1. OUEVRE (Per Jonsson, revisions by F. Werner

2. What have we learned? What models (or other approaches to synthesis) exist or are needed and of what type? How does climate influence variability of recruitment in these systems?

3. 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

4. Nested 3D physical models, linked to climate models u,v,w,Kz,T... 3D-coupled NPZD model (primary and secondary production) 3D-coupled ZLCM (distribution and abundance of individual zooplankton species) 3D-coupled fish larvae trophodynamic model (growth and survival of fish larvae) Environmental conditions for recruitment (Prey fields)

5. What are the critical characteristics that make these species useful for pan regional comparisons? Restate the question: What evidence do we have that knowledge of the life history characteristics and physiological attributes of the individual species is essential to understanding the ecosystem dynamics? Consensus is that detailed knowledge of the individual life histories of zooplankton is important

6. Egg survival 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Egg production 0 10 20 30 40 50 60 Copepod Life History Trade-offs Pseudocalanus. Calanus finmarchicus

7. The species question continued We have approaches and detailed knowledge to answer questions of climate forcing on recruitment of the target species During synthesis, we need to identify how our knowledge can be applied to the broad question of climate forcing on ecosystem and function. Do the target species responses representative of ecosystem structure and function. Will inclusion of other key species now identified be sufficient? How much simplification can we re-introduce?

8. Data gaps Identification of key species not originally targeted (e.g. pteropods) Microbial components for NPZ Nutrient and phytoplankton data for model validation

9. The overarching question Climate forcing mechanisms: local vs remote - Freshwater effects on density driven circulation and stratification - Winds Model approaches: common technical issues linking the coupled models Different life histories- responses to forcing: compare and contrast among regions Similarities in geomorphology; eg. GB and Antarctica translate into similarities in forcing and ecosystem responses?

11. The structural components required for a basin-scale study focused on planktivorus fish. Wiebe et al. BASIN proposal (RARGOM Modeling Theme Session)

12. Biological challenges 1.Growth and reproduction dependency on food availability 2.Understanding the processes determining entry and exit from fall-winter dormancy 3.Mortality rates 4.Vertical distribution of life stages

13. Durbin et al. 2003: Gulf of MaineRunge et al. (2006): Georges Bank Calanus finmarchicus: Relationship of egg production to phytoplankton biomass Biological challenges…1 Description of linkage between primary production and copepod growth and reproduction

14. Linking the Coastal Ocean Ecosystem to Fisheries in the Gulf of Maine: Perspectives of an Oceanographer Jeffrey A. Runge Institute for the Study of Earth, Oceans and Space University of New Hampshire (this is no small topic)

15. E.O. Wilson. Back from Chaos. The Atlantic Monthly May, 1998 Consilience: The linking of facts and fact- based theory across disciplines to create a common groundwork of explanation.

16. Coastal ocean observing in the GoM SST Surface chlorophyll S, T, currents,wind, chl.a CPR Zooplankton (NOAA) Remote sensing (Univ. Maine) GoMOOS buoys Chl a time series (2001-04) R. Morrison UNH COOA Pershing et al. 2005 Atlantic herring coastal stock complex: 1960-2000 B. Overholtz,2000

17. Platt, Fuentes-Yaco and Frank, 2003) Haddock Scotian Shelf

18. Sustainable fisheries in a period of global change management policy precautionary principleIncluding oceanography and earth system science the fishing communities Modeling integrates knowledge across scientific disciplines Simulations provide predictions that can be tested against data The computer as a medium for communicating to non-experts and experts the complex synthesis of system knowledge (Adapted from E.O. Wilson, 1998)

19. A general set of NPZ model equations

20. Nitrates Ammonium Large phytoplankton > 5 µm Small phytoplankton < 5 µm Mesozooplankton (200-2000 µm) Microzooplankton (20-200 µm) PON: Particulate Organic Nitrogen DON: Dissolved Organic Nitrogen An NNPPZZDD coupled model in the Gulf of St. Lawrence Lefouest et al., AGU 2003

