Simulate time series with the generalized Lotka-Volterra model

Source: R/glv.R

Simulate a community time series using the generalized Lotka-Volterra model, defined as \(\frac{dx}{dt}=x(b+Ax)\), where x is the vector of species abundances, A is the interaction matrix and b the vector of growth rates.

glv(N = 4, A, b = runif(N), y = runif(N), tstart = 0, tend = 100,
  tstep = 0.1, perturb = NULL)

Arguments

N

species number
A

interaction matrix
b

growth rates
y

initial abundances
tstart

initial time point
tend

final time point
tstep

time step
perturb

perturbation object describing growth changes

Value

a matrix with species abundances as rows and time points as columns, column names give time points

See also

ricker for the Ricker model

Examples

tsplot(glv(N=4,generateA(4)),header="gLV")
#> [1] "Adjusting connectance to 0.02"
#> [1] "Initial edge number 16"
#> [1] "Initial connectance 1"
#> [1] "Number of edges removed 12"
#> [1] "Final connectance 0"
#> [1] "Final connectance: 0"
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter
#> Warning: "header" is not a graphical parameter