modelos: Produces ecological niche models

In diogosbr/modelos: Modelagem de nicho ecológico

Description

A function to produce ecological niche models.

Usage

modelos(coord, abio, k = 3, diretorio = "teste", plot = T, bc = T,
  mx = F, GLM = F, RF = F, SVM = F, dm = F, mah = F, proj,
  buffer = "none", geo.filt.res, mod = "before", tss = 0)

Arguments

coord	data.frame. Table with the occurrence data of the species. It should contain only two columns: long and lat, in this order.
abio	the rasters to be cut. Accepts an object of the type _stack_
k	number of partitions. The default is 3.
diretorio	name of the directory to be created with the results in the modeling.
plot	logical. If TRUE (deafult), plots the final model.
bc	bioclim
mx	Maxent
GLM	Generalized linear model
RF	Random Forest (regression)
SVM	Support Vector Machine
dm	Domain
mah	Mahalanobis distance
proj	_stack_ with the variables where the model will be projected. If you are not informed, the model is projected in the same place of creation of the model (informed in abio).
buffer	distance chosen to generate a buffer around the occurrence points where the pseudo-absence points will be generated. "mean" is the mean distance between points, "median" is the median distance between points and "max" is the maximum distance between points. Or if it is "none", no buffer is used (default).
geo.filt.res	numeric. Keep only the points that are at least far from each other the number of kilometers informed.
mod	when the model is cut to generate the ensemble. "before" each partition is cut by its own TSSth. "after" the ensemble of each algorithm is cut by the average TSSth of the partitions.
tss	numeric. Selects only models that present higher than reported TSS value.

Details

The most complex function of this package

Value

Raster files in a user-specified directory.

Author(s)

Diogo S. B. Rocha

See Also

bioclim, mask

Examples

fnames <- list.files(path=paste(system.file(package="dismo"), '/ex', sep=''), pattern='grd', full.names=TRUE )
predictors <- raster::stack(fnames)
occurence <- paste(system.file(package="dismo"), '/ex/bradypus.csv', sep='')
occ <- read.table(occurence, header=TRUE, sep=',')[,-1]
modelos(coord = occ, abio = predictors)

diogosbr/modelos documentation built on May 9, 2019, 5:23 p.m.