raptr (version 0.0.3)

sim.species: Simulate species distribution data for RAP

Description

This function simulates species distributions for RAP.

Usage

sim.species(x, ...)
# S3 method for RasterLayer
sim.species(x, n = 1, model = list("uniform",
  "normal", "bimodal", RPgauss())[[1]], ...)
# S3 method for SpatialPolygons
sim.species(x, res, n = 1, model = list("normal",
  "uniform", "bimodal", RPgauss())[[1]], ...)

Arguments

x

RasterLayer or SpatialPolygons object delineate the spatial extent to delineate study area.

...

parameters passed to RandomFields.

n

integer number of species. Defaults to 1.

model

RMmodel model to simulate species distributions with. Defaults RPgauss.

res

numeric resolution to simulate distributions. Only needed when SpatialPolygons supplied.

Value

RasterStack with layers for each species.

Details

Distributions are simulated by passing model to RFsimulate and converting to logistic values using inv.logit.

See Also

RFsimulate.

Examples

# NOT RUN {
# make polygons
sim_pus <- sim.pus(225L)
# simulate 1 uniform species distribution using RasterLayer
s1 <- sim.species(blank.raster(sim_pus, 1), n=1, model='uniform')

# simulate 1 uniform species distribution based on SpatialPolygons
s2 <- sim.species(sim_pus, res=1, n=1, model='uniform')

# simulate 1 normal species distributions
s3 <- sim.species(sim_pus, res=1, n=1, model='normal')

# simulate 1 bimodal species distribution
s4 <- sim.species(sim_pus, res=1, n=1, model='bimodal')

# simulate 1 species distribution using a RModel object from RandomFields
s5 <- sim.species(sim_pus, res=1, n=1, model=RandomFields::RPgauss())

# simulate 5 species distribution using a RModel object from RandomFields
s6 <- sim.species(sim_pus, res=1, n=5, model=RandomFields::RPgauss())

# plot simulations
par(mfrow=c(2,2))
plot(s2, main='constant')
plot(s3, main='normal')
plot(s4, main='bimodal')
plot(s5, main='RPgauss()')
# }