YplantQMC (version 0.6-6)

leafdispersion: Leaf dispersion of 3D plants

Description

This function calculates the leaf dispersion for 3D plants, following Duursma et al. (2012).

The method is based on the mean distance to k nearest neighbors in 3D. The function 'leafdispersion' computes this observed mean distance (Ok) for a plant (an object of class plant3d), as well as for a square box with randomly distributed leaves at the same leaf area density.

Usage

leafdispersion(plant, kneighbors = 5, nreplicate = 10, nleaves = NA, crownvol = NA)

Arguments

plant

An object of class 'plant3d'.

kneighbors

Number of neighbors to be used.

nreplicate

For the random distribution, the number of replicates to simulate.

crownvol, nleaves

Crown volume and number of leaves - optional. If not provided, they are calculated from the 'plant' object.

Value

A list with the following components:

list("Ok")

Observed distance to k nearest neighbors

list("Ek_noedge")

Expected distance to k nearest neighbors, for random distribution; no edge correction.

list("Ek_edge")

As above, but with an edge correction

list("Ek_edgeSD")

Standard deviation among replicates of Ek_edge

list("kneighbors")

Number of neighbors for distance calculation

list("disp_edge")

Edge-corrected leaf dispersion (as in Duursma et al. 2012).

list("disp_noedge")

Non edge-corrected leaf dispersion

References

Duursma, R.A., D.S. Falster, F. Valladares, F.J. Sterck, R.W. Pearcy, C.H. Lusk, K.M. Sendall, M. Nordenstahl, N.C. Houter, B.J. Atwell, N. Kelly, J.W.G. Kelly, M. Liberloo, D.T. Tissue, B.E. Medlyn and D.S. Ellsworth. 2012. Light interception efficiency explained by two simple variables: a test using a diversity of small- to medium-sized woody plants. New Phytologist. 193:397-408.

Examples

# Leafdispersion for the Toona plant
leafdispersion(toona)