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Ecosystem composition and CO 2 flux variability

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. CO 2 budget (PgC/y). 1980-2000. 5.9. Fossil fuel emissions. 3.2.

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Ecosystem composition and CO 2 flux variability

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  1. Ecosystem composition and CO2 flux variability Corinne Le Quéré Max-Planck-Institut für Biogeochemie, Jena, Germanynow at University of East Anglia/British Antarctic Survey with: Erik T. Buitenhuis and Olivier Aumont

  2. CO2 budget (PgC/y) 1980-2000 5.9 Fossil fuel emissions 3.2 Atmospheric increase 0.9 Land sink 1.8 Ocean sink

  3. CO2 budget (PgC/y) 1980-2000 100% Fossil fuel emissions 54% Atmospheric increase 15% (42%) Land sink 31% Ocean sink

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

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

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

  7. biological activity 45 Si PO4 NO3 NH4 Fe DMS 34 CO2 + H2O + CO2-3 2HCO-3 Calcifiers Nano phytoplankton DMS producers N2 fixers Silicifiers CaCO3 DOM 33 11 11 physical transport oceanic carbon cycle 90 CO2 chemical reactions

  8. C L I M A T E R E S P O NS E O F OCE A N I C U PT A KE S a r mi e nto M ate a r a n d J o os e t a l. et a l. (1 9 9 8 ) H i r s t (1 9 9 9 ) ( 19 9 9 ) T i me S p a n 19 9 0 - 20 6 5 18 5 0 - 210 0 17 6 5 - 210 0 W a rm i n g E f f e ct -11 % -1 2 % -1 3 % C i rc u la t io n E ff ect - 2 2% -1 0 % - 3 % B iolo gi cal E ff ect + 2 4 % + 8 % + 6 % T O TA L - 9 % -1 4 % -1 0 % (slide from J. Sarmiento)

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

  10. UP biological activity 45 Si PO4 NO3 NH4 Fe DMS 34 CO2 + H2O + CO2-3 2HCO-3 Calcifiers Nano phytoplankton DMS producers N2 fixers Silicifiers CaCO3 DOM 33 11 11 physical transport DOWN chemical reactions

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

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

  13. NPZD model CO2 flux PO4 Phyto DOC Zoo POC export

  14. Geider et al., 1997

  15. PISCES model (NNNPPZZDDD) CO2 flux big Aumont et al., 2003

  16. can we constrain complex ecosystem models?

  17. yes

  18. Ocean Physical Model: • OPA General Circulation model (Madec et al. 2001) • NCEP daily forcing • 0.5-1.5ox2o 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. Meso zooplankton rates (d-1) PISCES-T model 1.4 3.0 growth growth chl T 0.6 2.5 mortality respiration T T Buitenhuis et al., in prep.; Hirst and Kiorboe 2002; Ikeda 2001; Hirst and Bunker 2003

  20. can we evaluate complex ecosystem models?

  21. yes

  22. Surface chla (mgChl/m3) PISCES Observations (SeaWiFS) PISCES-T

  23. export of C (mol/m2/y) PISCES from observations (Schlitzer 2001) PISCES-T

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

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

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

  27. what do complex ecosystem models bring?

  28. freedom

  29. Interannual chla variability (mgChl/m3) PO4 Fe PO4 Calcifiers DOC Zoo POC export Observations (SeaWiFS) NPZD PISCES-T DGOM

  30. Fe PO4 Calcifiers Dynamic Green Ocean Model (NNNPPPZZDDD) CO2 flux big Buitenhuis et al., in prep.

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

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

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

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

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

  36. can complex ecosystem models help our understanding?

  37. can complex ecosystem models bring new information?

  38. does it matter for CO2 fluxes?

  39. CO2 sink (PgC/y) 0 4 10 Export (PgC/y) 14

  40. biological activity 45 Si PO4 NO3 NH4 Fe DMS 34 CO2 + H2O + CO2-3 2HCO-3 Calcifiers Nano phytoplankton DMS producers N2 fixers Silicifiers CaCO3 DOM 33 11 11 physical transport oceanic carbon cycle 90 CO2 chemical reactions

  41. CO2 + H2O + CO2-3 2HCO-3 oceanic carbon cycle 90 1.8 CO2 biological activity chemical reactions 45 Si PO4 NO3 NH4 Fe DMS 34 Calcifiers Nano phytoplankton DMS producers N2 fixers Silicifiers CaCO3 DOM 33 11 11 physical transport

  42. CO2 + H2O + CO2-3 2HCO-3 oceanic carbon cycle CO2 90 1.8 – 0.8 biological activity chemical reactions 45 Si PO4 NO3 NH4 Fe DMS 34+1 Calcifiers Nano phytoplankton DMS producers N2 fixers Silicifiers CaCO3 DOM 33 11 11-1 physical transport

  43. CO2 budget (PgC/y) 1980-2000 100% Fossil fuel emissions 54% Atmospheric increase 15% (42%) Land sink 31% Ocean sink

  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. 71 147 23 50 Standard deviation in winter MLD Observations (WOA 2001) OPA model

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

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

  49. MIT model CO2 variability (Pg C/y) OPA model Hamburg model (Peylin, Bousquet, Le Quéré et al., submitted)

  50. northern sub-tropics MIT model OPA model CO2 variability (mol/m2/y) observations (Peylin, Bousquet, Le Quéré et al., submitted)

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