localLotkaVolterra: Lotka-Volterra with local predation interactions

In ibm: Individual Based Models in R

Description

This function simulates several trajectories for a Lotka-Volterra model with local predation interactions as decribed in Brigatti et al. (2009).

Usage

localLotkaVolterra(par, T, replicates = 1, dim = 1, periodic = TRUE,
  spatial = FALSE, verbose = FALSE, maxpop = 1e+06)

Arguments

par	A list containing the parameters to run the model, currently the growth rate of prey (r), the mortality rate of predator (l), predation interaction parameters (alpha and beta), diffusion rates (D), diameters of local interaction (L) and initial population size (initial). For D, L and initial population, a list with two values (named N and P) is required.
T	Time horizon, number of time steps to be simulated.
replicates	Number of replicates (trajectories) to be simulated.
dim	Spatial dimension for the space. Can be 1, 2 or 3.
periodic	Spatial boundary conditions. If periodic is set to TRUE, the space is a torus. If set to FALSE, the boundaries are reflective.
spatial	Boolean, should spatial outputs (position of individuals) to be saved?
verbose	Boolean, to print population sizes by step?
maxpop	Maximum population size. If predator or prey population size get bigger, the simulation ends.

Value

A list with the following elements:

N	A matrix with prey population sizes by time (rows) and replicates (columns)
P	A matrix with predator population sizes by time (rows) and replicates (columns)
pop	Prey and predator positions by time, if spatial is TRUE

Author(s)

Ricardo Oliveros–Ramos

References

Brigatti et al. 2009.

Examples

## Not run: 
set.seed(880820)
par = list(alpha=5e-4, beta=5e-4, r=0.1, m=0.05, D=list(N=8e-5, P=8e-5), 
L=list(N=0.2, P=0.2))
N0 = with(par, m/(2*beta*L$P))
P0 = with(par, r/(2*alpha*L$N))
par$initial = list(N=round(N0), P=round(P0))
sim = localLotkaVolterra(par, T=240, replicates=100, maxpop = 1e4)
plot(sim)

## End(Not run) 

ibm documentation built on May 2, 2019, 5:53 a.m.