1. Ecosystem composition and CO 2 flux variability Corinne Le Quéré Max-Planck-Institut für Biogeochemie, Jena, Germany now at University of East Anglia/British Antarctic Survey with : Erik T. Buitenhuis and Olivier Aumont

2. 1980-2000 5.9 3.2 0.9 1.8 Fossil fuel emissions Atmospheric increase Land sink Ocean sink CO 2 budget (PgC/y)

3. 1980-2000 100% 54% 15% (42%) 31% Fossil fuel emissions Atmospheric increase Land sink Ocean sink CO 2 budget (PgC/y)

4. Sabine et al., 2004 Anthropogenic C 60S60N depth (m) 0 55 umol/kg DOWN

5. Sabine et al., 2004; Key et al., 2004; CDIAC Total C Anthropogenic C UP DOWN 60S60N depth (m) 60S60N 0 55 1800 2400 umol/kg

6. Sabine et al., 2004; Key et al., 2004; CDIAC Total C Anthropogenic C UP DOWN 60S60N depth (m) 60S60N 1800 2400 umol/kg

7. oceanic carbon cycle Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11 45 34 physical transport 11 33 CO 2 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions 90

8. (slide from J. Sarmiento)

9. winter mixed layer depth biological export production UP DOWN Schlitzer 2001; World Ocean Atlas 2001

10. Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11 45 34 physical transport 11 33 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions UP DOWN

11. pico nano micro nano/micro meso macro Photosynth. Bacteria, N2-fixers Calcifiers, DMS-producers, autothr. dinoflagellates diatoms Ciliates, heterotr. flagellates Copepods, euphausids Salps, pteropods bacteria phyto- plankton zoo- plankton ecosystem composition

12. bacteria phyto- plankton zoo- plankton Export 11 PgC/y Respiration 34 PgC/y Primary Production 45 PgC/y

13. NPZD model Phyto PO 4 DOCZoo POC export CO 2 flux

14. Geider et al., 1997

15. Aumont et al., 2003 PISCES model (NNNPPZZDDD) CO 2 flux big

16. can we constrain complex ecosystem models?

17. yes

18. Ocean Physical Model: OPA General Circulation model (Madec et al. 2001) NCEP daily forcing 0.5-1.5 o x2 o resolution 10 vertical levels in top 100 m (30 total) Thermodynamic Sea Ice model (Louvain La Neuve, Fichefet et al.) Nutrients restored under the Mixed layer (50<mld<100)

19. Buitenhuis et al., in prep.; Hirst and Kiorboe 2002; Ikeda 2001; Hirst and Bunker 2003 chl T growth T T mortality growth respiration Meso zooplankton rates (d -1 ) 1.43.0 0.6 2.5 PISCES-T model

20. can we evaluate complex ecosystem models?

21. yes

22. PISCES PISCES-T Observations (SeaWiFS) Surface chla (mgChl/m 3 )

23. PISCES PISCES-T from observations (Schlitzer 2001) export of C (mol/m 2 /y)

24. PISCES PISCES-T Observations (WOA, FSU, CPR) Meso-zooplankton (uM)

25. PISCES Interannual chla variability (mgChl/m3) PISCES-T Observations (SeaWiFS) 0.1

26. PISCES Interannual chla variability (percent) PISCES-T Observations (SeaWiFS) 40 20 60

27. what do complex ecosystem models bring?

28. freedom

29. NPZD DGOM Interannual chla variability (mgChl/m3) PISCES-T Observations (SeaWiFS) Calcifiers PO 4 Fe PO 4 DOCZoo POC export

30. Buitenhuis et al., in prep. Dynamic Green Ocean Model (NNNPPPZZDDD) CO 2 flux Calcifiers PO 4 Fe big

31. NPZD DGOM Surface chla (mgChl/m3) PISCES-T Observations (SeaWiFS)

32. NPZD DGOM Interannual chla variability (mgChl/m3) PISCES-T Observations (SeaWiFS)

33. NPZD DGOM Interannual chla variability (percent) PISCES-T Observations (SeaWiFS)

34. NPZD DGOM Surface chla (mgChl/m3) PISCES-T Observations (SeaWiFS) mean Interannual standard deviation 0.6 0.3

35. Log (meso-zoo/chl) Log (chl) NPZD PISCES-T Observations DGOM

36. can complex ecosystem models help our understanding?

37. can complex ecosystem models bring new information?

38. does it matter for CO 2 fluxes?

39. CO 2 sink (PgC/y) Export (PgC/y) 4 10 14 0

40. oceanic carbon cycle Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11 45 34 physical transport 11 33 CO 2 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions 90

41. oceanic carbon cycle Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11 45 34 physical transport 11 33 CO 2 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions 901.8

42. oceanic carbon cycle Silicifi ers N 2 fixers DMS producer s Calcifiers Nano phytoplankt on Fe NO 3 SiSi CaCO 3 DM S PO4PO4 NH 4 DOM biological activity 11-1 45 34+1 physical transport 11 33 CO 2 CO 2 + H 2 O + CO 2- 3 2HCO - 3 chemical reactions 901.8 – 0.8

43. 1980-2000 100% 54% 15% (42%) 31% Fossil fuel emissions Atmospheric increase Land sink Ocean sink CO 2 budget (PgC/y)

44. conclusions simple ecosystem models are too tightly linked to ocean physics but easy to use complex ecosystem models are difficult to parameterize but add degrees of freedom both are needed

45. related posters Thursday: Leticia Cotrim da Cunha, Impact of river sources of P, Si and Fe on coastal biogeochemistry Friday: Manfredi Manizza, Bio-optical impact of phytoplankton on ocean physics and air-sea fluxes

46. 71147 2350 Standard deviation in winter MLD Observations (WOA 2001) OPA model

47. PISCES PISCES-T observations (WOA, FSU, CPR) Log (meso-zoo/chl) Log (chl)

48. 240, 1185, 35525 total C latitude 60S60N depth (m) 2000 2400 umol/kg 500 winter mixed layer depth

49. CO 2 variability (Pg C/y) MIT model Hamburg model OPA model (Peylin, Bousquet, Le Quéré et al., submitted)

50. northern sub-tropics (Peylin, Bousquet, Le Quéré et al., submitted) CO 2 variability (mol/m 2 /y) MIT model OPA model observations