1. Globec Legacy- the SSC ideas A.Philosophy B.Body of Knowledge C.Innovative Methodologies D.Management and information transfer E.Education/Outreach

2. Philosophy Multi/interdisciplinary international collaboration Coupled models as integrative tools Mult-scale (time,space, institutional) analysis Enhanced understanding of role of higher trophic levels

3. Innovative methodologies Coupled models (trophic, scale, time) to investigate structure, function and variability Sampling and technological advances Retrospective studes of past ecosystem states Comparative approach among regions

4. Management and information transfer Policy (providing conceptual understanding of ecosystem function) Managers (providing tools to incorporate climate-driven variability) Communities (enhancing communication on global ecosystem change and marine sustainability

5. ESSAS: Ecosystem Studies of Subarctic Seas A new GLOBEC program

6. Science 304: 1463-1466 4June2004 There is no single, fully integrated model that can simulate all possible ocean ecosystem states The key steps in representing extended food webs in complex marine systems are (i) to concentrate the biological resolution, or detail of representation, in the main target species and (ii) make increasing simplifications, or decrease in resolution, with distance both up and down the trophic scale from the target species (the “rhomboid” or “middle out” approach).

7. Model Resolution-Temporal/Spatial Issues of Model Integration Bacteria Birds/mammals THE SEA Number of Species SPECIES IN THE MODEL Number of State Variables Detail of Resolution

8. Residual currents and temperature field

9. The rhomboid approach in GB GLOBEC NPZ type Copepod life cycle type Larval fish dynamics type

10. Hydrodynamic model (The Unstructured Grid Finite Volume Costal Ocean Model) Lower trophic level food web model (NPZD Model) Eulerian approach Zooplankton or fish larvae population dynamics model (Individual Based Model) Lagrange approach Modeling approach Prey Hydro- Fields Hydro- Fields Ji and Chen

11. Ammonia Silicate Small Phytoplankton Large Phytoplankton Small Zooplankton Large Zooplankton Detritus Nitrogen Detritus Silica Predation Mortality Remineralization Uptake Dissolution Fecal Mortality Grazing Mortality Nitrate Grazing Mortality Model Structure Ji, Chen and coworkers

12. Chlorophyll a (mg m -3 ) 0.10 0.32 1.00 3.16 10.00 1999 Day:73-80 1 2 1999 Day:81-881999 Day:89-96 SeaWiFS data from GOMOOS website By Dr. Andrew Thomas, UMaine

13. Day 76 Subtidal currents wind Surface 20 m 3-D Model

14. Biological Model Day 63Day 66 Day 71Day 76 Day 81Day 86 Ji, Chen and coworkers

15. Copepod life history models: biological resolution on target species

16. Population dynamics of Calanus finmarchicus Zakardjian et al. 1999: CJFAS 56:2420-32 Zakardjian et al. 2003. JGR. Vol. 108. No.C11, 8016.

17. Zakardjian et al. 2003

18. Examples of copepod models in Georges Bank GLOBEC Miller, Lynch, Carlotti, Gentleman, Lewis, 1998 –3-D finite element model and climatology –Individual based model –Growth and reproduction as f (temperature) –Supply to GB from all GoM basins and Scotian Shelf –Jordan and Georges must be restocked from upstream sources; role of local production in Wilkinson unresolved

19. Examples of copepod models in Georges Bank GLOBEC Lynch, Gentleman, McGillicuddy, Davis, 1998 – 3D finite element hydrodynamic model, mean climatological circulation –Advective- diffusive-reactive equation, stage-based development –Food limitation represented as linear decline below 150 µgC l -1 –Surface only and depth-averaged transport –Base model has low mortality and abundant food –Spatial and temporal pattersn of Calanus recruitment in first generation consistent with observations only when model included food limitation of populations in low chlorophyll GoM in late winter/early spring

