NLR_AM (AQRTa) model

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NLR_AM (AQRTa) model. Asko Noormets University of Toledo Toledo, Ohio, USA. Model. R 10 ( μ mol CO 2 m -2 s -1 ) – reference respiration Ea (kJ mol -1 K -1 ) – activation energy R (8.3134 J mol -1 K -1 ) – universal gas constant T ref ( K ) – reference air temperature - PowerPoint PPT Presentation

Transcript of NLR_AM (AQRTa) model

  • NLR_AM (AQRTa) modelAsko NoormetsUniversity of Toledo Toledo, Ohio, USA

  • ModelNoormets et al., In press, EcosystemsR10 (mol CO2 m-2 s-1) reference respirationEa (kJ mol-1 K-1) activation energyR (8.3134 J mol-1 K-1) universal gas constantTref (K) reference air temperatureTa (K) ambient air temperaturea (mol CO2 mol-1 PAR) apparent quantum yieldf (mol quanta m-2 s-1) PARPmax (mol CO2 m-2 s-1 ) light-saturated assimilation rate

  • FeaturesMonthly time-windowCo-fitting respiration and assimilation models

    Reflect functional changesProvide robust parameter estimates

  • 1. Monthly time windowInformation content diurnal synoptic phenological

    Baldocchi et al., 2001, GCBKatul & Parlange, 1995, Water Resour. Res.Stoy et al., 2005, Tree Physiol.; 2006, GCB

  • Seasonal changesNoormets et al., 2006. Ch. 4 in Ecology of Hierarchical LandscapesDeForest et al., 2006. Int. J. Biomet.

  • Time window Weekly vs. monthly integrationdomain of functional changediurnal pH, Rubisco, CHOseasonal SLA, xylem conductance, SWC, VPD

  • Time window Weekly vs. monthly integrationdomain of functional changediurnal pH, Rubisco, CHOseasonal SLA, xylem conductance, VPD, SWCOverlapping vs. non-overlapping windows

  • 2. Co-fitting R & AConstrains parameter estimatesbroader data spread = better constrained model

    Compromises nighttime accuracy

  • Other modelsCofilled: AQRTAlso done: RT+AQ

    Temp.R10Window1.Taconst.Month2.Taconst.Week3.Tsconst.Month4.Tsconst.Week5.Taf (SWC)Month6.Taf (SWC)Week7.Tsf (SWC)Month8.Tsf (SWC)Week

  • Tair vs. Tsoil & confounding factorsTair and Tsoil are out of phaseSR peaks at ~4-7 PM ER higher after dusk than before dawnCHO transport highest after dusk

    ? Tsoil- vs. CHO-dependence ?

  • Conclusions - ways to improveNeed:Formal criteria for selecting time window

    More sophisticated ER function

    Likelihood-based estimates