High-level sub-models representing transpiration, plant hydraulics, photosynthesis and water relations within plants.
Usage
transp_transpirationSperry(
x,
meteo,
day,
latitude,
elevation,
slope,
aspect,
canopyEvaporation = 0,
snowMelt = 0,
soilEvaporation = 0,
herbTranspiration = 0,
stepFunctions = NA_integer_,
modifyInput = TRUE
)
transp_transpirationSureau(
x,
meteo,
day,
latitude,
elevation,
slope,
aspect,
canopyEvaporation = 0,
snowMelt = 0,
soilEvaporation = 0,
herbTranspiration = 0,
modifyInput = TRUE
)
transp_transpirationGranier(
x,
meteo,
day,
latitude,
elevation,
slope,
aspect,
modifyInput = TRUE
)Arguments
- x
An object of class
spwbInputorgrowthInput, built using the 'Granier', 'Sperry' or 'Sureau' transpiration modes.- meteo
A data frame with daily meteorological data series (see
spwb).- day
An integer to identify a day (row) within the
meteodata frame.- latitude
Latitude (in degrees).
- elevation, slope, aspect
Elevation above sea level (in m), slope (in degrees) and aspect (in degrees from North).
- canopyEvaporation
Canopy evaporation (from interception) for
day(mm).- snowMelt
Snow melt values for
day(mm).- soilEvaporation
Bare soil evaporation for
day(mm).- herbTranspiration
Transpiration of herbaceous plants for
day(mm).- stepFunctions
An integer to indicate a simulation step for which photosynthesis and profit maximization functions are desired.
- modifyInput
Boolean flag to indicate that the input
xobject is allowed to be modified during the simulation.
Value
A list with the following elements:
"cohorts": A data frame with cohort information, copied fromspwbInput."Stand": A vector of stand-level variables."Plants": A data frame of results for each plant cohort. When usingtransp_transpirationGranier, element"Plants"includes:"LAI": Leaf area index of the plant cohort."LAIlive": Leaf area index of the plant cohort, assuming all leaves are unfolded."AbsorbedSWRFraction": Fraction of SWR absorbed by each cohort."Transpiration": Transpirated water (in mm) corresponding to each cohort."GrossPhotosynthesis": Gross photosynthesis (in gC/m2) corresponding to each cohort."psi": Water potential (in MPa) of the plant cohort (average over soil layers)."DDS": Daily drought stress [0-1] (relative whole-plant conductance).
transp_transpirationSperryortransp_transpirationSureau, element"Plants"includes:"LAI": Leaf area index of the plant cohort."LAIlive": Leaf area index of the plant cohort, assuming all leaves are unfolded."Extraction": Water extracted from the soil (in mm) for each cohort."Transpiration": Transpirated water (in mm) corresponding to each cohort."GrossPhotosynthesis": Gross photosynthesis (in gC/m2) corresponding to each cohort."NetPhotosynthesis": Net photosynthesis (in gC/m2) corresponding to each cohort."RootPsi": Minimum water potential (in MPa) at the root collar."StemPsi": Minimum water potential (in MPa) at the stem."StemPLC": Proportion of conductance loss in stem."LeafPsiMin": Minimum (predawn) water potential (in MPa) at the leaf (representing an average leaf)."LeafPsiMax": Maximum (midday) water potential (in MPa) at the leaf (representing an average leaf)."LeafPsiMin_SL": Minimum (predawn) water potential (in MPa) at sunlit leaves."LeafPsiMax_SL": Maximum (midday) water potential (in MPa) at sunlit leaves."LeafPsiMin_SH": Minimum (predawn) water potential (in MPa) at shade leaves."LeafPsiMax_SH": Maximum (midday) water potential (in MPa) at shade leaves."dEdP": Overall soil-plant conductance (derivative of the supply function)."DDS": Daily drought stress [0-1] (relative whole-plant conductance)."StemRWC": Relative water content of stem tissue (including symplasm and apoplasm)."LeafRWC": Relative water content of leaf tissue (including symplasm and apoplasm)."LFMC": Live fuel moisture content (in percent of dry weight)."WaterBalance": Plant water balance (extraction - transpiration).
"Extraction": A data frame with mm of water extracted from each soil layer (in columns) by each cohort (in rows). The sum of a given row is equal to the total extraction of the corresponding plant cohort."ExtractionPools": A named list with as many elements as plant cohorts, where each element is a matrix data with mm of water extracted from each layer (in columns) of the water pool of each cohort (in rows). The sum of a given matrix is equal to the total extraction of the corresponding plant cohort.The remaining items are only given by
transp_transpirationSperryortransp_transpirationSureau:"EnergyBalance": A list with the following elements:"Temperature": A data frame with the temperature of the atmosphere ('Tatm'), canopy ('Tcan') and soil ('Tsoil.1', 'Tsoil.2', ...) for each time step."CanopyEnergyBalance": A data frame with the components of the canopy energy balance (in W/m2) for each time step."SoilEnergyBalance": A data frame with the components of the soil energy balance (in W/m2) for each time step.
"RhizoPsi": Minimum water potential (in MPa) inside roots, after crossing rhizosphere, per cohort and soil layer."Sunlitleaves"and"ShadeLeaves": Data frames for sunlit leaves and shade leaves and the following columns per cohort:"LAI": Cumulative leaf area index of sunlit/shade leaves."Vmax298": Average maximum carboxilation rate for sunlit/shade leaves."Jmax298": Average maximum electron transport rate for sunlit/shade leaves.
