reduce.env: Reduce environmental data
In sdStaf: Species Distribution and Stability Future Models

Description Usage Arguments Details Value See Also Examples

This function allows reduce environmental data clipping by mask or buffer area

1	reduce.env(env, transfer = NULL, occ_data, mask)

`env`	RasterStack* objet.
`transfer`	List of rasterstack object
`occ_data`	A data.frame of occurrence records. It must include two column based on latitude and longitude.
`mask`	Croped mask, must be shapefile (.shp), readOGR.

Reduce the correlation among predicted variables either buffer zone, or clipping mask.

Provide reduce objet with cut predicted variables and data.frame for the values of each point of occurrence of them.

@crop RasterStack* Objet

@m.env data.frame of environmental values to occurrence localities.

cor.show

# Phytotoma ocurrence data
data(phytotoma)


# Complement
library(dismo)
predictor <- stack(list.files(path=paste(system.file(package="dismo"),'/ex', sep=''),
 pattern='grd', full.names=TRUE ))

 maskM <- stim.M(phytotoma[,2:3], 131)

reduce_cut <- reduce.env(env = predictor, occ_data = phytotoma[,2:3], mask=maskM)

# Plot reduce_cut
plot(reduce_cut@cropa$bio1)

# Add points
points(phytotoma[,2:3], pch=16,col='blue')

# Correlogram
cor.show(reduce_cut)
rd <- c('bio1','bio12','bio16','biome','bio8')

# Removing rd-variables on correlogram
cor.show(reduce_cut, rm=TRUE, var.rm = rd)

# Remove rd-variables
var_reduce <- dropLayer(reduce_cut@cropa, rd)

# summary
var_reduce