1. Using a Global Flux Network—FLUXNET— to Study the Breathing of the Terrestrial Biosphere Dennis Baldocchi University of California, Berkeley BrasFlux, Santa Maria Rio Grande do Sul, Brazil Nov. 14, 2011

2. Contemporary CO 2 Record

3. Methods To Assess Terrestrial Carbon Fluxes at Landscape to Continental Scales, and Across Multiple Time Scales GCM Inversion Modeling Remote Sensing/ MODIS Eddy Flux Measurements/ FLUXNET Forest/Biomass Inventories Biogeochemical/ Ecosystem Dynamics Modeling Physiological Measurements/ Manipulation Expts.

4. remote sensing of CO 2 Temporal scale Spatial scale [km] hour day week month year decade century local 0.1 1 10 100 1000 10 000 global Continent plot/site tall tower obser- vatories Eddy covariance towers Landsurface remote sensing Developing a System that is Everywhere, All of the Time Credit: Markus Reichstein, MPI

5. Status of Global Network, 500+ Sites FLUXNET

6. FLUXNET Represents Many Climate Spaces, Well More Data and Sites in Tropical Rain Forests are Welcome!

7. Time Line of Flux Data

8. Growth in Africa, Australia and Asia, Sustenance in Brazil and Europe Decline in Canada and US Voids in India and Latin America

9. Many Towers are Not Active, nor Submitting data, circa La Thuile dataset

10. Fluxdata.org – A Common, Shared Database Individual Sites Regional Networks Flux/Met Data www.Fluxdata.org BADM Data Flux/Met Data BADM Data + Flux/Met Gap-Filled/QA/Products

11. Data processing, Value Added Products and Uncertainty Estimation Half hourly data u* threshold selection - 3/5 different methods u* filtering - 3/4 possibility Gapfilling - 2 methods Partitioning - 3 methods 3 methods, bootstraping… Also daytime, also data after low turb., … MDS and ANN Reichstein, Lasslop, van Gorsel

12. Community Building/OutReach Shared Database: www.fluxdata.org www.fluxdata.org Newsletter: FluxLetter Young Scientist Forums International Workshops Marconi, 2000 Orvieto, 2002 Lake Tahoe, 2003 Firenze, 2004 La Thuile, 2007 Asilomar, 2009 Berkeley, 2011

13. Challenges/Opportunities for Future To Sustain and Grow the Network that Asks and Answers Network-Scale Questions –To sample representative Climates and Biomes –To sample representative Disturbance Classes –Detect trends in Fluxes as Climate and Land Use Changes –Validate and Parameterize New Generation of Land Surface- Atmosphere Exchange Models –Serve as Critical Partner in Machine Learning Approaches to Flux Upscaling with Satellite Remote Sensing –Provide Ground Truth for MODIS Land Products –Provide Ground Truth for Sources/Sinks produced by global CO 2 networks and next generation CO 2 Satellite Sensors

14. Big Network Issues Facing Flux Networks in 2011 How can we Sustain the Network? How many Stations are Enough? Where do we need new Stations? How can we encourage Scientists to Participate, Submit Data and Open the Data to the Wider Science Community, with Benefits to ALL?

15. Data Sharing is a Win/Win Activity Get Access to Data from other Sites and Networks Learn more about your site though Comparisons Can Initiate, Lead or Participate on multi-site synthesis activities Data Sharing Rules Come from the Community via Bottom-Up Process –Multiple Levels of Data Availability are Provided –Proposed Projects are Vetted to Protect PIs and Reduce Duplication Future of Biogeosciences and Flux Research

16. Charge/Recommendations for BrasFlux Roving Network Calibration System Expand Suite of Sensors –Digital Camera for Phenology and LAI –Diffuse Radiation –4 Band Net Radiometers and High Quality Quantum Sensor Database, with Vetted Processing Algorithms, Qa/Qc, Comprehensive Site Documentation and Version Control

