bamm (version 0.5.0)

bam_sim: bam_sim: Simulate dispersal dynamics using the set B of the BAM framework.

Description

bam_sim: Simulate dispersal dynamics using the set B of the BAM framework.

Usage

bam_sim(
  sp1,
  sp2,
  set_M,
  initial_points,
  periods_toxic,
  periods_suitable,
  nsteps,
  progress_bar = TRUE
)

Value

An object of class bam. The object contains 12 slots of information (see details) from which simulation results are stored in sdm_sim object, a list of sparse matrices with results of each simulation step.

Arguments

sp1

Niche model of the focal species (the one that disperses).

sp2

Niche model of the species with whom sp1 interacts (currently no dispersal dynamics for this species).

set_M

A setM object containing the adjacency matrix for sp1. See adj_mat

initial_points

A sparse vector returned by the function occs2sparse

periods_toxic

Time periods that sps2 takes to develop defense mechanisms (i.e. toxic).

periods_suitable

This is the time that sp2 takes to become non-toxic

nsteps

Number of steps to run the simulation

progress_bar

Show progress bar

Author

Luis Osorio-Olvera & Jorge Soberón

Details

The returned object inherits from setA, setM classes. Details about the dynamic model can be found in Soberon and Osorio-Olvera (2022). The model is cellular automata where the occupied area of a species at time \(t+1\) is estimated by the multiplication of three binary matrices: one matrix represents movements (M), another abiotic -niche- tolerances (A), and a third, biotic interactions (B) (Soberon and Osorio-Olvera, 2022). $$\mathbf{G}_j(t+1) =\mathbf{B}_j(t)\mathbf{A}_j(t)\mathbf{M}_j \mathbf{G}_j(t)$$

References

SoberonOsoriobamm.

Examples

# Compute dispersal dynamics of Urania boisduvalii as a function of
# palatable Omphalea
urap <- system.file("extdata/urania_omph/urania_guanahacabibes.tif",
                                  package = "bamm")
ura <- raster::raster(urap)
ompp <- system.file("extdata/urania_omph/omphalea_guanahacabibes.tif",
                                  package = "bamm")
omp <- raster::raster(ompp)
msparse <- bamm::model2sparse(ura)
init_coordsdf <- data.frame(x=-84.38751, y= 22.02932)
initial_points <- bamm::occs2sparse(modelsparse = msparse,init_coordsdf)
set_M <- bamm::adj_mat(modelsparse = msparse,ngbs = 1)
ura_sim <- bamm::bam_sim(sp1=ura, sp2=omp, set_M=set_M,
                         initial_points=initial_points,
                         periods_toxic=5,
                         periods_suitable=1,
                         nsteps=40)
ura_omp <- bamm::sim2Raster(ura_sim)
raster::plot(ura_omp[[c(1,5,10,15,20,30,35,40)]])
# \donttest{
if(requireNamespace("animation")){
# Animation example
anp <-tempfile(pattern = "simulation_results_",fileext = ".gif")
# new_sim <- bamm::sim2Animation(sdm_simul = ura_sim,
#                                which_steps = seq_len(ura_sim@sim_steps),
#                                fmt = "GIF",
#                               filename = anp)
}
# }