fluxweb (version 2.0.0)

stability.value: Estimates network stability

Description

Computes resilience of the system through Jacobian matrix eigenvalues.

Usage

stability.value(
  val.mat,
  biomasses,
  efficiencies,
  metabolic.types,
  ef.level = "prey",
  full.output = FALSE
)

Value

Maximum eigenvalue of the Jacobian matrix of a Lotka Voltera like system of equations. If full.output, Jacobian eigenvalues and eigenvectors are returned.

Arguments

val.mat

A matrix describing fluxes between species (usually a result of fluxing function).

biomasses

A vector of species biomasses.

efficiencies

A vector or an array of conversion efficiencies of species in the adjacency matrix. These values describe the proportion of consumed energy that is converted to biomass of the consumer.

metabolic.types

A vector containing information on species type ("detritus", "plant" or "animal")

ef.level

Set to "prey" if efficiencies are defined by prey, "pred" if they are a property of the predator.

full.output

Logical, if TRUE function return supplementary informations.

Author

Benoit Gauzens,

Details

• efficiencies: Determines how efficient species are to convert energy (see ef.level for more details). Providing an array will assume values depending on both prey and predator identity.

• ef.level: If "prey" (resp "pred"), the total amount of energy that can be metabolized from a trophic link will be determined by prey (resp pred) identity. "link.specific" assumes that efficiencies are defined for each trophic interaction and implies efficiencies parameter to be a matrix

• full.output: If TRUE, function result is a list of eigenvalues and eigenvectors of the Jacobian matrix.

Examples

losses = 0.15 * groups.level$bodymasses^(-0.25)
# define metbolic types:
met.types = rep('animal', length(losses))
met.types[groups.level$efficiencies == 0.545] = 'plant'

val.mat = fluxing(groups.level$mat, 
                  groups.level$biomasses, 
                  losses, 
                  groups.level$efficiencies, 
                  bioms.pref = TRUE, 
                  ef.level = "pred")
                  
stability.value(val.mat, 
                groups.level$biomasses, 
                groups.level$efficiencies,
                metabolic.types = met.types,
                ef.level = "pred")