/optimal_vcmax_R

calculate optimal vcmax in R as in Smith et al. Photosynthetic capacity is optimized to the environment. Ecology Letters.

Primary LanguageR

optimal_vcmax_R

Repository Description

This repository contains the R functions necessary for calculating optimal vcmax in R as first described in Smith et al. (2019) Global photosynthetic capacity is optimized to the environment. Ecology Letters 22(3): 506-517. doi: 10.1111/ele.13210. link.

Summary of main files and folders

The script calc_optimal_vcmax.R contains code for the optimal vcmax function.' The function will calculate optimal vcmax, optimal jmax, and the optimal jmax/vcmax ratio. The inputs required are temperature, PAR, VPD, elevation, and an estimate for the quantum efficiency of photosynthetic electron transport, and the curvature of the light response curve of photosynthetic electron transport.

Th folder functions contains the functions necessary to run the calc_optimal_vcmax.R script.

The script test_calc_optimal_vcmax.R will test the functions. It is suggested that users run this script first to ensure the function will run properly.

All function descriptions, including parameter descriptions, can be found in the script files.

Model Inputs

  • pathway: photosynthetic pathway, either "C3" or "C4"
  • tg_c: acclimated temperature (degC)
  • z: elevation (m)
  • vpdo: vapor pressure deficit at sea level (kPa)
  • cao: atmospheric CO2 at sea level (umol mol-1)
  • oao: atmospheric O2 at sea level (ppm)
  • paro: photosynthetically active radiation at sea level (µmol m-2 s-1)
  • q0_resp: yes or no, use the q0 response curve calculation
  • q0_int: intercept for the q0 response curve calculation
  • q0: quantum efficiency of photosynthetic electron transport (mol/mol)
  • theta: curvature of the light response of electron transport (unitless)
  • chi: leaf intercellular to atmospheric CO2 ratio (ci/ca) (unitless), defaults to "NA"
  • f: fraction of year in growing season
  • lma: leaf mass area (g m-2), defaults to "NA"

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DOI

Contact

Any questions or issues can be submitted via GitHub or directed to Nick Smith (nick.smith@ttu.edu).