17. What Have We Learned? Time –Annual Integration –Seasonal Dynamics –Inter-Annual Variability –Disturbance/Chronosequence Processes –Photosynthesis = f(Q,T,functional type) –Respiration = f(T, growth, ppt,  Space Other Uses and Application –Ecosystem Modeling

18. Probability Distribution of Published NEE Measurements, Integrated Annually

19. Baldocchi, Austral J Botany, 2008 Does Net Ecosystem Carbon Exchange Scale with Photosynthesis? Ecosystems with greatest GPP don’t necessarily experience greatest NEE

20. Baldocchi, Austral J Botany, 2008 Ecosystem Respiration Scales Tightly with Ecosystem Photosynthesis, But Is with Offset by Disturbance

21. FLUXNET 2007 Database GPP at 2% efficiency and 365 day Growing Season Are Large Carbon Fluxes Defensible? tropics GPP at 2% efficiency and 182.5 day Growing Season

22. Baldocchi, Austral J Botany, 2008 Net Ecosystem Carbon Exchange Scales with Length of Growing Season

23. Data of Wofsy, Munger, Goulden, et al. Decadal Plus Time Series of NEE: Flux version of the Keeling’s Mauna Loa Graph

24. Interannual Variation and Long Term Trends in Net Ecosystem Carbon Exchange (F N ), Photosynthesis (F A ) and Respiration (F R ) Urbanski et al 2007 JGR

25. Baldocchi, Austral J Botany, 2008 Interannual Variations in Photosynthesis and Respiration are Coupled

26. Perturbations in Fluxes following 2003 European Heat Spell/Drought Implications on Drying of the Amazon

27. How many Towers are needed to estimate mean NEE, GPP and assess Interannual Variability, at the Global Scale? We Need about 75 towers to produce Robust and Invariant Statistics Based on Current Population

28. Increasing the Size of the Network Reduces the Sampling Error, but in an Asymptotic Manner Limit in the Precision of NEE Change that can be detected if Upscaled Globally: +/- 20 gC m-2 y-1 ~ 2 PgC/y = 2 10 15 gC/y Can We Truly Detect Year-Year Variations in Fluxes with a Sparse Network? Errors that sound Small at one scale may be Huge at another.. Says Nothing about Biases by Under Sampling Dominant Regions like the Tropics

29. Interannual Variability in NEE is tiny across the Global Network

30. What is Interannual Variability of Fluxes, sampled with the Network and the Network Detection Limit?

31. This Analysis Would Suggest Global Metabolism is Invariant with Time, like the Solar Constant Assuming Global Arable Land area is 110 10 6 km 2, Mean Global GPP ranges between 121.3 and 127.8 PgC/y Precision is about +/- 7 PgC/y

32. Complicating Dynamical Factors Switches –Phenology –Drought –Frost/Freeze Pulses –Rain –Litterfall Emergent Processes –Diffuse Light/LUE Acclimation Lags Stand Age/Disturbance

33. Emergent Scale Process: CO 2 Flux and Diffuse Radiation Niyogi et al., GRL 2004 We are poised to see effects of Cleaner/Dirtier Skies and Next Volcano

34. E. Falge et al 2002 AgForMet; Baldocchi et al 2001 BAMS Optimal NEE: Acclimation with Temperature

35. Data of Pilegaard et al. Soil Temperature: An Objective Indicator of Phenology??

36. Baldocchi et al. Int J. Biomet, 2005 Soil Temperature: An Objective Measure of Phenology, part 2

37. Rain-Induced Respiration Pulses Xu et al. 2005 GBC

38. Spatial Variations in C Fluxes Xiao et al. 2008, AgForMet

39. Upscale NEP, Globally, Explicitly 1.Compute GPP = f(T, ppt) 2.Compute R eco = f(GPP, Disturbance) 3.Compute NEP = GPP-R eco Leith-Reichstein Model R eco = 101 + 0.7468 * GPP R eco, disturbed= 434.99 + 0.922 * GPP FLUXNET Synthesis Baldocchi, 2008, Aust J Botany

