The script is intended to compute raw and/or logistic prediction maps from a lambdas file produced with MaxEnt 3.3.3e.
It will parse the specified lambdas-file from MaxEnt 3.3.3e and translate it into an r.mapcalc-expression
which is then stored in a temporary file and finally piped to r.mapcalc. If alias names had been used in MaxEnt, these
alias names can automatically be replaced according to a CSV-like file provided by the user.
This file should contain alias names in the first column and map names in the second column, seperated by comma,
without header. It should look e.g. like this:
If such a CSV-file with alias names used in MaxEnt is provided, the alias names from MaxEnt are replaced by map names.
A raw output map is always computed from the MaxEnt model as a first step. If logistic output is requested, the raw output
map can be deleted by the script ( using the l-flag). The logistic map can be produced as an integer map. To do so the user
has to specify the number of decimal places, that should be preserved in integer output.
Optionally the map calculator expressions can be saved in a text file as especially the one for the raw output is likely to exceed
the space in the map history.
This script works only if the maps containing the input data to MaxEnt are accessible from the current region.
Due to conversion from double to floating-point in exp()-function, a loss of precision from the 7th decimal place onwards may occur
in the logistic output.
MaxEnt 3.3.3e http://biodiversityinformatics.amnh.org/open_source/maxent/
Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudík, Yung En Chee, Colin J. Yates. 2011: A statistical explanation of MaxEnt
for ecologists. Diversity and Distributions, (17):43-57, 2011.
Wilson, Peter D. 2009: Guidelines for computing MaxEnt model output values from a lambdas file. (Avaliable at
Steven J. Phillips, Robert P. Anderson, Robert E. Schapire. 2006: Maximum entropy modeling of species geographic distributions.
Ecological Modelling, (190):231-259, 2006.
Steven J. Phillips, Miroslav Dudík, Robert E. Schapire. 2004: A maximum entropy approach to species distribution modeling. In: Proceedings
of the Twenty-First International Conference on Machine Learning, p. 655-662, 2004.