelling indexes - Currents, temperature and turbulence - Particle and tracer distributions from given sites (spawning, oil production….) - Fluxes of water masses and nutrients (though given sections) - Timing (of peak spring bloom) and strength of primary prod. - Light in water column - Transport, growth and distribution of zoo-plankton - Transport, growth and distribution of selected fish larvae - Contaminant exposure on plankton and benthic ecosystems - Sedimentation (resuspension) - Overlap between species (prey and predators)

10. Predicting horse mackerel fishing from modeled volume transport ( Catch ) Catch

11. 2005 was extremely warm

12. Results: Monthly mean SST Observed Climatology March (Pathfinder) Model results March, 2004

13. 50 year simulations demonstrate large decadal variability High NAO (1990-1995) Low NAO (1963-1966) We need to be continuously updated on the status

14. Variability in BSO-inflow Anomalies from 1981-2000 average

15. Trophic transfer Spawning and nursery grounds Svalbard Norway Russia

18. Cod recruitment, volume transport and prim.prod. Svendsen (2006)

19. Cod recruitment (3y) prediction and ICES estimates

20. Priorities (conclusion) Finalize and analyse long term simulations (50 year) of physics and phytoplankton globally, regionally and locally. Easy access to results Develop and prepare operational systems ala MONCOZE-MONBASE Implimentert realistic zooplankton modelling operational and long term simulations Improve and implement fish growth and migration models to explain the dynamics in natural mortality Couple models for pollution and biology to estimate contaminant dozes on “stocks” Build systems where “bottom-up ecosystem approach” can be useful for management advice on the marine ecosystems Simulate potential ecosystem effects from climate change

21. Climate