Code Supplement for Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology

This file contains all the code needed to replicate the analyses of McGill, D.J., X. Xiao, J. Kitizes, and E.P. White. submitted. Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology. http://biorxiv.org/content/early/2014/03/30/003657 This file should be decompressed in what R recognizes as the home directory (the R code will need to be modified if you decide not to use your home directory). R v 2.12 or higher and python 2.6 are needed to run the code. The following python packages are required: matplotlib, mpmath, numpy, and scipy, and the following R packages are required: vegan, hash, RCurl and bigmemory. It is also possible to access this code via GitHub at the following addresses: The primary code repository is located at: https://github.com/weecology/mete-spatial Additional scripts needed to run the core METE DDR functions are located here: https://github.com/weecology/METE https://github.com/weecology/macroecotools After the files are downloaded (from GitHub) or decompressed (from the mete-spatial.zip file) navigate to the METE directory and run the following python command python setup.py install run the same command in the macroecotools directory. To download the publically available data and run the analysis navigate to the directory ~/mete-spatial and run the command: Rscript ddr_run_all.R This script will download two datasets, analyze them, and graph the results. The plots will appear in the directory ~/mete-spatial/figs/