Partitioning Forest Carbon Fluxes with Over- and Understory Eddy-Covariance

1. Partitioning Forest Carbon Fluxes with Over- and Understory Eddy-Covariance Laurent Misson*; Baldocchi DD; Black TA; Blanken PD; Brunet Y; Curiel Yuste J; Dorsey JR; Falk M; Granier A; Irvine MR; Jarosz N; Lamaud E; Launiainen S; Law BE; Longdoz B; Loustau D; McKay M; Paw U KT; Vesala T; Vickers D; Wilson KB; Goldstein AH * University of California, Berkeleyand soon at CNRS, MontpellierFunded by: Kearney Foundation of Soil Science, UC Agricultural Experiment Station, US Department of Energy (NIGEC) 

2. Most forests are vertically complex Overstory Pinus ponderosa Ceanothus cordulatus Understory Soil

3. Most forests are vertically complex Photosynthesis CO2 CO2 Overstory Pinus ponderosa CO2 CO2 Ceanothus cordulatus Respiration Understory Soil

4. Photosynthesis CO2 CO2 Questions 1/ how canopy density influences the coupling between overstory and understory meteo? CO2 CO2 Respiration

5. Photosynthesis CO2 CO2 Questions 1/ how canopy density influences the coupling between overstory and understory meteo? CO2 CO2 2/ how different forest types, structures, and climates influence CO2 flux partitioning? Respiration

6. Photosynthesis CO2 CO2 Questions 1/ how canopy density influences the coupling between overstory and understory meteo? CO2 CO2 2/ how different forest types, structures, and climates influence CO2 flux partitioning? Respiration 3/ what factors control understory CO2 fluxes for these different forests?

7. Synthesis Based on FLUXNET Data Walker Branch Hyytiala Wind River Blodgett Jackpine Le Bray Metolius Hesse Aspen Tonzi

8. 10 Sites • 6 evergreen / 4 deciduous • 3 boreal, 4 temperate, 3 (semi)-arid • LAI overstory [ 1 - 9.0 ] m2 m-2 • LAIunderstory [ 0 - 3.2 ] m2 m-2

9. CO2 CO2 10 Sites • 6 evergreen / 4 deciduous • 3 boreal, 4 temperate, 3 (semi)-arid • LAI overstory [ 1 - 9.0 ] m2 m-2 • LAIunderstory [ 0 - 3.2 ] m2 m-2 Methodology • Aubinet et al. (2000) and Baldocchi et al. (2001) • 1 year of summertime data at each site • NEE above includes storage term (not below) • GPP and respiration were separated using Q10

10. Results 1/ Micrometeorology 2/ Flux partitionning 3/ Controlling factors

11. How canopy density influences temperature stratification ?

12. How canopy density influences temperature stratification ? Tover – Tunder DAY LAI Tunder > Tover for low LAI

13. How canopy density influences temperature stratification ? Tover – Tunder DAY LAI Tunder > Tover for low LAI Open forest: good mixing Closed forest: weaker mixing

14. How canopy density influences temperature stratification ? Tover – Tunder DAY Tover – Tunder NIGHT LAI LAI Tunder > Tover for low LAI Open forest: good mixing Closed forest: weaker mixing Tunder < Tover for low LAI

15. How canopy density influences temperature stratification ? Tover – Tunder DAY Tover – Tunder NIGHT LAI LAI Tunder > Tover for low LAI Open forest: good mixing Closed forest: weaker mixing Tunder < Tover for low LAI Open forest: strong inversion Closed forest: good mixing

16. How canopy density influences wind deflection ? Wind Dirover – Wind Dirunder (º) LAI

17. How canopy density influences wind deflection ? Wind Dirover – Wind Dirunder (º) LAI Wind is strongly defleted in dense forests probably because of stronger drag force

18. How canopy density influences wind deflection ? Wind Dirover – Wind Dirunder (º) LAI Wind is strongly defleted in dense forests probably because of stronger drag force Overstory and understory flux footpint may be different

