| ecospat.mess {ecospat} | R Documentation |
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). |
Details
Shows the variable that drives the multivariate environmental similarity surface (MESS) value in each grid cell.
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. |
Author(s)
Blaise Petitpierre bpetitpierre@gmail.com. Modified by Daniel Scherrer daniel.j.a.scherrer@gmail.com
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
Examples
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)