optimize_leaf: Optimize leaf photosynthesis
In cdmuir/leafoptimizer: Optimize leaf traits to different environments in silico

Description Usage Arguments Details Value Examples

View source: R/optimize_leaf.R

optimize_leaf: simulate C3 photosynthesis over a single parameter set

1
2
3

optimize_leaf(traits, carbon_costs, bake_par, constants, enviro_par,
  leaf_par, set_units = TRUE, n_init = 1L, check = TRUE,
  quiet = FALSE, refit = TRUE, max_init = 3L)

`traits`	A vector of one or more character strings indicating which trait(s) to optimize. Stomatal conductance (`g_sc`) and stomatal ratio (`logit_sr`) are currently supported.
`carbon_costs`	A named list of resources with their costs in terms of carbon (e.g. mol C / mol H2O). Currently only H2O and SR are supported. See details below.
`bake_par`	A list of temperature response parameters inheriting class `bake_par`. This can be generated using the `make_bakepar` function.
`constants`	A list of physical constants inheriting class `constants`. This can be generated using the `make_constants` function.
`enviro_par`	A list of environmental parameters inheriting class `enviro_par`. This can be generated using the `make_enviropar` function.
`leaf_par`	A list of leaf parameters inheriting class `leaf_par`. This can be generated using the `make_leafpar` function.
`set_units`	Logical. Should `units` be set? The function is faster when FALSE, but input must be in correct units or else results will be incorrect without any warning.
`n_init`	Integer. Number of initial values for each trait to try during optimization. If there are multiple traits, these initial values are crossed. For example, if `n_init = 3`, the total number of intitial values sets is 3, 9, 27 for 1, 2, 3 traits, respectively. This significantly increases the time, but may be important if the surface is rugged. Default is 1L.
`check`	Logical. Should arguments checks be done?
`quiet`	Logical. Should messages be displayed?
`refit`	Logical. Should optimization be retried from different starting parameters if it fails to converge? If TRUE, upon failure, `n_init` will increment up by 1 until successful convergence or `n_init > max_init`.
`max_init`	Integer. If `refit = TRUE`, the maximum number `n_init` to try.

optimize_leaf: This function optimizes leaf traits using an integrated leaf temperature and C3 photosynthesis model under a set of environmental conditions. The leaf temperature model is described in the tealeaves package. The C3 photosynthesis model is described in the photosynthesis-package package

A data.frame with the following units columns

Input:

`C_air`	atmospheric CO2 concentration (Pa)
`g_mc25`	mesophyll conductance to CO2 at 25 °C (μmol CO2 / (m^2 s Pa))
`g_sc`	stomatal conductance to CO2 (μmol CO2 / (m^2 s Pa))
`g_uc`	cuticular conductance to CO2 (μmol CO2 / (m^2 s Pa))
`gamma_star25`	chloroplastic CO2 compensation point at 25 °C (Pa)
`J_max25`	potential electron transport at 25 °C (μmol CO2) / (m^2 s)
`K_C25`	Michaelis constant for carboxylation at 25 °C (μmol / mol)
`K_O25`	Michaelis constant for oxygenation at 25 °C (μmol / mol)
`k_mc`	partition of g_mc to lower mesophyll (unitless)
`k_sc`	partition of g_sc to lower surface (unitless)
`k_uc`	partition of g_uc to lower surface (unitless)
`leafsize`	leaf characteristic dimension (m)
`O`	atmospheric O2 concentration (kPa)
`P`	atmospheric pressure (kPa)
`phi`	initial slope of the response of J to PPFD (unitless)
`PPFD`	photosynthetic photon flux density (umol quanta / (m^2 s))
`R_d25`	nonphotorespiratory CO2 release at 25 °C (μmol CO2 / (m^2 s))
`RH`	relative humidity (unitless)
`theta_J`	curvature factor for light-response curve (unitless)
`T_air`	air temperature (K)
`T_leaf`	leaf tempearture (K)
`V_cmax25`	maximum rate of carboxylation at 25 °C (μmol CO2 / (m^2 s))
`V_tpu25`	rate of triose phosphate utilisation at 25 °C (μmol CO2 / (m^2 s))
`wind`	wind speed (m / s)

Baked Input:

`g_mc`	mesophyll conductance to CO2 at `T_leaf` (μmol CO2 / (m^2 s Pa))
`gamma_star`	chloroplastic CO2 compensation point at `T_leaf` (Pa)
`J_max`	potential electron transport at `T_leaf` (μmol CO2) / (m^2 s)
`K_C`	Michaelis constant for carboxylation at `T_leaf` (μmol / mol)
`K_O`	Michaelis constant for oxygenation at `T_leaf`(μmol / mol)
`R_d`	nonphotorespiratory CO2 release at `T_leaf` (μmol CO2 / (m^2 s))
`V_cmax`	maximum rate of carboxylation at `T_leaf` (μmol CO2 / (m^2 s))
`V_tpu`	rate of triose phosphate utilisation at `T_leaf` (μmol CO2 / (m^2 s))

Output:

`A`	photosynthetic rate at `C_chl` (μmol CO2 / (m^2 s))
`C_chl`	chloroplastic CO2 concentration where `A_supply` intersects `A_demand` (Pa)
`g_tc`	total conductance to CO2 at `T_leaf` (μmol CO2 / (m^2 s Pa))
`value`	`A_supply` - `A_demand` (μmol CO2 / (m^2 s)) at `C_chl`
`convergence`	convergence code (0 = converged)

# Single parameter set with 'optimize_leaf'

bp <- make_bakepar()
cs <- make_constants()
ep <- make_enviropar()
lp <- make_leafpar()
traits <- "g_sc"
carbon_costs <- list(H2O = 1000, SR = 0)
optimize_leaf("g_sc", carbon_costs, bp, cs, ep, lp, n_init = 1L)