Code and Data: Power laws and critical fragmentation in global forests

Source code for image processing and statistical analysis, and the patch size data files for the manuscript:Power laws and critical fragmentation in global forests. (2016) Saravia L.A. Doyle S.R. Bond-Lamberty B. bioRxiv 091751; doi: http://dx.doi.org/10.1101/091751Zip Files:Patch Sizes distribution by region, year and threshold from 2000 to 2015: these are binary files consisting on a vector of doubles, the R command used to read it is readBin(connection_file, "double", n = 10^8)Africa_PatchSizes.zipNorthamerica_PatchSizes.zipSouthamerica_PatchSizes.zipEurasia_PatchSizes.zipOceania_PatchSizes.zipSouthasia_PatchSizes.zipLargestPatchAnimations.zip Animations of the two largest patches for all the regions defined in the paper. PercolationAnimations.zip Animation demonstrating percolation in a forest/non-forest modelStudy_areas_definition.zip These files needed to be unziped in a folder and the location added to the script data_input_script.m fileR markdown files:Threshold_sensitivity.Rmd # Fitting heavy tails to modis VCF, Smax & RSmax patch analysis. Download_modis.Rmd # Download modis files MOD44B version 051Map_study_areas.Rmd # Generate maps of study areas Map_Max_patches.Rmd # Generate GIF animations of maximum patch dynamics R Filesmap_fun.r # Map raster functionspower_fun.r # Function to fit continuos heavy tail distributionsMATLAB FilesExtract patch sizes from bin, and other analysis not used in the paperdata_input_script.mGCF_spatial_analyses.mPYTHON Filespowlawfit.py : Call the Python powerlawpackage from command line DATA Tables: csv and tab separated text files with model fits for the patch size distribution models.Fitted_Patch_models.csvFitted_Patch_models.txt