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FLUXNET: Measuring CO 2 and Water Vapor Fluxes Across a Global Network

FLUXNET: Measuring CO 2 and Water Vapor Fluxes Across a Global Network. Dennis Baldocchi ESPM/Ecosystem Science Div. University of California, Berkeley. IndoFlux, Chennai, India, July 2006. FLUXNET: From Sea to Shining Sea 379 Sites, circa 2006.

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FLUXNET: Measuring CO 2 and Water Vapor Fluxes Across a Global Network

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  1. FLUXNET: Measuring CO2 and Water Vapor Fluxes Across a Global Network Dennis Baldocchi ESPM/Ecosystem Science Div. University of California, Berkeley IndoFlux, Chennai, India, July 2006

  2. FLUXNET: From Sea to Shining Sea379 Sites, circa 2006

  3. Global distribution of Flux Towers with Respect to Climate

  4. Evolution of FLUXNET • Measure Annual Cycle of NEE • Micromet issues of Detrending, Transfer Functions, Flux Sampling and Measurements, Gap-filling, Error Assessment • Measure and Interpret Intra-annual Variation of NEE • Flux partitioning (GPP & Reco); assessment of metadata,e.g. Vcmax, soil respiration, LAI, biomass inventories. • Measure and Interpret Inter-annual variations of NEE • Measure NEE over multiple Land-Use Classes • crops, grasslands, deciduous and evergreen broadleaf and conifer forests • Disturbance: logging, biodiversity and fire • Manipulative Studies • Nitrogen and H2O additions • Measure NEE over Representative Areas • Scaling Flux Information of Footprint to MODIS pixel

  5. Successes • Mountains of data from a spectrum of canopy roughness conditions, functional types and climate spaces have been collected • A Model for Data Sharing • FLUXNET Web Site, a venue for distributing Primary, Value-added and Meta-Data products • Value-Added Products have been produced • Development of Gap-Filling Techniques • Production of Gap-Filled Daily and Annual Sums • Data for Validating and Improving SVAT models used for weather, climate, biogeochemistry and ecosystem dynamics • Collaboration & Synthesis through Workshops and Hosting Visitors • Building a Collaborative, Cooperative, Multi-Disciplinary & International Community of Researchers • Characterizing Annual C Fluxes • Environmental Controls on NEE • Training New and Next Generation of Scientists, Postdocs, Students

  6. ‘Failures’/’Un-resolved’ Issues • Not Measuring Night-time Fluxes Well • Not Measuring Fluxes over Complex terrain and during Advection Well • ImPerfect U* correction • New Gu Algorithm • ImPerfect Flux Partitioning • Works Better on Longer Time Scales • ImPerfect Energy Balance Closure • Could be ‘red-herring’ • Need Better Outreach and Training • Needs Expansion into other Regions • India • Africa

  7. Visions with a Flux Measurement Network • Processes • Canopy-Scale Response Functions • Emergent Processes • Flux Partitioning, NEP=GPP-Reco • Acclimation • Time • Daily/Seasonal Dynamics • Pulses, Lags, Switches • Intra- + Interannual Variability • Stand Age/Disturbance • Space • Climate/Structure/Function • Coherence/Gradients • Upscaling with Remote Sensing • New Directions

  8. Probability Statistics of NEE

  9. Light and Photosynthesis:Emergent Processes at Leaf and Canopy Scales

  10. Volcanoes, Aerosols + NEE

  11. CO2 Flux and Diffuse Radiation Niyogi et al., GRL 2004

  12. Photosynthesis-Respiration Processed by Falge

  13. NEE: Acclimation with Temperature Analysis of E. Falge

  14. Linking Water and Carbon: Potential to assess Gc with Remote Sensing Xu + DDB

  15. Temporal Dynamics of C Fluxes • Hour • Day • Month • Season • Year • Multiple Years • Pulses • Lags • Switches

  16. Complicating Dynamical Factors • Switches/Pulses • Rain • Phenology/Length of Season • Frost/Freezing • Emergent Processes • Clouds & LUE • Acclimation • Lags • Stand Age/Disturbance

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

  18. DRe vs DGPP

  19. Lag Effects Due to Drought/Heat Stress Knohl et al Max Planck, Jena

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

  21. Soil Temperature: An Objective Measure of Phenology, part 2 Data of: ddb, Wofsy, Pilegaard, Curtis, Black, Fuentes, Valentini, Knohl, Yamamoto. Granier, Schmid Baldocchi et al. Int J. Biomet, in press

  22. Spatial Variations in C Fluxes

  23. Spatial Gradients:NEE and Length of Growing Season

  24. Tower vs Satellite NDVI Falk et al., to be submitted

  25. Sims et al 2005 AgForMet

  26. Heinsch et al. IEEE 2006

  27. Global MODIS Test Heinsch et al. IEEE 2006

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

  29. Effects of Stand Age:After Logging Law et al. 2003 Global Change Biology

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

  31. Value of Flux Networks • Documenting Change in Ecosystem Metabolism • Network acts as ‘canary in the mine’ • Produces Large and Long Data Sets • Reduced Sampling Error • Robust Dataset for Model Development • Study Spectra of Time Scales • Capture Pulses and Lags • Study Gradient of Climates, Structure and Function • Field of Dreams: ‘Build it and they will Come’ • Better Integrated Research Studies

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