Supplementary code and data from the study: Pinheiro, R. B. P., Dormann, C. F., Felix, G. M. F., & Mello M. A. R. Linking null models to hypotheses to improve nestedness analysis. Submitted.
Ecological Synthesis Lab (SintECO)
Authors: Rafael B. P. Pinheiro, Gabriel M. Felix, Carsten F. Dormann, and Marco A. R. Mello.
E-mail: [email protected]{.email}.
Published originaly on September 29th, 2021 (English version).
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R version 4.2.0 (2022-04-22) -- "Vigorous Calisthenics"
You may use this script freely for commercial or non-commercial purposes at your own risk. We assume no responsibility or liability for the use of this software, convey no license or title under any patent, copyright, or mask work right to the product. We reserve the right to make changes in the software without notification. We also make no representation or warranty that such application will be suitable for the specified use without further testing or modification. If this script helps you produce any academic work (paper, book, chapter, dissertation, monograph, thesis, report, talk, keynote, lecture etc.), please acknowledge the authors and cite the source.
In this repo you will find commented scripts to reproduce our study, including R functions for applying our new protocol to other networks.
If you are well acquainted with R, you may reproduce the case study presented in our paper using the file case_study.R. You may also experiment with our custom-made functions in the folder functions.
Alternatively, you can run the step-by-step tutorial provided in the file case_study.Rmd. Or just read its knitted PDF version in the file case_study.pdf.
See further instructions and details about our protocol in the complete user guide: README file.
If you have any questions, corrections, or suggestions, please feel free to open an issue or make a pull request.
- https://github.com/pinheirorbp/ihsmodel
- https://github.com/gabrielmfelix/Restricted-Null-Model
- https://github.com/marmello77/multiple-networks
- https://github.com/marmello77/network-significance
- https://github.com/biometry/bipartite
We thank our institutions and colleagues, who helped us in different ways during this project. The Ph.D. defense committee of RBPP, composed by Tatiana Cornelissen, Aristóteles Neto, Mario Almeida-Neto, and Paulo Peixoto, provided suggestions that considerably improved the quality of our study. Nico Blüthgen, Paulo Guimarães Jr., and Tiago Quental helped us get new insights through exciting discussions about species interactions and ecological networks. The Graduate School in Ecology of the Federal University of Minas Gerais (ECMVS), Brazil, provided RBPP with a Ph.D. scholarship from the Brazilian Council for Scientific and Technological Development (CNPq). Infrastructure for this study was provided by ECMVS, the Department of Ecology of the University of São Paulo (USP), Brazil, and the Department of Biometry and Environmental System Analysis of the University of Freiburg, Germany. The Graduate School in Ecology of the State University of Campinas (PPGE-UNICAMP), Brazil, provided GMFF with a scholarship from the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES). RBPP received a scholarship from the joint program between CAPES, CNPq, and Deutscher Akademischer Austauschdienst (DAAD) (88887.161398/2017-00) and is currently funded by São Paulo Research Foundation (FAPESP, post-doctoral grant 2020/06771-2). MARM was funded by the Minas Gerais Research Foundation (FAPEMIG: PPM-00324-15), Alexander von Humboldt Foundation (AvH, 3.4-8151/15037 and 3.2-BRA/1134644), CNPq (302700/2016-1 and 304498/2019-0), Dean of Research of the University of São Paulo (PRP-USP, 18.1.660.41.7), and FAPESP (2018/20695-7). Last, but not least, we thank the StackOverflow community, where we solve most of our coding dilemmas.