Contains modeling and analytical tools for plant ecophysiology.
MODELING: Simulate C3 photosynthesis using the Farquhar, von Caemmerer,
Berry (1980)
photosynthesis is a lightweight R package to model C3 photosynthesis using the Farquhar-von Caemmerer-Berry model. It uses the R package units to ensure that parameters are properly specified and transformed before calculations.
From GitHib
install.packages("devtools")remotes::install_github("cdmuir/photosynthesis")
And load photosynthesis
library("photosynthesis")
The photosynthesis package simulates photosynthetic rate given a set of leaf traits and environmental conditions by solving the Farquhar-von Caemmerer-Berry C3 biochemical model. There are two main steps to using photosynthesis:
photo
and photosynthesis
for single and
multiple parameter sets, respectively).In this vignette, I’ll show you how to:
You can use the default parameter settings and simulate photosynthetic
rate in a single leaf using the make_*()
functions and photo()
.
library(dplyr)library(magrittr)library(photosynthesis)# Leaving the make_* functions empty will automatically default to defaults# parameters.bake_par <- make_bakepar() # temperature response parametersconstants <- make_constants(use_tealeaves = FALSE) # physical constantsleaf_par <- make_leafpar(use_tealeaves = FALSE) # leaf parametersenviro_par <- make_enviropar(use_tealeaves = FALSE) # environmental parametersphoto(leaf_par, enviro_par, bake_par, constants, quiet = TRUE,use_tealeaves = FALSE)#> C_chl value convergence g_tc#> 1 24.52925 [Pa] -1.09648e-06 0 1.668765 [umol/m^2/Pa/s]#> A g_mc25 g_sc#> 1 27.48581 [umol/m^2/s] 4 [umol/m^2/Pa/s] 4 [umol/m^2/Pa/s]#> g_uc gamma_star25 J_max25 K_C25#> 1 0.1 [umol/m^2/Pa/s] 3.743 [Pa] 200 [umol/m^2/s] 27.238 [Pa]#> K_O25 k_mc k_sc k_uc leafsize phi_J R_d25#> 1 16.582 [kPa] 1 [1] 1 [1] 1 [1] 0.1 [m] 0.331 [1] 2 [umol/m^2/s]#> T_leaf theta_J V_cmax25 V_tpu25 g_mc gamma_star#> 1 298.15 [K] 0.825 [1] 150 [umol/m^2/s] 200 [umol/m^2/s] 4 3.743#> J_max K_C K_O R_d V_cmax V_tpu C_air O#> 1 200 27.238 16.582 2 150 200 41 [Pa] 21.27565 [kPa]#> P PPFD RH wind#> 1 101.3246 [kPa] 1500 [umol/m^2/s] 0.5 [1] 2 [m/s]
You can look at default parameters settings in the manual (run
?make_parameters
). These defaults are reasonable, but of course you
will probably want to use different choices and allow some parameters to
vary. Here, I’ll demonstrate how to replace a default. In the next
section, I’ll show you how to set up a gradient of parameter values over
which to solve for leaf temperature.
# Use the `replace` argument to replace defaults. This must be a named list, and# each named element must have the proper units specified. See `?make_parameters`# for all parameter names and proper units.# Temperature response parameters can be updated (but we won't do that here)bake_par <- make_bakepar()# Physical constants probably do not need to be replaced in most cases,# that's why we call them 'constants'!constants <- make_constants(use_tealeaves = FALSE)# First, we'll change photosynthetic photon flux density to 1000 umol / (m^2 s)enviro_par <- make_enviropar(replace = list(PPFD = set_units(1000, "umol/m^2/s")), use_tealeaves = FALSE)# Next, we'll change stomatal conductance to 3 umol / (m^2 s Pa)leaf_par <- make_leafpar(replace = list(g_sc = set_units(3, "umol/m^2/s/Pa")), use_tealeaves = FALSE)photo <- photo(leaf_par, enviro_par, bake_par, constants, quiet = TRUE,use_tealeaves = FALSE)photo %>%select(PPFD, C_chl, A) %>%knitr::kable()
PPFD | C_chl | A |
---|---|---|
1000 [umol/m^2/s] | 24.0449 [Pa] | 25.21885 [umol/m^2/s] |
In the previous two examples, I used the photo
function to solve for a
single parameter set. In most cases, you’ll want to solve for many
parameter sets. The function photosynthesis
generalizes photo
and
makes it easy to solve for multiple parameter sets using the same
argument structure. All you need to do is specify multiple values for
one or more leaf or environmental parameters and photosynthesis
uses
the purrr::cross
function to fit all combinations[1].