40. Pros and Cons of Extracting Global Information from a Sparse Network

41. FLUXNET Over represents GPP in Temperate, Mid-Productive Ecosystems; Under-represents GPP in Semi-Arid, low-productive and Tropical, High Productive Regions

42. Sims et al 2005 AgForMet Do Snap-Shot C Fluxes, inferred from Remote Sensing, Relate to Daily C Flux Integrals?

43. UpScaling of FluxNetworks

44. Beer et al. 2010 Science Global GPP 121 +/- 8 PgC/y

45. Joint pdf GPP, Solar Radiation and Temperature E[GPP]= 1237 gC m -2 y -1 ~136 PgC/y

46. Importance, and Uncertainty, of Tropical GPP Beer et al. 2010 Science

47. Regional Maps for Carbon Markets Disturbances Climate Anomalies

48. Jung et al. 2010 Nature Evaluation of upscaled global Evapotranspiration (a)Map of mean Evapotranspiration from 1982-2008 (b) Predicted vs. Observed ET at FLUXNET sites (10-fold cross- validation from MTE training) (c)Corroboration aganist river catchment water balances (d)Comparison against GSWP-2 land surface model ensemble (16 models) stratified according to bioclimatic zones

49. Baldocchi, White, Schwartz, unpublished Spatialize Phenology with Transformation Using Climate Map

50. Limits to Landscape Classification by Functional Type Stand Age/Disturbance Biodiversity Fire Logging Insects/Pathogens Management/Plantations Kyoto Forests

51. Time Since Disturbance Affects Net Ecosystem Carbon Exchange: What Happens in the Tropics? Baldocchi, Austral J Botany, 2008 Data of teams lead by Amiro, Dunn, Paw U, Goulden

52. Other Activities and Uses of Fluxnet Data Landuse Ecosystem Modeling EcoHydrology Biodiversity Climate Modeling

53. Biodiversity and Evaporation Baldocchi, 2004: Data from Black, Schmid, Wofsy, Baldocchi, Fuentes

54. Deciduous Temperate Forest Baldocchi, unpublished

55. Kucharik et al., 2006 Ecol Modeling Ecosystem Model Testing and Development

56. Seasonality of Photosynthetic Capacity Wang et al, 2007 GCB

57. Optimizing Seasonality of Vcmax improves Prediction of Fluxes Wang et al, 2007 GCB

58. Bonan et al 2011, JGR Biogeoscience Improvement in CLM-4 Via better radiative transfer modeling, VCmx and stomatal Conduct Model structural revisions reduce global GPP over the period 1982–2004 from 165 Pg C yr−1 to 130 Pg C yr−1, and global evapotranspiration decreases from 68,000 km3 yr−1 to 65,000 km3 yr−1,

59. Improvements in CLM vs Fluxnet upscaling

60. Important to Sustain Networks Because Big Science Questions Being Answered by Flux Networks What is Global GPP? –123 +/- 8 PgC/ y, Beer et al, Science What is Global ET? –65,000 km3/y, Jung et al. 2010, Nature What is Global Year to Year Variability in GPP and NEE? What Emergent Scale Properties arise at the Ecosystem Scale? –Rain-induced respiration Pulses, modulated by photodegradation –Diffuse Light Enhances LUE –Q10 are static and Respiration Decrease with Heat and Drought –Optimal temperature of Photosynthesis Acclimates with local Climate –What is the effect of time since disturbance on NEE of tropical regions?

61. Acknowledgements Founding Leadership –Riccardo Valentini, Steve Running Data Preparation: FLUXNET-2007 –Dario Papale, Markus Reichstein, Catharine Van Ingen, Deb Agarwal, Tom Boden, Bob Cook, +++ FLUXNET Office @ Berkeley –Eva Falge, Lianhong Gu, Matthias Falk, Rodrigo Vargas, Laurie Koteen Regional Networks –AmeriFlux, CarboEurope, AsiaFlux, ChinaFlux, Fluxnet Canada, OzFlux, LBA, +++ Agencies –NSF/RCN, ILEAPS, DOE/TCP, NASA, Microsoft, ++++