19. How much is the understory contribution to whole ecosystem fluxes ? Understory Contribution in %

20. How much is the understory contribution to whole ecosystem fluxes ? (%) R GPP Understory Contribution

21. How much is the understory contribution to whole ecosystem fluxes ? (%) R GPP • Evergreen = Deciduous (14%) • Semi-Arid > Temperate > Boreal Understory Contribution 20% 13% 6%

22. How much is the understory contribution to whole ecosystem fluxes ? • Deciduous (62%) > Evergreen (49%) (%) Soil C:N = 16 Soil C:N = 31 R GPP • Evergreen = Deciduous (14%) • Semi-Arid > Temperate > Boreal Understory Contribution 20% 13% 6%

23. How much is the understory contribution to whole ecosystem fluxes ? • Deciduous (62%) > Evergreen (49%) (%) Soil C:N = 16 Soil C:N = 31 R • Semi-Arid < Temperate = Boreal GPP 44% 60% 60% • Evergreen = Deciduous (14%) • Semi-Arid > Temperate > Boreal Understory Contribution 20% 13% 6%

24. What controls understory respiration fluxes across different forests ?

25. What controls understory respiration fluxes across different forests ? Mean summertime respiration flux (µmol m-2 s-1) NS Soil temperature (ºC)

26. Normalized flux for soil temperature and soil moisture

27. Normalized flux for soil temperature and soil moisture FluxT,SM R2 = 0.64 Soil temperature (ºC)

28. Normalized flux for soil temperature and soil moisture FluxT,SM FluxT,SM R2 = 0.64 R2 = 0.82 Soil temperature (ºC) Soil C (g C m-2)

29. Normalized flux for soil temperature and soil moisture FluxT,SM FluxT,SM R2 = 0.64 R2 = 0.82 Soil temperature (ºC) Soil C (g C m-2) Uncorrelated

30. Normalized flux for soil temperature and soil moisture FluxT,SM FluxT,SM R2 = 0.64 R2 = 0.82 Soil temperature (ºC) Soil C (g C m-2) Uncorrelated Partial evidence that respiration acclimates to temperature Zogg et al. 1997, Zhang et al. 2005, Atkin et al. 2005

31. Normalized flux for soil temperature and soil carbon FluxT,C R2 = 0.67 Relative soil moisture

32. Normalized flux for soil temperature and soil carbon FluxT,C R2 = 0.67 Relative soil moisture Microbial metabolic activity limited by soil moisture

33. Mean summertime respiration flux (µmol m-2 s-1) R2 = 0.78 Slope = 0.23 GPP ecosystem (µmol m-2 s-1)

34. Mean summertime respiration flux (µmol m-2 s-1) R2 = 0.78 Slope = 0.23 GPP ecosystem (µmol m-2 s-1) Understory respiration is linked to gross primary productivity

35. Conclusion

36. Conclusion • Eddy-Covariance method: able to measure understory fluxes for a wide range of forest types, structures and climates

37. Conclusion • Eddy-Covariance method: able to measure understory fluxes for a wide range of forest types, structures and climates • Problems: open forests  night inversion • dense forests  different flux footprint

38. Conclusion • Eddy-Covariance method: able to measure understory fluxes for a wide range of forest types, structures and climates • Problems: open forests  night inversion • dense forests  different flux footprint • Understory can contribute significantly to whole ecosystem CO2 sinks and sources, but variations across sites are important

39. Conclusion • Eddy-Covariance method: able to measure understory fluxes for a wide range of forest types, structures and climates • Problems: open forests  night inversion • dense forests  different flux footprint • Understory can contribute significantly to whole ecosystem CO2 sinks and sources, but variations across sites are important • Understory LAI and light penetration are important factors influencing understory GPP

40. Conclusion • Eddy-Covariance method: able to measure understory fluxes for a wide range of forest types, structures and climates • Problems: open forests  night inversion • dense forests  different flux footprint • Understory can contribute significantly to whole ecosystem CO2 sinks and sources, but variations across sites are important • Understory LAI and light penetration are important factors influencing understory GPP • Substrate availability and quality, soil temperature and soil moisture are important factors for understory respiration