BIOMASS (version 2.1.8)

summaryByPlot: Summarize by plot (or subplot) the posterior distribution of AGB values

Description

This function summarizes the matrix AGB_val given by the function AGBmonteCarlo() by plot. Or just do the sums for each plot of the AGB if the argument AGB_val is the resulting vector from the function computeAGB().

Usage

summaryByPlot(AGB_val, plot, drawPlot = FALSE, subplot = NULL)

Arguments

AGB_val

Matrix resulting from the function AGBmonteCarlo() (AGB_val element of the list), or just the output of the function AGBmonteCarlo(). Or the output of the function computeAGB()

plot

Vector with the code of plot

drawPlot

a logical to draw the plot (see Details)

subplot

Data frame, output of the function cutPlot()

Value

a data frame where:

• plot: the code of the plot

• AGB: AGB value at the plot level

• Cred_2.5: the quantile 2.5\

• Cred_97.5: the quantile 97.5\

If the subplot is set, the output is a list with the previous data frame and a simple features (sf) geometry object.

Details

If some trees belong to an unknown plot (i.e. NA value in the plot arguments), their AGB values are randomly assigned to a plot at each iteration of the AGB monte Carlo approach. Or discarded when using output from computeAGB().

The drawPlot argument is a logical that if it is set TRUE, a graph will appear with the plot given on absciss and the value of AGB on ordinate, the red segments are the quantile, if AGB_val is the result of the function AGBmonteCarlo(). If the subplot arguments is set and the drawPlot is set TRUE, a graph is drawn with the spatialisation of the plots.

Examples

# NOT RUN {
# Load a database
data(NouraguesHD)
data(KarnatakaForest)

# Modelling height-diameter relationship
HDmodel <- modelHD(D = NouraguesHD$D, H = NouraguesHD$H, method = "log2")

# Retrieving wood density values
KarnatakaWD <- getWoodDensity(KarnatakaForest$genus, KarnatakaForest$species,
  stand = KarnatakaForest$plotId
)

# Propagating errors
filt <- KarnatakaForest$plotId %in% c("BSP20", "BSP14")
resultMC <- AGBmonteCarlo(
  D = KarnatakaForest$D[filt], WD = KarnatakaWD$meanWD[filt],
  errWD = KarnatakaWD$sdWD[filt], HDmodel = HDmodel
)

plot <- KarnatakaForest$plotId[ filt ]

# The summary by plot
summaryByPlot(AGB_val = resultMC$AGB_simu, plot)

# The summary by plot for computeAGB
H <- retrieveH(KarnatakaForest$D[filt], model = HDmodel)$H
AGB <- computeAGB(KarnatakaForest$D[filt], WD = KarnatakaWD$meanWD[filt], H = H)
summaryByPlot(AGB, plot)
# }