Make an initial guess of "variable J" model parameter values for one curve

Creates a function that makes an initial guess of "variable J" model parameter values for one curve. This function is used internally by fit_c3_variable_j.

Values estimated by this guessing function should be considered inaccurate, and should always be improved upon by an optimizer.

Usage

initial_guess_c3_variable_j(
    alpha_g,
    alpha_old,
    alpha_s,
    Gamma_star,
    cc_threshold_rd = 100,
    atp_use = 4.0,
    nadph_use = 8.0,
    a_column_name = 'A',
    ci_column_name = 'Ci',
    etr_column_name = 'ETR',
    j_norm_column_name = 'J_norm',
    kc_column_name = 'Kc',
    ko_column_name = 'Ko',
    oxygen_column_name = 'oxygen',
    phips2_column_name = 'PhiPS2',
    qin_column_name = 'Qin',
    rl_norm_column_name = 'RL_norm',
    vcmax_norm_column_name = 'Vcmax_norm'
  )

Arguments

alpha_g: A dimensionless parameter where 0 <= alpha_g <= 1, representing the proportion of glycolate carbon taken out of the photorespiratory pathway as glycine. alpha_g is often assumed to be 0. If alpha_g is not a number, then there must be a column in rc_exdf called alpha_g with appropriate units. A numeric value supplied here will overwrite the values in the alpha_g column of rc_exdf if it exists.
alpha_old: A dimensionless parameter where 0 <= alpha_old <= 1, representing the fraction of remaining glycolate carbon not returned to the chloroplast after accounting for carbon released as CO2. alpha_old is often assumed to be 0. If alpha_old is not a number, then there must be a column in rc_exdf called alpha_old with appropriate units. A numeric value supplied here will overwrite the values in the alpha_old column of rc_exdf if it exists.
alpha_s: A dimensionless parameter where 0 <= alpha_s <= 0.75 * (1 - alpha_g) representing the proportion of glycolate carbon taken out of the photorespiratory pathway as serine. alpha_s is often assumed to be 0. If alpha_s is not a number, then there must be a column in rc_exdf called alpha_s with appropriate units. A numeric value supplied here will overwrite the values in the alpha_s column of rc_exdf if it exists.
Gamma_star: The CO2 compensation point in the absence of day respiration, expressed in micromol mol^(-1). If Gamma_star is not a number, then there must be a column in rc_exdf called Gamma_star with appropriate units. A numeric value supplied here will overwrite the values in the Gamma_star column of rc_exdf if it exists.
cc_threshold_rd: An upper cutoff value for the chloroplast CO2 concentration in micromol mol^(-1) to be used when estimating RL.
atp_use: The number of ATP molecules used per C3 cycle.
nadph_use: The number of NADPH molecules used per C3 cycle.
a_column_name: The name of the column in rc_exdf that contains the net assimilation in micromol m^(-2) s^(-1).
ci_column_name: The name of the column in rc_exdf that contains the intercellular CO2 concentration in micromol mol^(-1).
etr_column_name: The name of the column in rc_exdf that contains the electron transport rate as estimated by the measurement system in micromol m^(-2) s^(-1).
j_norm_column_name: The name of the column in rc_exdf that contains the normalized J values (with units of normalized to J at 25 degrees C).
kc_column_name: The name of the column in rc_exdf that contains the Michaelis-Menten constant for rubisco carboxylation in micromol mol^(-1).
ko_column_name: The name of the column in rc_exdf that contains the Michaelis-Menten constant for rubisco oxygenation in mmol mol^(-1).
oxygen_column_name: The name of the column in exdf_obj that contains the concentration of O2 in the ambient air, expressed as a percentage (commonly 21% or 2%); the units must be percent.
phips2_column_name: The name of the column in rc_exdf that contains values of the operating efficiency of photosystem II (dimensionless).
qin_column_name: The name of the column in rc_exdf that contains values of the incident photosynthetically active flux density in micromol m^(-2) s^(-1).
rl_norm_column_name: The name of the column in rc_exdf that contains the normalized RL values (with units of normalized to RL at 25 degrees C).
vcmax_norm_column_name: The name of the column in rc_exdf that contains the normalized Vcmax values (with units of normalized to Vcmax at 25 degrees C).

Details

The variable J method is a fitting procedure for estimating values of alpha_g, alpha_old, alpha_s, Gamma_star, J_at_25, RL_at_25, tau, Tp, and Vcmax_at_25 from a measured C3 CO2 response curve + chlorophyll fluorescence. For more information about these parameters, see the documentation at calculate_c3_variable_j and calculate_c3_assimilation.

Here, we make an estimate for tau by noting that gas exchange measurement systems equipped with chlorophyll fluorometers typically make an estimate for the electron transport rate (ETR), which is essentially synonymous with the actual RuBP regeneration rate. Thus, tau can be estimated by inverting the equation for J_actual:

tau = ETR / (Qin * PhiPSII)

Estimates of the remaining parameters are calculated by setting Cc = Ci and then calling initial_guess_c3_aci.

Value

A function with one input argument rc_exdf, which should be an exdf object representing one C3 CO2 response curve. The return value of this function will be a numeric vector with nine elements, representing the values of alpha_g, alpha_old, alpha_s, J_at_25, RL_at_25, tau, Tp, and Vcmax_at_25 (in that order).

Examples

# Read an example Licor file included in the PhotoGEA package
licor_file <- read_gasex_file(
  PhotoGEA_example_file_path('c3_aci_1.xlsx')
)

# Define a new column that uniquely identifies each curve
licor_file[, 'species_plot'] <-
  paste(licor_file[, 'species'], '-', licor_file[, 'plot'] )

# Organize the data
licor_file <- organize_response_curve_data(
    licor_file,
    'species_plot',
    c(9, 10, 16),
    'CO2_r_sp'
)

# Calculate the total pressure in the Licor chamber
licor_file <- calculate_total_pressure(licor_file)

# Calculate temperature-dependent values of C3 photosynthetic parameters
licor_file <- calculate_arrhenius(licor_file, c3_arrhenius_bernacchi)

# Create the guessing function; here we set all alpha values to 0 and use the
# temperature-dependent values of Gamma_star calculated above
guessing_func <-
  initial_guess_c3_variable_j(alpha_g = 0, alpha_old = 0, alpha_s = 0, Gamma_star = '')

# Apply it and see the initial guesses for each curve
str(by(licor_file, licor_file[, 'species_plot'], guessing_func))
#> List of 3
#>  $ soybean - 5a: num [1:9] 0 0 0 56.6 209 ...
#>  $ tobacco - 1 : num [1:9] 0 0 0 55.6 247.4 ...
#>  $ tobacco - 2 : num [1:9] 0 0 0 55.9 220.5 ...

# Calculate simulated A-Ci curves based on the guesses and compare them to the
# actual data
calculated_aci <- do.call(rbind, by(
  licor_file,
  licor_file[, 'species_plot'],
  function(x) {
    param <- guessing_func(x)
    x <- cbind(x, calculate_c3_variable_j(x, param[1], param[3], param[4], param[6], param[7]))
    cbind(x,
      calculate_c3_assimilation(
        x,
        param[1], param[2], param[3], param[4], param[5], param[6], param[8], param[9]
      )
    )
  }
))

lattice::xyplot(
  Ac + Aj + Ap + An + A ~ Cc | species_plot,
  data = cbind(licor_file, calculated_aci)$main_data,
  type = 'b',
  auto = TRUE,
  grid = TRUE
)