rpmodel provides an implementation of the P-model (Prentice et al., 2014; Wang et al., 2017; Stocker et al., 2019), which predicts acclimated photosynthetic parameters, assimilation, and dark respiration rates as a function of the environment. The main function is rpmodel() which returns a list of variables that are mutually consistent within the theory of the P-model (see Theory, below). Further functions used within rpmodel() are also provided through the package.
This loads the rpmodel package and executes the rpmodel() function without \(J_{\text{max}}\) limitation (argument method_jmaxlim = "none"), and with a temperature-independent quantum yield efficiency (argument do_ftemp_kphio = FALSE):
library(rpmodel)
out_pmodel <- rpmodel(
tc = 20 # temperature, deg C
vpd = 1000 # Pa,
co2 = 400 # ppm,
elv = 0 # m.a.s.l.,
kphio = 0.05 # quantum yield efficiency,
beta = 146, # unit cost ratio a/b,
fapar = 1 # fraction ,
ppfd = 300 # mol/m2/d,
method_optci = "prentice14",
method_jmaxlim = "none",
do_ftemp_kphio = FALSE
)
print( out_pmodel )rpmodel is available on CRAN here.
To install and load the rpmodel package (development release) run the following command in your R terminal:
if(!require(devtools)){install.packages(devtools)}
devtools::install_github( "stineb/rpmodel", build_vignettes = TRUE )
library(rpmodel)Benjamin Stocker benjamin.stocker@gmail.com
Stocker, B. D., Wang, H., Smith, N. G., Harrison, S. P., Keenan, T. F., Sandoval, D., Davis, T., and Prentice, I. C.: P-model v1.0: An optimality-based light use efficiency model for simulating ecosystem gross primary production, Geosci. Model Dev. Discuss., in review, 2019.
Wang, H., Prentice, I. C., Keenan, T. F., Davis, T. W., Wright, I. J., Cornwell, W. K.,Evans, B. J., and Peng, C.: Towards a universal model for carbon dioxide uptake by plants, Nat Plants, 3, 734–741, 2017.
Prentice, I. C., Dong, N., Gleason, S. M., Maire, V., and Wright, I. J.: Balancingthe costs of carbon gain and water transport: testing a new theoretical frameworkfor plant functional ecology, Ecology Letters, 17, 82–91, 10.1111/ele.12211, 2014.
This project was funded by Marie Sklodowska-Curie fellowship H2020-MSCA-IF-2015, project FIBER, grant number 701329.