"ExtractionInst": Water extracted by each plant cohort during each time step."PlantsInst": A list with instantaneous (per time step) results for each plant cohort:"E": A data frame with the cumulative transpiration (mm) for each plant cohort during each time step."Ag": A data frame with the cumulative gross photosynthesis (gC/m2) for each plant cohort during each time step."An": A data frame with the cumulative net photosynthesis (gC/m2) for each plant cohort during each time step."Sunlitleaves"and"ShadeLeaves": Lists with instantaneous (for each time step) results for sunlit leaves and shade leaves and the following items:"Abs_SWR": A data frame with instantaneous absorbed short-wave radiation (SWR)."Net_LWR": A data frame with instantaneous net long-wave radiation (LWR)."An": A data frame with instantaneous net photosynthesis (in micromol/m2/s)."Ci": A data frame with instantaneous intercellular CO2 concentration (in ppm)."GW": A data frame with instantaneous stomatal conductance (in mol/m2/s)."VPD": A data frame with instantaneous vapour pressure deficit (in kPa)."Temp": A data frame with leaf temperature (in degrees Celsius)."Psi": A data frame with leaf water potential (in MPa).
"dEdP": A data frame with the slope of the plant supply function (an estimation of whole-plant conductance)."RootPsi": A data frame with root crown water potential (in MPa) for each plant cohort during each time step."StemPsi": A data frame with stem water potential (in MPa) for each plant cohort during each time step."LeafPsi": A data frame with leaf (average) water potential (in MPa) for each plant cohort during each time step."StemPLC": A data frame with the proportion loss of conductance [0-1] for each plant cohort during each time step."StemRWC": A data frame with the (average) relative water content of stem tissue [0-1] for each plant cohort during each time step."LeafRWC": A data frame with the relative water content of leaf tissue [0-1] for each plant cohort during each time step."StemSympRWC": A data frame with the (average) relative water content of symplastic stem tissue [0-1] for each plant cohort during each time step."LeafSympRWC": A data frame with the relative water content of symplastic leaf tissue [0-1] for each plant cohort during each time step."PWB": A data frame with plant water balance (extraction - transpiration).
"LightExtinction": A list of information regarding radiation balance through the canopy, as returned by functionlight_instantaneousLightExtinctionAbsortion."CanopyTurbulence": Canopy turbulence (seewind_canopyTurbulence)."SupplyFunctions": IfstepFunctionsis not missing, a list of supply functions, photosynthesis functions and profit maximization functions.
Details
Three sub-models are available:
Sub-model in function
transp_transpirationGranierwas described in De Cáceres et al. (2015), and implements an approach originally described in Granier et al. (1999).Sub-model in function
transp_transpirationSperrywas described in De Cáceres et al. (2021), and implements a modelling approach originally described in Sperry et al. (2017).Sub-model in function
transp_transpirationSureauwas described for SurEau-Ecos v2.0 model in Ruffault et al. (2022).
References
De Cáceres M, Martínez-Vilalta J, Coll L, Llorens P, Casals P, Poyatos R, Pausas JG, Brotons L. (2015) Coupling a water balance model with forest inventory data to predict drought stress: the role of forest structural changes vs. climate changes. Agricultural and Forest Meteorology 213: 77-90 (doi:10.1016/j.agrformet.2015.06.012).
De Cáceres M, Mencuccini M, Martin-StPaul N, Limousin JM, Coll L, Poyatos R, Cabon A, Granda V, Forner A, Valladares F, Martínez-Vilalta J (2021) Unravelling the effect of species mixing on water use and drought stress in holm oak forests: a modelling approach. Agricultural and Forest Meteorology 296 (doi:10.1016/j.agrformet.2020.108233).
Granier A, Bréda N, Biron P, Villette S (1999) A lumped water balance model to evaluate duration and intensity of drought constraints in forest stands. Ecol Modell 116:269–283. https://doi.org/10.1016/S0304-3800(98)00205-1.
Ruffault J, Pimont F, Cochard H, Dupuy JL, Martin-StPaul N (2022) SurEau-Ecos v2.0: a trait-based plant hydraulics model for simulations of plant water status and drought-induced mortality at the ecosystem level. Geoscientific Model Development 15, 5593-5626 (doi:10.5194/gmd-15-5593-2022).
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
#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("Granier")
#Initialize input
x1 <- spwbInput(exampleforest,examplesoil, SpParamsMED, control)
# Transpiration according to Granier's model, plant water potential
# and plant stress for a given day
t1 <- transp_transpirationGranier(x1, examplemeteo, 1,
latitude = 41.82592, elevation = 100, slope = 0, aspect = 0,
modifyInput = FALSE)
#Switch to 'Sperry' transpiration mode
control <- defaultControl("Sperry")
#Initialize input
x2 <- spwbInput(exampleforest,examplesoil, SpParamsMED, control)
# Transpiration according to Sperry's model
t2 <- transp_transpirationSperry(x2, examplemeteo, 1,
latitude = 41.82592, elevation = 100, slope = 0, aspect = 0,
modifyInput = FALSE)
#Switch to 'Sureau' transpiration mode
control <- defaultControl("Sureau")
#Initialize input
x3 <- spwbInput(exampleforest,examplesoil, SpParamsMED, control)
# Transpiration according to Sureau model
t3 <- transp_transpirationSureau(x3, examplemeteo, 1,
latitude = 41.82592, elevation = 100, slope = 0, aspect = 0,
modifyInput = FALSE)
