Calculate mesophyll conductance to CO2 diffusion — calculate_gm

Calculates mesophyll conductance to CO2 diffusion (gmc) from combined gas exchange and isotope discrimination measurements as described in Busch et al. (2020). This function can accomodate alternative colum names for the variables taken from exdf_obj; it also checks the units of each required column and will produce an error if any units are incorrect.

Usage

calculate_gm_busch(
    exdf_obj,
    e = -3,
    f = 11,
    e_star_equation = 20,
    gm_type = 'dis',
    a_bar_column_name = 'a_bar',
    a_column_name = 'A',
    ci_column_name = 'Ci',
    co2_s_column_name = 'CO2_s',
    csurface_column_name = 'Csurface',
    delta_c13_r_column_name = 'delta_C13_r',
    delta_obs_growth_column_name = 'Delta_obs_growth',
    delta_obs_tdl_column_name = 'Delta_obs_tdl',
    gamma_star_column_name = 'Gamma_star_tl',
    rl_column_name = 'RL',
    total_pressure_column_name = 'total_pressure',
    t_column_name = 't'
  )

Arguments

exdf_obj: An exdf object.
e: The isotopic fractionation during day respiration in ppt.
f: The isotopic fractionation during photorespiration in ppt.
e_star_equation: The equation from Busch et al. (2020) to use for calculating e_star; must be 19 or 20.
gm_type: Determines whether day respiration is assumed to be isotopically connected to the CBB cycle (gm_type = 'con') or isotopically disconnected from the CBB cycle (gm_type = 'dis'). This choice will determine which equations are used to calculate mesophyll conductance; when gm_type is 'con', Equations 2 and 21 will be used; otherwise, Equations 13 and 22 will be used.
a_bar_column_name: The name of the column in exdf_obj that contains the weighted isotopic fractionation across the boundary layer and stomata in ppt. Values of a_bar are typically calculated using calculate_ternary_correction.
a_column_name: The name of the column in exdf_obj that contains the net CO2 assimilation rate in micromol m^(-2) s^(-1).
ci_column_name: The name of the column in exdf_obj that contains the intercellular CO2 concentration in micromol mol^(-1).
co2_s_column_name: The name of the column in exdf_obj that contains the CO2 concentration in the sample line (outgoing air) in micromol mol^(-1).
csurface_column_name: The name of the column in exdf_obj that contains the CO2 concentration at the leaf surface in micromol mol^(-1). Values of Csurface are typically calculated using calculate_gas_properties.
delta_c13_r_column_name: The name of the column in exdf_obj that contains the CO2 isotope ratio in the reference line (incoming air) in ppt.
delta_obs_growth_column_name: The name of the column in exdf_obj that contains the observed discrimination under the typical CO2 concentration in the plant's environment during its growth (in ppt). This is only required when using Equation 20 for e_star (see e_star_equation).
delta_obs_tdl_column_name: The name of the column in exdf_obj that contains the observed isotope discrimination values in ppt.
gamma_star_column_name: The name of the column in exdf_obj that contains the chloroplastic CO2 concentration at which CO2 gains from Rubisco carboxylation are exactly balanced by CO2 losses from Rubisco oxygenation, at leaf temperature, expressed in micromol mol^(-1). Values of Gamma_star at leaf temperature are typically calculated using calculate_gamma_star or calculate_temperature_response.
rl_column_name: The name of the column in exdf_obj that contains the rate of non-photorespiratory CO2 release in the light, in micromol m^(-2) s^(-1).
total_pressure_column_name: The name of the column in exdf_obj that contains the total pressure in bar.
t_column_name: The name of the column in exdf_obj that contains the ternary correction factor (dimensionless). Values of t are typically calculated using calculate_ternary_correction

Details

This function uses a model for photosynthetic discrimination against 13C in C3 plants to determine mesophyll conductance values as described in Busch et al. (2020). That paper provides two alternate ways to calculate e_star, and two alternate ways to calculate mesophyll conductance gmc; this function allows the user to choose between them. In more detail:

Isotopic fractionation due to day respiration (e_prime = e + e_star) is calculated with e_star given by either Equation 19 or 20 depending on the value of e_star_equation.
Isotopic discrimination assuming infinite mesophyll conductance (Delta_i) is calculated by setting Cc = Ci in either Equation 2 or 13, depending on the value of gm_type.
Mesophyll conductance to CO2 (gmc) is calculated using either Equation 21 or 22, depending on the value of gm_type.

Note 1: Setting e_star_equation = 19 and gm_type = 'con' should produce identical or similar results to calculate_gm_ubierna.

Note 2: Using e_star_equation = 20 and gm_type = 'dis' is expected to be more accurate, as discussed in Busch et al. (2020); however, be aware that this method requires a value for Delta_obs_growth, which may not always be available unless it is intentionally measured.

References:

Busch, F. A., Holloway-Phillips, M., Stuart-Williams, H. and Farquhar, G. D. "Revisiting carbon isotope discrimination in C3 plants shows respiration rules when photosynthesis is low." Nat. Plants 6, 245–258 (2020) [doi:10.1038/s41477-020-0606-6 ].

Value

An exdf object based on exdf_obj that includes the following additional columns, calculated as described above: e_prime, e_star, Delta_i, and gmc, as well as the values of a few intermediate calculations such as Delta_i_term_1 and Delta_i_term_2. The category for each of these new columns is calculate_gm_busch to indicate that they were created using this function.

