leafdispersion: Leaf dispersion of 3D plants
In YplantQMC: Plant architectural analysis with Yplant and QuasiMC.

Description Usage Arguments Value Author(s) References Examples

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.

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

`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.

A list with the following components:

Ok: Observed distance to k nearest neighbors
Ek_noedge: Expected distance to k nearest neighbors, for random distribution; no edge correction.
Ek_edge: As above, but with an edge correction
Ek_edgeSD: Standard deviation among replicates of Ek_edge
kneighbors: Number of neighbors for distance calculation
disp_edge: Edge-corrected leaf dispersion (as in Duursma et al. 2012).
disp_noedge: Non edge-corrected leaf dispersion

Remko Duursma

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.