species_fitness: Fitness of a species

View source: R/species_fitness.R

species_fitnessR Documentation

Fitness of a species

Description

Calculates the fitness of a species sensu Godoy et al. (2014).Note that its definition is model-specific, i.e. it depends on the model family from which interaction coefficients were estimated. The function given here assumes a community of n-species, so that species fitness is calculated according to a general competitive response (r) substituting the 2-sp denominator terms of table A1 of Hart et al. 2018. This competitive response can be calculated for a series of species with the function 'cxr_er_fit'.

Usage

species_fitness(
  effect_response_fit = NULL,
  lambda = NULL,
  competitive_response = NULL,
  model_family = NULL
)

Arguments

effect_response_fit

cxr_er_fit object with valid lambda and response terms.

lambda

per capita fecundity of the species in the absence of competition.

competitive_response

parameter reflecting the species' sensitivity to competition.

model_family

model family for which to calculate species fitness.

Details

Thus, the function accepts two sets of parameters. First, a 'cxr_er_fit' object returned from that function. In this case, species fitness will be calculated for all focal taxa included in the 'cxr_er_fit' object.

Otherwise, users may enter a specification of the model to use, as well as lambda and competitive response parameters of a single species.

If no model family is provided, or a model family for which there is no associated 'XX_species_fitness' function, the function resorts to the standard Lotka-Volterra formulation (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 species fitness (see vignette 4).

Value

single numeric value/vector, species fitness of one or several taxa


cxr documentation built on Oct. 27, 2023, 1:08 a.m.