Supplement 1. The program Com_Sim: a Monte Carlo community simulator designed to test for community change.

File List com_sim.exe <br>com_sim.zip <br>sample1.txt <br>sample2.txt <br>sample3.txt Descriptioncom_sim is a Monte Carlo community simulator designed to test for community change. The model requires as input a text file describing a reference sample. This file must have (1) the number of species to be simulated on the first line and (2) each species mean abundance and coefficient of variation in abundance. Each species is listed on its own line with mean and CV separated by spaces. A simple reference sample with 5 species might look like this: <br> 5 <br> 1 0.8 <br> 2 0.6 <br> 6 0.4 <br> 17 0.3 <br> 45 0.2 <br> Where the first species has an abundance of 1.0 and a CV in abundance of 0.8 etc. Files must be in the same directory as the com_sim program and can only have 8 characters plus a three character extension. Three sample data sets are included as examples. Once the program has started it will ask for the name of this file along with some other input variables: A random number seed. Assuming all other input is the same, using the same random number seed will result in identical results. Name of the output file to store generated communities. Data generated are species abundances separated by spaces, one community per line. The end of each line also has some similarity indices, comparing the simulated community with the reference. Number of communities to generate in the simulation (minimum of 100, maximum of 10,000). Species not present in the reference sample (abundance=0) need an estimate of mean abundance. The model will generate rare species abundances based on this vale and the CV specified in the reference sample. This can be any value greater than 0.0. Sensitivity analyses can be run by generating data sets with half the expected variability (0.5*CV) and twice the variability (2.0*CV). If sensitivity analyses are run, the first set of data in the output file will be from the expected level of variability, followed 0.5*CV and 2.0*CV. <br> After all parameters are entered the program will give a summary before starting simulations. <br> Depending on the size of the data set, the number of communities simulated and the speed of your computer the program may run for some time before generating results. Press any key to start simulations. <br> Program output will look something like this: Created 1000 communities. <br> =============================== <br> PSI p(0.05)=0.525 p(0.01) 0.439 p(0.001) 0.392 <br> Bray-Curtis p(0.05)=0.497 p(0.01) 0.421 p(0.001) 0.263 <br> Morrisita's p(0.05)=0.274 p(0.01) 0.243 p(0.001) 0.182 <br> Jaccard's p(0.05)=0.600 p(0.01) 0.550 p(0.001) 0.500 <br> =============================== <br> Success. <br> Press any key to continue... <br> Indicating, for example, that 5% of the generated communities (20 of the 1000) had PSI values &lt;= 0.525. <br> Exact p values for observed data can be obtained by importing simulated data into a spreadsheet and examining the frequency distribution of generated PSI values. <br> Alternatively, the raw simulated community data could be used to generate a distrubtion of any metric of community change by comparing all simulated comunities to the reference.