competitive_ability {cxr}R Documentation

Competitive ability among pairs of species

Description

Computes the competitive ability among two species, as defined by Hart et al. (2018). This metric, as others in MCT, is model-specific; the formulation for a series of Lotka-Volterra-like models is given in table A1 of Hart et al. (2018). We include in cxr by default the formulation for Beverton-Holt, Ricker, Law-Watkinson, and Lotka-Volterra families.

Usage

competitive_ability(
  cxr_multifit = NULL,
  cxr_sp1 = NULL,
  cxr_sp2 = NULL,
  lambda = NULL,
  pair_matrix = NULL,
  model_family = NULL
)

Arguments

cxr_multifit

cxr_pm_multifit object, with parameters for a series of species.

cxr_sp1

cxr_pm_fit object giving the parameters from the first species.

cxr_sp2

cxr_pm_fit object giving the parameters from the second species.

lambda

numeric lambda value of the focal species.

pair_matrix

2x2 matrix with intra and interspecific interaction coefficients between the focal and competitor species.

model_family

model family for which to calculate competitive ability.

Details

The function, as in avg_fitness_diff and niche_overlap, accepts three different parameterizations:

If the third parameterization is used, the function will try to find a model-specific function for obtaining the competitive ability, by looking at the 'model_family' parameter. If this specific function is not found, it will resort to the standard Lotka-Volterra formulation (lambda - 1 in the numerator term, Hart et al. 2018). Overall, we strongly suggest that you use the standard formulation ONLY if you are completely confident that the model from which you obtained your parameters is consistent with it. Otherwise, you should include your own formulation of competitive ability (see vignette 4).

Value

data frame with variable number of rows and three columns, specifying taxa identity and the competitive ability of focal species (sp1) relative to the competitor (sp2).

Examples

competitive_ability(lambda = runif(1,1,10),
                              pair_matrix = matrix(runif(4,0,1),nrow = 2),
                              model_family = "BH")

[Package cxr version 1.1.1 Index]