Examples

## In this example we load gas exchange and TDL data files, calibrate the TDL
## data, pair the data tables together, and then calculate mesophyll conductance

# Read the TDL data file, making sure to interpret the time zone as US Central
# time
tdl_data <- read_gasex_file(
  PhotoGEA_example_file_path('tdl_for_gm.dat'),
  'TIMESTAMP',
  list(tz = 'America/Chicago')
)

# Identify cycles within the TDL data
tdl_data <- identify_tdl_cycles(
  tdl_data,
  valve_column_name = 'valve_number',
  cycle_start_valve = 20,
  expected_cycle_length_minutes = 2.7,
  expected_cycle_num_valves = 9,
  timestamp_colname = 'TIMESTAMP'
)

# Use reference tanks to calibrate the TDL data
processed_tdl <- consolidate(by(
  tdl_data,
  tdl_data[, 'cycle_num'],
  process_tdl_cycle_erml,
  noaa_valve = 2,
  calibration_0_valve = 20,
  calibration_1_valve = 21,
  calibration_2_valve = 23,
  calibration_3_valve = 26,
  noaa_cylinder_co2_concentration = 294.996,
  noaa_cylinder_isotope_ratio = -8.40,
  calibration_isotope_ratio = -11.505
))

# Read the gas exchange data, making sure to interpret the time stamp in the US
# Central time zone
licor_data <- read_gasex_file(
  PhotoGEA_example_file_path('licor_for_gm_site11.xlsx'),
  'time',
  list(tz = 'America/Chicago')
)

# Get TDL valve information from Licor file name; for this TDL system, the
# reference valve is 12 when the sample valve is 11
licor_data <- get_sample_valve_from_filename(licor_data, list('11' = 12))

# Pair the Licor and TDL data by locating the TDL cycle corresponding to each
# Licor measurement
licor_data <- pair_gasex_and_tdl(licor_data, processed_tdl$tdl_data)

# Calculate total pressure (needed for calculate_gas_properties)
licor_data <- calculate_total_pressure(licor_data)

# Calculate Csurface (needed for calculate_ternary_correction)
licor_data <- calculate_gas_properties(licor_data)

# Calculate ternary correction
licor_data <- calculate_ternary_correction(licor_data)

# Set Rubisco specificity (needed for calculate_gamma_star)
licor_data <- set_variable(
    licor_data,
    'rubisco_specificity_tl',
    'M / M',
    value = 90
)

# Calculate Gamma_star (needed for calculate_gm_busch)
licor_data <- calculate_gamma_star(licor_data)

# Calculate isotope discrimination (needed for calculate_gm_busch)
licor_data <- calculate_isotope_discrimination(licor_data)

# Set Delta_obs_growth to the average of Delta_obs_tdl over the first 6 points,
# where the ambient CO2 concentration was set to the atmospheric value (420 ppm)
# (needed for calculate_gm_busch).
licor_data <- set_variable(
  licor_data,
  'Delta_obs_growth',
  'ppt',
  value = mean(licor_data[1:6, 'Delta_obs_tdl'])
)

# Set respiration (needed for calculate_gm_busch)
licor_data <- set_variable(
  licor_data,
  'RL',
  'micromol m^(-2) s^(-1)',
  value = 1.2
)

# Calculate mesophyll conductance
licor_data <- calculate_gm_busch(licor_data)

# Calculate Cc using the new values of mesophyll conductance
licor_data <- calculate_temperature_response(
  licor_data,
  c3_temperature_param_flat['gmc_norm']
)

licor_data <- set_variable(
  licor_data,
  'gmc_at_25',
  units = licor_data$units$gmc,
  value = licor_data[, 'gmc']
)

licor_data <- apply_gm(licor_data)

# View some of the results
licor_data[, c('replicate', 'CO2_s', 'Delta_obs_tdl', 'e_prime', 'gmc', 'Ci', 'Cc')]
#>    replicate   CO2_s Delta_obs_tdl     e_prime       gmc       Ci        Cc
#> 1          1 417.363      8.039825 -0.18823755 0.1741137 286.7663 101.17189
#> 2          1 420.552      8.137268 -0.19234146 0.1842765 276.9970 102.18116
#> 3          1 418.796      7.893969  0.22659156 0.1673504 291.8317  99.70574
#> 4          1 419.493      8.029239  0.04858619 0.1692784 291.1437 101.74081
#> 5          1 420.102      8.964915 -0.79223714 0.1802174 293.7559 116.20312
#> 6          1 421.133      8.673921 -0.50309810 0.1734677 295.9070 112.18043
#> 7          1 262.873      6.434975  2.07663004 0.1596937 182.7755  55.63881
#> 8          1 262.720      6.747186  1.59617713 0.1656192 181.1386  58.38280
#> 9          1 262.633      6.326945  2.46892812 0.1623944 179.6180  54.31518
#> 10         1 262.271      6.358834  2.17658584 0.1497082 191.7498  55.81379
#> 11         1 262.112      7.450206  0.92544892 0.1536710 199.2717  66.86048
#> 12         1 262.176      6.843263  1.42169819 0.1425367 204.1826  61.70023