kernel: Competition Kernel Functions
In siplab: Spatial Individual-Plant Modelling

kernel

R Documentation

Competition Kernel Functions

Description

Functions representing the effect of a competitor on a subject plant, depending on distance and plant sizes (marks). For use in pairwise().

Note: In previous versions of siplab the function names had .ker in place of _ker.

Usage

powers_ker(imarks, jmarks, dists, dranks, par = list(pi=1, pj=1,
    pr=1, smark = 1))

staebler_ker(imarks, jmarks, dists, dranks, par = list(k=0.1, p=1,
    smark=1))

spurr_ker(imarks, jmarks, dists, dranks, par = list(type=1,
    smark=1))

Arguments

`imarks`	Marks for the subject plant, a 1-row data frame.
`jmarks`	Data frame with marks for competitors
`dists`	Vector of distances between the subject plant and the competitors.
`dranks`	Distance ranks.
`par`	List of parameters.

Details

The values of par are taken from the argument kerpar of pairwise(), if not NULL.

smark in par must be 1 or “mark” if there is only one mark. If the marks are a data frame, smark must be the number or name of the column with the plant size variable.

powers_ker() is a general form that includes many examples from the literature. If Si is the size of the subject plant, Sj the size of the competitor, and R is the distance between them, then this kernel is (Sj^pj / Si^pi) / R^pr. For instance, the popular Hegyi's index corresponds to pi=1, pj=1, pr=1. This and other examples could be coded directly if computational efficiency is important, see the example below.

staebler_ker() is the width of the overlap of zones of influence (ZOI), used by Staebler in 1951. Assumes that the ZOI radius is k S^p, where S is size.

spurr_ker() is an example of an index that depends on distance ranks: equations (9.5a), (9.5b) of Burkhart and Tomé (2012).

Competition kernels seem to be limited only by the researchers imagination. Others can be written following these examples.

Value

Vector of length equal to the length of dists.

Author(s)

Oscar García.

References

https://github.com/ogarciav/siplab

Burkhart, H. E. and Tomé, M. (2012) Modeling Forest Trees and Stands. Springer.

García, O. “Siplab, a spatial individual-based plant modelling system”. Computational Ecology and Software 4(4), 215-222. 2014.

Examples

# Originally Hegyi added one foot to the distance:
hegyiorig_ker <- function(imarks, jmarks, dists, ...) {
# Assume coordinates in meters, and a single mark (dbh)
    (jmarks$mark / imarks$mark) / (dists + 0.30481)
}

siplab documentation built on March 18, 2022, 6:53 p.m.