20. Examples of copepod models in Georges Bank GLOBEC McGillicuddy, Lynch, Moore, Gentleman, Davis, Meise 1998 McGilluddy, Bucklin et al. papers –Adjoint data assimilation –3D finite element, climatological circulation –Assuming advective fields correct, calculate biological terms (R) that fit the observations

21. Durbin et al. 2003: Gulf of MaineRunge et al. (in prep.): Georges Bank Calanus finmarchicus: Relationship of egg production to phytoplankton biomass

23. Start x 0,y 0,z 0,t 0 Yolk ? Yolk Sac Contribution Light ? Encounter Rate Successful Pursuit Prey Biomass Encountered Next Time Step Advect, Behave x t,y t,z t,t t Metabolic Costs Reduce Prey Biomass Satiated ? Consume Prey Y Y Y N N Growth Length,Weight Larval Size Light Level Turbulence Temperature Larval Age Larval Size Larval Behavior Prey Conc Prey Type

24. Werner et al, 1996

26. Simulated larval cod growth rates (% d -1 ) on Georges Bank based on observed copepod prey concentrations Top: April, 1995 Bottom: April, 1998 (Runge et al. in prep.)

32. 3D Physical model u,v,w,Kz,T... 3D-coupled NPZD model (primary and secondary production) 3D-coupled CLCM (distribution and abundance of copepods) 3D-coupled fish larvae trophodynamic model (growth and survival of fish larvae) Environmental conditions for recruitment (Prey fields)

33. Local Growth vs Retention/Exchange Due to the circulation gyre, the residence time of water over the Bank is long relative to biological time scales so that in situ growth rather than lateral exchange is the dominant process controlling population abundance on the Bank Fine-scale horizontal exchange causes significant leakage of nutrients, plankton and fish larvae across the frontal boundaries of the Bank, thus causing a chronic input and exchange/loss of nutrients, plankton and fish larvae Secondary circulation associated with the tidal mixing fron causes a surface convergence near the well-mixed area boundary, providing a mechanism for concentrating target species in the tidal front zone. Transport towards the center of the Bank should be greatest for plankton in the upper layer of the water column in this zone, or for those species that undertake vertical migrations. Periodic vertical migration of zooplankton and juvenile fish into and out of the sheared bottom-boundary layer can lead to horizontal movement against the mean flow

34. Stratification Seasonal density stratification over the southern flank of the Bank causes prey aggregation in the pycnocline and increased survival of predator populations Differences in phytoplankton abundance and species composition mediated by differences in water column stability result in measureable differences in copepod recruitment and growth rates. This leads to greater abundances in one region over another, due solely to high growth rates in situ Turbulent mixing, generated by wind and tidal forcing, has a significant impact on rates of ingestion, respiration and predation; the processes of turbulent mixing and seasonal density stratification influence predator-prey encounter rates and thus growth and survival of individual organisms

35. Episodic gains and Exchanges/Losses The residual mean flow is important in horizontal transport of zooplankton and fish larvae onto and off of Georges Bank, thus causing major sources and sinks for Bank populations The seeding of copepod populations from the Gulf of Maine during winter has a significant impact on the level of prey biomass for larval fish during late spring and early summer. A corollary is that the population genetic makeup of the prey on Georges Bank reflects the generic makeup of the source populations Storms, especially during winter and early spring, as well as impingement of warm-core rings, can cause large exchanges/losses of zooplankton and fish larvae from Georges Bank, thus increasing the apparent mortality rate of Bank populations Population size is continuously regulated by incremental rather than episodic events, i.e. the time scale of the variability of the driving forces is of the same order as the generation time of the population.

36. Mortality Predation rather than starvation is the dominant source of mortality of fish larvae; predation rather than advective exchange is ths dominant source of mortality of copepods

37. Science 304: 1463-1466 4June2004 An important challenge in the development of a new generation of ocean basin scale models is the incorporation of uncertainty Simulations should be probabalistic rather than deterministic, such that our endemic lack of knowledge of processes and structure can be acknowledged.