It calculates pairwise competition coefficients as overlap of Gaussian resource utilization curve
Gaussian.competition.kernel(
trait.values,
trait.compet = "trait.b",
sigma.b = 0.03,
...
)Dataframe of all traits
Name of trait related to resource use
Width of Gaussian kernel
Any additional parameters
It assumes that each species has Gaussian resource utilization curve: $$\exp(\frac{(x-trait.value)^2}{sigma.b})$$ where: x = quality of resource (e.g. seed size or rooting depth
Optima of curves depend on trait value related to resource use,
while standard deviation is the same for all species (note that for technical reason
parameter sigma.b is twice of the common sqared s.d.).
Pairwise competition coefficients are calculated as overlap of
resource utilization functions (MacArthur & Levins 1967).See details in
vignette("competition")
MacArthur R, Levins R (1967) The Limiting Similarity, Convergence, and Divergence of Coexisting Species. The American Naturalist 101: 377-385. 10.1086/282505