biometrics (version 1.0.1)

domvar: Function to compute the dominant stand-level variable based on a sample plot data.

Description

Computes the so-called dominant stand-level variable, corresponding to the average of a tree-level variable for the 100 largest sorting-tree-level diameter trees in 1-ha.

Usage

domvar(
  data = data,
  var.int = var.int,
  var.sort = var.sort,
  plot.area = plot.area
)

Value

The main output is the calculated dominant stand-variable for the given sample plot.

Arguments

data

data frame having the tree list of a sample plot.

var.int

column name with the tree-level variable of interest (e.g., height).

var.sort

column name with the tree-level variable for defining the

plot.area

column name having the plot area, in square meters.

Author

Christian Salas-Eljatib.

Details

The original function was written by Dr Oscar García for computing top height, and the corresponding reference is provided. Nevertheless, several changes were applied, thus the current function provide a broader application. Regardless, the function aims to calculate a "dominant" stand-level variable by taking into account the plot area. Thus, requires having a dataframe having both the variable of interest (e.g., height) and the sorting variable used for the computation (e.g., diameter) for all trees in a sample plot, as well as, the plot area.

References

- Garcia O, Batho A. 2005. Top height estimation in lodgepole pine sample plots. Western Journal of Applied forestry 20(1):64-68.

Examples

##Creates a fake dataframe
set.seed(45)
x <- round(rnorm(20,mean=45,sd=10),1); y=round(1.3+35*(1-exp(-.07*x)),1)
df<-data.frame(dap=x,atot=y)
head(df)
datana::descstat(df)
##Using the domvar function
domvar(data=df,var.int="atot",var.sort="dap",plot.area=500)