# As before, use the `replace` argument to replace defaults, but this time we# enter multiple valuesbake_par <- make_bakepar()constants <- make_constants(use_tealeaves = FALSE)# First, we'll change the PPFD to 1000 and 1500 umol / (m^2 s)enviro_par <- make_enviropar(replace = list(PPFD = set_units(c(1000, 1500), "umol/m^2/s")), use_tealeaves = FALSE)# Next, we'll change stomatal conductance to to 2 and 4 umol / (m^2 s Pa)leaf_par <- make_leafpar(replace = list(g_sc = set_units(c(2, 4), "umol/m^2/s/Pa")), use_tealeaves = FALSE)# Now there should be 4 combinations (high and low g_sc crossed with high and low PPFD)ph <- photosynthesis(leaf_par, enviro_par, bake_par, constants,use_tealeaves = FALSE, progress = FALSE, quiet = TRUE)ph %>%select(g_sc, PPFD, A) %>%knitr::kable()
g_sc | PPFD | A |
---|---|---|
2 [umol/m^2/Pa/s] | 1000 [umol/m^2/s] | 23.90532 [umol/m^2/s] |
4 [umol/m^2/Pa/s] | 1000 [umol/m^2/s] | 25.87941 [umol/m^2/s] |
2 [umol/m^2/Pa/s] | 1500 [umol/m^2/s] | 25.17778 [umol/m^2/s] |
4 [umol/m^2/Pa/s] | 1500 [umol/m^2/s] | 27.48581 [umol/m^2/s] |
It can take a little while to simulate many different parameter sets. If
you have multiple processors available, you can speed things up by
running simulations in parallel. In the photosynthesis
function,
simply use the parallel = TRUE
argument to simulate in parallel. Here
I’ll provide an example simulating an A-Cc curve.
# We'll use the `replace` argument to enter multiple atmospheric CO2 concentrationsbake_par <- make_bakepar()constants <- make_constants(use_tealeaves = FALSE)enviro_par <- make_enviropar(replace = list(C_air = set_units(seq(1, 200, length.out = 20), "Pa")), use_tealeaves = FALSE)leaf_par <- make_leafpar(use_tealeaves = FALSE)ph <- photosynthesis(leaf_par, enviro_par, bake_par, constants,use_tealeaves = FALSE, progress = FALSE,quiet = TRUE, parallel = TRUE)# Plot C_c versus Alibrary(ggplot2)## Drop units for plottingph %<>% mutate_if(~ is(.x, "units"), drop_units)ggplot(ph, aes(C_chl, A)) +geom_line(size = 2) +xlab(expression(paste(C[chl], " [Pa]"))) +ylab(expression(paste("A [", mu, "mol ", m^-2~s^-1, "]"))) +theme_bw() +NULL
In experiments, leaf temperature can be kept close to air temperature,
but in nature, leaf temperature can be quite a bit different than air
temperature in the shade depending on environmental and leaf parameters.
If use_tealeaves = TRUE
, photo()
and photosynthesis()
will call on
the tealeaves
package to calculate leaf temperature using an energy balance model.
# You will need to set use_tealeaves = TRUE when making parameters because additional parameters are needed for tealeaves.bake_par <- make_bakepar()constants <- make_constants(use_tealeaves = TRUE)enviro_par <- make_enviropar(replace = list(T_air = set_units(seq(288.15, 313.15, 1), K)), use_tealeaves = TRUE)leaf_par <- make_leafpar(replace = list(g_sc = set_units(c(2, 4), umol/m^2/s/Pa)), use_tealeaves = TRUE)ph <- photosynthesis(leaf_par, enviro_par, bake_par, constants,use_tealeaves = TRUE, progress = FALSE,quiet = TRUE, parallel = TRUE)# Plot temperature and photosynthesislibrary(ggplot2)## Drop units for plottingph %<>%mutate_if(~ is(.x, "units"), drop_units) %>%mutate(`g[s]` = ifelse(g_sc == 2, "low", "high"))ggplot(ph, aes(T_air, T_leaf, color = `g[s]`)) +geom_line(size = 2, lineend = "round") +geom_abline(slope = 1, intercept = 0, linetype = "dotted") +scale_color_discrete(name = expression(g[s])) +xlab(expression(paste(T[air], " [K]"))) +ylab(expression(paste(T[leaf], " [K]"))) +theme_bw() +NULL
ggplot(ph, aes(T_air, A, color = `g[s]`)) +geom_line(size = 2, lineend = "round") +scale_color_discrete(name = expression(g[s])) +xlab(expression(paste(T[leaf], " [K]"))) +ylab(expression(paste("A [", mu, "mol ", m^-2~s^-1, "]"))) +theme_bw() +NULL
I welcome comments, criticisms, and especially contributions! GitHub issues are the preferred way to report bugs, ask questions, or request new features. You can submit issues here:
https://github.com/cdmuir/photosynthesis/issues
citation(package = 'photosynthesis')
progress = TRUE
to show
progress bar with estimated time remaining.