21. Prognostic hindcast solution for domain-averaged salinity & temperature profiles, and sea ice volume Salinity Observation Model Time (years) Sea ice volume Temperature sea-ice – ocean circulation model Saucier et al., in prep

22. Le Fouest V, Zakardjian B, Saucier FJ, Starr M (2005) Chifflet M, Le Fouest V, Starr M, Saucier F, Zakardjian B (in prep)

23. 199719981999 Annual integrated production - gC/m 2 /an Mean winter nitrate concentration (mmolN m -2 ) coupled ecosystem – sea-ice ocean circulation model Interannual variability in primary production Chifflet et al., in prep

24. coupled ecosystem – sea-ice ocean circulation model Le Fouest et al., submitted Comparisons to satellite-derived fields: St. Lawrence discharge effect model satellite AVHRR SeaWIFS SST Chl a k CDOM vs Chl a 3rd – 6th of August 1998

25. Towards a linked model system for coastal waters of the Northwest Atlantic: Examples of coupled physical-biological models Copepod life history model structure Example: Zakardjian et al. (2003) Biological challenges

26. Northeast Consortium PULSE (www.pulse.unh.edu)

27. Calanus finmarchicus and map showing its subarctic distribution

28. An example of a copepod life history model: Zakardjian et al. (2003)  Development rate: Taux de mue dépendant pour chaque stade de la température  Mortality rate: Taux de mortalité spécifique pour chaque stade et variant de façon saisonnière  Reproductive rates: Taux de ponte variant de façon saisonnière  Overwintering strategy: Fonction de diapause variant de façon saisonnière  Vertical distribution: Comportement natatoire spécifique par stade de développement

29. Population dynamics of Calanus finmarchicus Zakardjian et al. 1999: CJFAS 56:2420-32 Zakardjian et al. 2003 JGR.

31. Flux computations

32. C. finmarchicus: Lower St. Lawrence Estuary 1991-1997 Jul-Sept. Runge, Plourde, Joly, in prep.

33. 2003

34. Georges Bank Broadscale cruises 1995-1999 Ohman et al., 2002 N=2555 N=2786

35. U.S. GLOBEC Georges Bank Broadscale Survey Cruises 0 20,000 40,000 60,000 80,000 100,000 01234567 Month Egg loss rate ( No. m-2 d-1 ) C. finmarchicus egg loss rate 5-yr mean 0 20,000 40,000 60,000 JanuaryFebMarchAprilMayJune Month Eggs eaten m-2 d-1 C.typicus FC.hamatus FT. longicornis M. lucens FC.finmarchicus C4C.finmarchicus C5 C. finmarchicus Fmedusaehydroids CalanusF Centropages typicusF Centropages hamatusF Cumulative CalanusC5 medusae hydroids Calanus C4 Metridia F TemoraF ` Predation potential: 5 yr mean

36. Towards a linked model system for coastal waters of the Northwest Atlantic: Examples of coupled physical-biological models Early life stages of fish Trophodynamics Transport: role of variabilty in circulation

37. 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 Werner, Lough, Buckley and colleagues

38. 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.)

39. NAMA Inshore Fisheries Conservation and Stewardship Plan (2003) E. P. Ames, 2004. Fisheries 29: 10-28

40. May June Oct-Dec summer B. Ueberschaer Adults Spawning Early Fall Cod Herring NAMA-UNH Western Gulf of Maine Inshore Fisheries- Ecosystems Project

41. March 95March 99 Huret M, Chen C

42. May 95May 99 Huret M, Chen C

43. May 95May 99 Huret M, Chen C, Runge J unpubl

45. 199719981999 Spring Fall Observed vs simulated chlorophyll a biomass predicted observed coupled ecosystem – sea-ice ocean circulation model Chifflet et al., in prep

46. 199719981999 Spring Fall Observed vs simulated nitrate concentration predicted observed coupled ecosystem – sea-ice ocean circulation model Chifflet et al., in prep

47. 1995 surface layermid-layerbottom layer