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
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NLR_AM (AQRTa) modelAsko NoormetsUniversity of Toledo Toledo, Ohio, USA
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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
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FeaturesMonthly time-windowCo-fitting respiration and assimilation models
Reflect functional changesProvide robust parameter estimates
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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
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Seasonal changesNoormets et al., 2006. Ch. 4 in Ecology of Hierarchical LandscapesDeForest et al., 2006. Int. J. Biomet.
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Time window Weekly vs. monthly integrationdomain of functional changediurnal pH, Rubisco, CHOseasonal SLA, xylem conductance, SWC, VPD
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Time window Weekly vs. monthly integrationdomain of functional changediurnal pH, Rubisco, CHOseasonal SLA, xylem conductance, VPD, SWCOverlapping vs. non-overlapping windows
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2. Co-fitting R & AConstrains parameter estimatesbroader data spread = better constrained model
Compromises nighttime accuracy
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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
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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 ?
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Conclusions - ways to improveNeed:Formal criteria for selecting time window
More sophisticated ER function
Likelihood-based estimates
