15 June 2013
Welcome to the new EcoSim homepage. Aaron Ellison and I are pleased to be offering EcoSimR 1.00, an R version of the original EcoSim package. EcoSimR consists of fully-annotated R-script files, along with help files, tutorials, and sample data sets for you to work with.
This initial release of EcoSimR contains only the Niche Overlap module. However, if you are already an R programmer, you can immediately start adding new functions for algorithms and metrics to conduct new null model analyses.
EcoSimR offers four distinct advantages over the original EcoSim:
We hope that EcoSimR will serve as a gateway drug and inspire you to do your own R-programming and modify the code to suit your specific needs!
Gotelli, N.J. and A.M. Ellison. 2013. EcoSimR 1.00.
15 June 2013
There have been many exciting advances in null model analysis since the appearance of EcoSim. We intend to update some of the algorithms and indices to keep EcoSimR current with the literature. In the meantime, here are some issues for you to consider for the following EcoSim modules:
So what is the solution? Instead of calculating a statistical test for the entire matrix, the pattern can be tested for each individual pair of species in the matrix. But this solution generates a new problem: because there are S(S-1)/2 species pairs, the analysis would generate thousands of individual p-values (one for each unique species pair), even for a modest-sized matrix. This problem has also arisen in genomics and proteomics, where it is now possible to rapidly screen expression levels of thousands of genes. The empirical Bayes approach allows for a realistic adjustment and screening of the individual pairs to limit the rate of false positives (Effron 2005). Ulrich and Gotelli (2010) adapt these methods for co-occurrence analysis and apply them to a large set of empirical matrices from the ecological literature. Ulrich’s Pairs software implements these procedures and represents an important step forward for the analysis of species co-occurrence. Be sure to check out Werner’s many useful FORTRAN programs for ecological data analysis.
1 January 2012
Download the original EcoSim
This version of EcoSim is the most recent and represents the original programming effort (funded by NSF for 7 years). It still works fine, although it is beginning to show its age, as the modules have not been substantively updated in over 10 years. I will keep it available here at this website as long as it remains compatable with current versions of Windows. As always, I will continue to answer questions and provide advice about analyses with EcoSim.
Unfortunately, a “new” commercial version of EcoSim has recently appeared elsewhere on the web. The commercialization of EcoSim was done without my consent or approval, and I strongly oppose it. I had no involvement with the commercial product, and I cannot confirm the validity of any of the algorithms or modules contained in it.
To combat the commercialization of EcoSim, Aaron Ellison and I are initiating a new project. We are beginning to recode the routines in EcoSim to the R language and will release EcoSimR (“EcoSimmer”) at this site. EcoSimR will consist of fully annotated R-script files, along with help files, tutorials, and sample data sets for you to work with.
Castro-Arellano, I., T.E. Lacher, Jr., M.R. Willig, and T.F. Rangel. 2010. Assessment of assemblage-wide temporal niche segregation using null models. Methods in Ecology & Evolution 1: 311-318.
Colwell, R.K., A. Chao, N.J. Gotelli, S-Y. Lin, C.X. Mao, R.L. Chazdon, and J.T. Longino. 2012. Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages. Journal of Plant Ecology 5:3-21.
Efron, B. 2005. Bayesians, frequentists, and scientists. Journal of the American Statistical Association 100:1-5
Gotelli, N.J. and W. Ulrich. 2012. Statistical challenges in null model analysis. Oikos 121: 171-180.
Gotelli, N.J. and W. Ulrich. 2010. The empirical Bayes approach as a tool to identify non-random species associations. Oecologia 162:463-477.
Stone, L., and A. Roberts. 1990. The checkerboard score and species distributions. Oecologia 85:74-79.
Ulrich, W., M. Almeida-Neto, and N.J. Gotelli. 2009. A consumer's guide to nestedness analysis. Oikos 118: 3-17.
Ulrich, W. and N.J. Gotelli. 2007a. Disentangling community patterns of nestedness and species co-occurrence. Oikos 116: 2053-2061.
Ulrich, W. and N.J. Gotelli. 2007b. Null model analysis of species nestedness patterns. Ecology 88:1824-1831.
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