FHD {leafR}R Documentation

Foliage Height Diversity

Description

Calculates the foliage height diversity (FHD) metric from abundances considered as per-voxel relative LAD values, as described in MacArthur and MacArthur (1961).

Usage

FHD(lad_profile, evenness = FALSE, LAD.threshold = -1)

Arguments

lad_profile

a data.frame including values of relative LAD at height intervals, output of the lad.profile function (use relative = TRUE)

evenness

boolean, defines whether FHD should be based on Shannon's diversity or evenness (Hill 1973). The default FALSE calculates Shannon diversity as the original FHD by MacArthur and MacArthur (1961); the alternative TRUE was recommended by Valbuena et al. (2012), and it calculates Shannon evenness dividing it by the natural logarithm of the number of number of voxels with LAD values above the threshold.

LAD.threshold

numerical (0,1), defines the minimum value of LAD for considering the relative leaf abundance of a voxel in FHD calculation. Defaults to the inverse of the total number of voxels.

Value

A numeric containing the Foliage Height Diversity calculated from the Leaf Area Density profile

References

Hill M. O. (1973) Diversity and evenness: a unifying notation and its consequences. Ecology. 54: 427–432. doi: 10.2307/1934352

MacArthur R.H., MacArthur J.W. (1961). On bird species diversity. Ecology 42: 594–598. doi: 10.2307/1932254

Valbuena R., Packalen P., Martín-Fernández S., Maltamo M. (2012) Diversity and equitability ordering profiles applied to the study of forest structure. Forest Ecology and Management 276: 185–195. doi: 10.1016/j.foreco.2012.03.036

Examples

# Get the example laz file
normlas.file = system.file("extdata", "lidar_example.laz", package="leafR")

# Calculate LAD from voxelization
VOXELS_LAD = lad.voxels(normlas.file,
                        grain.size = 2)

# Calculate the LAD profile
lad_profile = lad.profile(VOXELS_LAD, relative = TRUE)

FHD(lad_profile, evenness = FALSE)
FHD(lad_profile, evenness = TRUE)


[Package leafR version 0.3.5 Index]