ecospat (version 3.0)

ecospat.mess: MESS

Description

Calculate the MESS (i.e. extrapolation) as in Maxent.

Usage

ecospat.mess (proj, cal, w="default")

Arguments

proj

A dataframe object with x, y and environmental variables, used as projection dataset.

cal

A dataframe object with x, y and environmental variables, used as calibration dataset.

w

The weight for each predictor (e.g. variables importance in SDM).

Value

MESS

The mess as calculated in Maxent, i.e. the minimal extrapolation values.

MESSw

The sum of negative MESS values corrected by the total number of predictors. If there are no negative values, MESSw is the mean MESS.

MESSneg

The number of predictors on which there is extrapolation.

Details

Shows the variable that drives the multivariate environmental similarity surface (MESS) value in each grid cell.

References

Elith, J., M. Kearney and S. Phillips. 2010. The art of modelling range-shifting species. Methods in ecology and evolution, 1, 330-342.

See Also

ecospat.plot.mess

Examples

# NOT RUN {
x <- ecospat.testData[c(2,3,4:8)]
proj <- x[1:90,] #A projection dataset.
cal <- x[91:300,] #A calibration dataset

#Create a MESS object 
mess.object <- ecospat.mess (proj, cal, w="default")

#Plot MESS 
ecospat.plot.mess (mess.object, cex=1, pch=15)
# }

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