rpmodel provides an implementation of the P-model (Prentice et al., 2014; Wang et al., 2017; Stocker et al., 2020) for predicting 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 Usage ). Further functions used within rpmodel() are also provided through the package.
This loads the rpmodel package and executes the rpmodel() function without 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 latest version of the rpmodel package (development release, not yet on CRAN) 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 [email protected]
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., 13, 1545–1581, https://doi.org/10.5194/gmd-13-1545-2020, 2020.
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.