transp_stomatalregulation: Stomatal regulation

Description

Set of high-level functions used in the calculation of stomatal conductance and transpiration. Function transp_profitMaximization calculates gain and cost functions, as well as profit maximization from supply and photosynthesis input functions. Function transp_stomatalRegulationPlot produces a plot with the cohort supply functions against water potential and a plot with the cohort photosynthesis functions against water potential, both with the maximum profit values indicated.

Usage

transp_profitMaximization(
  supplyFunction,
  photosynthesisFunction,
  Gswmin,
  Gswmax
)
transp_stomatalRegulationPlot(
  x,
  meteo,
  day,
  timestep,
  latitude,
  elevation,
  slope = NA,
  aspect = NA,
  type = "E"
)

Value

Function transp_profitMaximization returns a list with the following elements:

Cost: Cost function [0-1].
Gain: Gain function [0-1].
Profit: Profit function [0-1].
iMaxProfit: Index corresponding to maximum profit (starting from 0).

Arguments

supplyFunction: Water supply function (see hydraulics_supplyFunctionNetwork).
photosynthesisFunction: Function returned by photo_photosynthesisFunction().
Gswmin, Gswmax: Minimum and maximum stomatal conductance to water vapour (mol·m-2·s-1).
x: An object of class spwbInput built using the 'Sperry' transpiration mode.
meteo: A data frame with daily meteorological data series (see spwb).
day: An integer to identify a day (a row) within meteo.
timestep: An integer between 1 and ndailysteps specified in x (see defaultControl).
latitude: Latitude (in degrees).
elevation, slope, aspect: Elevation above sea level (in m), slope (in degrees) and aspect (in degrees from North).
type: A string with plot type, either "E" (transpiration flow), "Ag" (gross photosynthesis), "An" (net photosynthesis), "Gsw" (stomatal conductance to water vapour), "T" (temperature) or "VPD" (leaf vapour pressure deficit).

Author

Miquel De Cáceres Ainsa, CREAF

References

Sperry, J. S., M. D. Venturas, W. R. L. Anderegg, M. Mencuccini, D. S. Mackay, Y. Wang, and D. M. Love. 2017. Predicting stomatal responses to the environment from the optimization of photosynthetic gain and hydraulic cost. Plant Cell and Environment 40, 816-830 (doi: 10.1111/pce.12852).

Examples

Run this code

#Load example daily meteorological data
data(examplemeteo)

#Load example plot plant data
data(exampleforest)

#Default species parameterization
data(SpParamsMED)

#Define soil with default soil params (4 layers)
examplesoil <- defaultSoilParams(4)

#Initialize control parameters
control <- defaultControl(transpirationMode="Sperry")

#Initialize input
x2 <- spwbInput(exampleforest,examplesoil, SpParamsMED, control)

# Stomatal VPD curve and chosen value for the 12th time step at day 100
transp_stomatalRegulationPlot(x2, examplemeteo, day=100, timestep = 12,
                              latitude = 41.82592, elevation = 100, type="VPD")

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