out.data: Generating TDM output
In TREXr: Tree Sap Flow Extractor

Description Usage Arguments Details Value Examples

Generates relevant outputs from the sap flux density (SFD) values. This function provides both Fd (SFD expressed in mmol m-2 s-1) and crown conductance values (Gc; an analogue to stomatal conductance) in an easily exportable format. Additionally, the function can perform environmental filtering on Fd and Gc and model Gc sensitivity to vapour pressure deficit (VPD). The user can choose between in- (method = "env.filt") or excluding (method = "stat") environmental filtering on the Gc and adjust the filter threshold manually.

out.data(
  input,
  vpd.input,
  sr.input,
  prec.input,
  peak.hours = c(10:14),
  low.sr = 150,
  peak.sr = 300,
  vpd.cutoff = 0.5,
  prec.lim = 1,
  method = "env.filt",
  max.quant = 1,
  make.plot = TRUE
)

`input`	An `is.trex`-compliant time series from `tdm_cal.sfd` outputs (e.g., `X$sfd.mw$sfd`)
`vpd.input`	An `is.trex`-compliant object an individual series of VPD in kPa (see vpd). The extent and temporal resolution should be equal to input. Use `dt.steps` to correct if needed.
`sr.input`	An `is.trex`-compliant object of an individual series of solar irradiance (e.g. either PAR or global radiation; see `sr`). The extent and temporal resolution should be equal to input. Use `dt.steps` to correct if needed. This data is only needed when applying the "env.filt" method.
`prec.input`	An `is.trex`-compliant object of daily precipitation in mm d-1 (see `preci`). The extent should be equal to input with a daily temporal resolution. Use `dt.steps` to correct if needed. This data is only needed when applying the "env.filt" method.
`peak.hours`	Numeric vector with hours which should be considered as peak-of-the-day hours (default = `c(10:14)`). This variable is only needed when the "stat" method is selected.
`low.sr`	Numeric threshold value in the unit of the sr.input time-series (e.g., W m-2) to exclude cloudy days which impact Gc (default = 150 W m-2). This variable is only needed when the "env.filt" method is selected.
`peak.sr`	Numeric threshold value in the unit of the sr.input time-series (e.g., W m-2) to exclude hours which are not considered as peak-of-the-day hours (default = 300 W m-2). This variable is only needed when the "env.filt" method is selected.
`vpd.cutoff`	Numeric threshold value in kPa for peak-of-the-day mean VPD to eliminate unrealistic and extremely high values of Gc due to low VPD values or high values of Gc (default = 0.5 kPa).
`prec.lim`	Numeric threshold value in mm d-1 for daily precipitation to remove rainy days (default = 1 mm d-1). This variable is only needed when "env.filt" method is selected.
`method`	Character string indicating whether precipitation and solar irradiance data should be used to determined peak-of-the-day Gc values and filter the daily Gc values ("env.filt") or not ("stat"; default). When `"env.filt"` is selected, `input`, `vpd.input`, `sr.input`, `prec.input`, `peak.sr`, `low.sr`, `vpd.cutoff` and `prec.lim` have to be provided. When `"stat"` is selected only `input`, `vpd.input` and `peak.hours`.
`max.quant`	Numeric, defining the quantile of the Gc data which should be considered as GC.max (default = 1).
`make.plot`	Logical; if `TRUE`, a plot is generated presenting the response of Gc to VPD.

Various relevant outputs can be derived from the SFD data. This function provides the option to recalculate SFD to Fd (expressed in mmol m-2 s-1) and crown conductance (according to Pappas et al. 2018). Gc is estimated per unit sapwood area, where GC = Fd / VPD (in kPa), assuming that i) the stem hydraulic capacitance between the height of sensor and the leaves is negligible, and ii) that the canopy is well coupled to the atmosphere. In order to reduce the effect of stem hydraulic capacitance, peak-of-the-day Gc are solely considered for calculating daily average Gc. Peak-of-the-day conditions are defined by peak.hours or peak.sr. Moreover, to analyse the relationship between Gc and environmental measurements (e.g., VPD), the daily mean peak-of-the-day Gc values can be restricted to: i) non-cloudy days (see low.sr), to reduce the impact of low irradiance on Gc, ii) non-rainy days (see prec.lim), as wet leaves are not well coupled to the atmosphere, and iii) daily mean peak-of-the-day Gc great then a threshold (see vpd.cutoff), to eliminate unrealistically high Gc values due to low Fd or VPD values (when method = "env.filt"). Moreover, the sensitivity of the daily mean peak-of-the-day Gc to VPD is modelled by fitting the following model:

GC = α + β VPD^(-0.5)

Besides using the raw daily mean peak-of-the-day Gc values, the function also applies a normalization where daily mean peak-of-the-day Gc is standardized to the maximum conductance (GC.max; see max.quant).

A named list of data.frame objects, containing the following items:

raw: A data.frame containing the input data and filtered values. Columns include the timestamp [,"timestamp"] (e.g., "2012-01-01 00:00:00"), year of the data [,"year"], day of year [,"doy"], input solar radiance data [,"sr"], daily average radiance data [,"sr"], input vapour pressure deficit data [,"vpd"], isolated peak-of-the-day vapour pressure deficit values [,"vpd.filt"], input daily precipitation [,"prec.day"], sap flux density expressed in mmol m-2 s-1 [,"fd"], crown conductance expressed in mmol m-2 s-1 kPa-1 [,"gc"], and the filtered crown conductance [,"gc.filt"]
peak.mean: A data.frame containing the daily mean crown conductance values. Columns include the timestamp [,"timestamp"] (e.g., "2012-01-01"), peak-of-the-day vapour pressure deficit [,"vpd.filt"], the filtered crown conductance mmol m-2 s-1 kPa-1 [,"gc.filt"], and the normalized crown conductance according to the maximum crown conductance [,"gc.norm"].
sum.mod: A model summary object (see summary()) of the model between VPD and Gc.
sum.mod.norm: A model summary object (see summary()) of the model between VPD and Gc/GC.max.

#Gc response function
#Gc response function
raw   <- is.trex(example.data(type="doy"), tz="GMT",
                 time.format="%H:%M", solar.time=TRUE,
                 long.deg=7.7459, ref.add=FALSE)

input <- dt.steps(input=raw, start="2013-05-01 00:00", end="2013-11-01 00:00",
                   time.int=15, max.gap=60, decimals=10, df=FALSE)

input[which(input<0.2)]<- NA
input <- tdm_dt.max(input, methods=c("dr"), det.pd=TRUE, interpolate=FALSE,
                 max.days=10, df=FALSE)

output.data<- tdm_cal.sfd(input,make.plot=TRUE,df=FALSE,wood="Coniferous", decimals = 6)

input<- output.data$sfd.dr$sfd

output<- out.data(input=input, vpd.input=vpd, sr.input=sr, prec.input=preci,
                  low.sr = 150, peak.sr=300, vpd.cutoff= 0.5, prec.lim=1,
                  method="env.filt", max.quant=0.99, make.plot=TRUE)
head(output)