plot.prebas: Plot PREBAS outputs

In ForModLabUHel/Rprebasso: PRELES, YASSO and PREBAS models

Plot PREBAS outputs

Description

This function plots the outputs of PREBAS model

Usage

plot.prebas(x, variableIDs=NA, siteIDs=NA, layerIDs=NA, leg=T, layerNam = NA, obsData=NA)

Arguments

x	a prebas or multiSitePrebas object.
variableIDs	a numeric vector indicating the output variables IDs to plot. See list below.
siteIDs	a numeric vector indicating the site IDs (only for a multiSitePrebas object).
layerIDs	a numeric vector indicating the layer IDs to plot.
leg	logical. If TRUE the legend is included in the plots.
layerNam	a character vector with the layer names.
obsData	a matrix with observed data. Rows are observations; Columns are 7: site IDs, layer IDs, the year of observation from the start of the simulations, variable IDs, the actual value observed, sd of the observation (if available).

Details

List of output variables:

1."siteID"
2."climID"
3."sitetype"
4."species"
5."ETS" effective temperature sums
6."P0" Potential annual gross primary production (gC m-2 y-1)
7."age" Age of the layer (years)
8."Respi_m /10000." (kgC m-2 y-1)
9."Respi_tot" Autotrophic respiration (gC m-2 y-1)
10."GPP/1000" Total GPP (kgC ha-1 y-1)
11."H" Layer average height (m)
12."D" Layer average diameter at breast height (cm)
13."BA" Layer basal area (m-2 ha-1)
14."Hc_base" Base of crown height (m)
15."Cw" Crorn width (m)
16."Lc" Length of the crown (m)
17."N" Layer density
18."npp" net primary production (gC m-2 y-1)
19."leff" Effective leaf area
20."keff" Effective light extintion coefficient
21."lproj" Projected leaf area
22."ET_preles" Annual evapotranspiration (mm m-2)
23."weight" Layer weight on photosynthesis
24."Wbranch" Branch biomass (kgC ha-1)
25."WfineRoots" Fine roots biomass (kgC ha-1)
26."Litter_fol" Foliage litter (kgC ha-1)
27."Litter_fr" Fine root litter (kgC ha-1)
28."Litter_branch" Branch litter (kgC ha-1)
29."Litter_wood" Woody litter (kgC ha-1)
30."V" Layer volume (m3 ha-1)
31."Wstem" Stem Biomass (kgC ha-1)
32."W_croot" Course root Biomass (kgC ha-1)
33."wf_STKG" Foliage biomass (kgC ha-1)
34."wf_treeKG" Foliage biomass of the average tree (kgC ha-1)
35."B_tree" Basal area of average tree (m2 ha-1)
36."Light" light interseption
37."Vharvested" harvested volume (m3 ha-1)
38."Vtot" total volume of the Layer considering also dead trees and harvested volume (m3 ha-1)
39."soilC" totaal soil carbon (kgC ha-1)
40."aSW" average available soil water (mm m-2)
41."summerSW" summer soil water (mm m-2)
42."Vmort" volume of dead trees (m3 ha-1)
43."gross growth" (m3 ha-1 y-1)
44."GPPspecies" Gross primary production per layer (gC m-2 y-1)
45."Rh species" (gC m-2 y-1)
46."NEP sp" Net ecosystem exchange (gC m-2 y-1)

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x, variables = NA, sites = NA, speciesIDs = NA, leg = T,
    speciesNam = NA, data = NA)
{
    varNam <- getVarNam()
    if (any(variables == "all") | anyNA(variables))
        variables <- c(5, 6, 8:18, 22, 24:34, 37:46)
    if (inherits(x, "prebas")) {
        if (anyNA(speciesIDs))
            speciesIDs <- 1:dim(x$output)[3]
        nSp <- length(speciesIDs)
        if (anyNA(speciesNam))
            speciesNam <- as.character(paste("sp", 1:nSp))
        count <- 0
        if (length(variables) > 1)
            par(mfrow = c(2, 3))
        else par(mfrow = c(1, 1))
        for (var in variables) {
            count <- count + 1
            plot(x$output[, var, speciesIDs[1], 1], type = "l",
                xaxt = "n", main = varNam[var], ylab = "units",
                xlab = "age (y)", col = speciesIDs[1], ylim = c(min(x$output[,
                  var, , 1]), max(x$output[, var, , 1])))
            if (nSp > 1)
                for (ij in speciesIDs[2:nSp]) lines(x$output[,
                  var, ij, 1], col = ij)
            axis(1, at = seq(1, (dim(x$output)[1]), length.out = 6),
                labels = x$output[seq(1, (dim(x$output)[1]),
                  length.out = 6), 7, 1, 1])
            if (leg == TRUE)
                legend("topleft", c(speciesNam[speciesIDs]),
                  lty = 1, col = 1:nSp)
            if (count%%6 == 0 & var != tail(variables, n = 1))
                pause()
        }
    }
    if (inherits(x, "multiPrebas")) {
        if (anyNA(speciesIDs))
            speciesIDs <- 1:dim(x$multiOut)[4]
        nSp <- length(speciesIDs)
        if (anyNA(speciesNam))
            speciesNam <- as.character(paste("sp", 1:nSp))
        if (anyNA(sites))
            sites <- 1:dim(x$multiOut)[1]
        for (iz in sites) {
            count <- 0
            if (length(variables) > 1)
                par(mfrow = c(2, 3))
            else par(mfrow = c(1, 1))
            for (var in variables) {
                plot(x$multiOut[iz, , var, speciesIDs[1], 1],
                  type = "l", xaxt = "n", main = varNam[var],
                  ylab = "units", xlab = "age (y)", col = speciesIDs[1],
                  ylim = c(min(x$multiOut[iz, , var, , 1]), max(x$multiOut[iz,
                    , var, , 1])))
                if (nSp > 1)
                  for (ij in speciesIDs[2:nSp]) lines(x$multiOut[iz,
                    , var, ij, 1], col = ij)
                axis(1, at = seq(1, (dim(x$multiOut)[2]), length.out = 6),
                  labels = x$multiOut[iz, seq(1, (dim(x$multiOut)[2]),
                    length.out = 6), 7, 1, 1])
                if (leg == TRUE)
                  legend("topleft", c(speciesNam[speciesIDs]),
                    lty = 1, col = speciesIDs)
                if (count%%6 == 0)
                  title(paste("Site:", x$multiOut[iz, 1, 1, 1,
                    1]), line = -22, outer = TRUE, cex.main = 2)
                count <- count + 1
                if (count%%6 == 0 & var != tail(variables, n = 1))
                  pause()
            }
            if (length(sites) > 1 & iz != tail(sites, n = 1))
                pause()
        }
    }
  }

ForModLabUHel/Rprebasso documentation built on April 13, 2025, 10:48 a.m.