photos_model: Photosynthesis model

In oscarperezpriego/ETpartitioning: Partitioning of eddy covariance ET into flux components

Description

Modelling eddy covariance derived photosynthesis via diffusion of CO2 through stomata and plant optimization theory (see Perez-Priego et al., 2018).

Usage

photos_model(par, data, ColPhotos, ColH, ColVPD, ColTair, ColPair, ColQ,
  ColCa, ColUstar, ColWS, ColSW_in, Chi_o)

Arguments

par	A vector containing optimal parameters (a1,Do,To,beta).
data	Data.frame or matrix containing all required variables.
ColPhotos	Column name of numeric vector containing time series of photosynthesis data (umol CO2 m-2 s-1).
ColH	Column name of numeric vector containing time series of sensible heat flux (W m-2).
ColVPD	Column name of numeric vector containing time series of vapor pressure deficit (hPa).
ColTair	Column name of numeric vector containing time series of air temperature (deg C).
ColPair	Column name of numeric vector containing time series of atmospheric pressure (kPa).
ColQ	Column name of numeric vector containing time series of photosynthetic active radiation (umol m-2 s-1).
ColCa	Column name of numeric vector containing time series of atmospheric CO2 concentration (umol Co2 mol air-1).
ColUstar	Column name of numeric vector containing time series of wind friction velocity (m s-1).
ColWS	Column name of numeric vector containing time series of wind velocity (m s-1).
ColSW_in	Column name of numeric vector containing time series of incoming short-wave radiation (W m-2).
Chi_o	Long-term effective chi.

Details

The following metrics are calculated as:

Photos <- (gc_bulk*Ca*(1-Chi)

gc_bulk accounts for stomatal and aerodynamic effects. While chi is estimated using optimality theory as:

Chi <- (Chi_o*1/(1+beta*VPD^0.5)

Value

a numeric vector containing estimates of photosyntesis rates (umolCO2 m-2 s-1)

Note

Model is constrained with estimates of Photos from the night-time NEE partitioning approach (Reichstein et al., 2005). chi is optimized following Perez-Priego et al., 2018.

References

Perez-Priego, O., G. Katul, M. Reichstein et al. Partitioning eddy covariance water flux components using physiological and micrometeorological approaches, Journal of Geophysical Research: Biogeosciences. In press

Reichstein, M., et al. (2005), On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm, Global Change Biology, 11(9), 1424-1439.

Examples

 ## Selecting a single day (e.g. 15-05-2011)
 tmp <-  EddySample[ EddySample$TIMESTAMP_START>  201105150000,]
 tmp <-  tmp[tmp$TIMESTAMP_START<  201105160000,]
 ## Defining parameter values
 par <- c(382, 0.05, 23, 0.62)

 photos_model(par = par
 ,data = tmp
 ,ColPhotos = "GPP_NT_VUT_MEAN"
 ,ColH = "H_F_MDS"
 ,ColVPD = "VPD_F"
 ,ColTair = "TA_F"
 ,ColPair = "PA_F"
 ,ColQ = "PPFD_IN"
 ,ColCa = "CO2_F_MDS"
 ,ColUstar = "USTAR"
 ,ColWS = "WS_F"
 ,ColSW_in = "SW_IN_F"
 ,Chi_o = 0.88
)

oscarperezpriego/ETpartitioning documentation built on June 4, 2019, 12:13 a.m.