FLUXNET: Measuring CO2 and Water Vapor Fluxes Across a Global Network

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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
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FLUXNET From Sea to Shining Sea379 Sites, circa
2006
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Global distribution of Flux Towers with Respect
to Climate
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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

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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

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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

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Visions with a Flux Measurement Network

• Processes
• Canopy-Scale Response Functions
• Emergent Processes
• Flux Partitioning, NEPGPP-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

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Probability Statistics of NEE
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Light and PhotosynthesisEmergent Processes at
Leaf and Canopy Scales
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Volcanoes, Aerosols NEE
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CO2 Flux and Diffuse Radiation
Niyogi et al., GRL 2004
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Photosynthesis-Respiration
Processed by Falge
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NEE Acclimation with Temperature
Analysis of E. Falge
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Linking Water and Carbon Potential to assess Gc
with Remote Sensing
Xu DDB
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Temporal Dynamics of C Fluxes

• Hour
• Day
• Month
• Season
• Year
• Multiple Years

• Pulses
• Lags
• Switches

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Complicating Dynamical Factors

• Switches/Pulses
• Rain
• Phenology/Length of Season
• Frost/Freezing
• Emergent Processes
• Clouds LUE
• Acclimation
• Lags
• Stand Age/Disturbance

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Decadal Plus Time Series of NEEFlux version of
the Keelings Mauna Loa Graph
Data of Wofsy, Munger, Goulden et al.
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DRe vs DGPP
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Lag Effects Due to Drought/Heat Stress
Knohl et al Max Planck, Jena
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Soil Temperature An Objective Indicator of
Phenology??
Data of Pilegaard et al.
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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
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Spatial Variations in C Fluxes
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Spatial GradientsNEE and Length of Growing
Season
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Tower vs Satellite NDVI
Falk et al., to be submitted
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Sims et al 2005 AgForMet
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Heinsch et al. IEEE 2006
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Global MODIS Test
Heinsch et al. IEEE 2006
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Limits to Landscape Classification by Functional
Type

• Stand Age/Disturbance
• Biodiversity
• Fire
• Logging
• Insects/Pathogens
• Management/Plantations
• Kyoto Forests

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Effects of Stand AgeAfter Logging
Law et al. 2003 Global Change Biology
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Biodiversity and Evaporation
Baldocchi, 2004 Data from Black, Schmid, Wofsy,
Baldocchi, Fuentes
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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