Selecting the Best Set of Relevant Environmental Variables along with the Optimal Regularization Multiplier for Maxent Niche Modeling R package MaxentVariableSelection version 1.0-3 Complex niche models show low performance in identifying the most important range-limiting environmental variables and in transferring habitat suitability to novel environmental conditions (Warren and Seifert, 2011 <DOI:10.1890/10-1171.1>; Warren et al., 2014 <DOI:10.1111/ddi.12160>). This package helps to identify the most important set of uncorrelated variables and to fine-tune Maxent's regularization multiplier. In combination, this allows to constrain complexity and increase performance of Maxent niche models (assessed by information criteria, such as AICc (Akaike, 1974 <DOI:10.1109/TAC.1974.1100705>), and by the area under the receiver operating characteristic (AUC) (Fielding and Bell, 1997 <DOI:10.1017/S0376892997000088>). Users of this package should be familiar with Maxent niche modelling. Software Depends: R (>= 3.1.2) Imports: ggplot2, raster Suggests: knitr, rmarkdown "Alexander Jueterbock" <Alexander-Jueterbock@web.de> Comprehensive R Archive Network (CRAN) Alexander Jueterbock GPL (>= 2) 2018-01-23 application/tgz https://CRAN.R-project.org/package=MaxentVariableSelection doi:10.32614/CRAN.package.MaxentVariableSelection