R packages used

Package Version Citation
adegenet 2.1.10 Jombart (2008); Jombart and Ahmed (2011)
base 4.4.0 R Core Team (2024)
BayesianNetworks 0.0.7 Rodriguez-Sanchez and Young (2024)
bayestestR 0.13.2 Makowski, Ben-Shachar, and Lüdecke (2019)
bipartite 2.19 Dormann, Gruber, and Fruend (2008); Dormann et al. (2009); Dormann (2011)
cluster 2.1.6 Maechler et al. (2023)
DHARMa 0.4.6 Hartig (2022)
fmsb 0.7.6 Nakazawa (2024)
GGally 2.2.1 Schloerke et al. (2024)
ggcorrplot 0.1.4.1 Kassambara (2023)
ggdist 3.3.2 Kay (2024b); Kay (2024a)
ggfortify 0.4.17 Tang, Horikoshi, and Li (2016); Horikoshi and Tang (2018)
ggh4x 0.2.8 van den Brand (2024)
ggrepel 0.9.5 Slowikowski (2024)
ggridges 0.5.6 Wilke (2024)
glmmTMB 1.1.9 Brooks et al. (2017)
gridExtra 2.3 Auguie (2017)
here 1.0.1 Müller (2020)
igraph 2.0.3 Csardi and Nepusz (2006); Csárdi et al. (2024)
iNEXT 3.0.1 Chao et al. (2014); Hsieh, Ma, and Chao (2024)
knitr 1.46 Xie (2014); Xie (2015); Xie (2024)
MetBrewer 0.2.0 Mills (2022)
modelbased 0.8.7 Makowski et al. (2020)
network.tools 0.0.4 Rodriguez-Sanchez (2024)
paletteer 1.6.0 Hvitfeldt (2021)
patchwork 1.2.0 Pedersen (2024)
psych 2.4.3 William Revelle (2024)
rcartocolor 2.1.1 Nowosad (2018)
renv 1.0.7 Ushey and Wickham (2024)
reshape2 1.4.4 Wickham (2007)
rmarkdown 2.26 Xie, Allaire, and Grolemund (2018); Xie, Dervieux, and Riederer (2020); Allaire et al. (2024)
scales 1.3.0 Wickham, Pedersen, and Seidel (2023)
summarytools 1.0.1 Comtois (2022)
tidylog 1.0.2 Elbers (2020)
tidyverse 2.0.0 Wickham et al. (2019)
tnet 3.0.16 Opsahl (2009)

You can paste this paragraph directly in your report:

We used R version 4.4.0 (R Core Team 2024) and the following R packages: adegenet v. 2.1.10 (Jombart 2008; Jombart and Ahmed 2011), BayesianNetworks v. 0.0.7 (Rodriguez-Sanchez and Young 2024), bayestestR v. 0.13.2 (Makowski, Ben-Shachar, and Lüdecke 2019), bipartite v. 2.19 (Dormann, Gruber, and Fruend 2008; Dormann et al. 2009; Dormann 2011), cluster v. 2.1.6 (Maechler et al. 2023), DHARMa v. 0.4.6 (Hartig 2022), fmsb v. 0.7.6 (Nakazawa 2024), GGally v. 2.2.1 (Schloerke et al. 2024), ggcorrplot v. 0.1.4.1 (Kassambara 2023), ggdist v. 3.3.2 (Kay 2024b, 2024a), ggfortify v. 0.4.17 (Tang, Horikoshi, and Li 2016; Horikoshi and Tang 2018), ggh4x v. 0.2.8 (van den Brand 2024), ggrepel v. 0.9.5 (Slowikowski 2024), ggridges v. 0.5.6 (Wilke 2024), glmmTMB v. 1.1.9 (Brooks et al. 2017), gridExtra v. 2.3 (Auguie 2017), here v. 1.0.1 (Müller 2020), igraph v. 2.0.3 (Csardi and Nepusz 2006; Csárdi et al. 2024), iNEXT v. 3.0.1 (Chao et al. 2014; Hsieh, Ma, and Chao 2024), knitr v. 1.46 (Xie 2014, 2015, 2024), MetBrewer v. 0.2.0 (Mills 2022), modelbased v. 0.8.7 (Makowski et al. 2020), network.tools v. 0.0.4 (Rodriguez-Sanchez 2024), paletteer v. 1.6.0 (Hvitfeldt 2021), patchwork v. 1.2.0 (Pedersen 2024), psych v. 2.4.3 (William Revelle 2024), rcartocolor v. 2.1.1 (Nowosad 2018), renv v. 1.0.7 (Ushey and Wickham 2024), reshape2 v. 1.4.4 (Wickham 2007), rmarkdown v. 2.26 (Xie, Allaire, and Grolemund 2018; Xie, Dervieux, and Riederer 2020; Allaire et al. 2024), scales v. 1.3.0 (Wickham, Pedersen, and Seidel 2023), summarytools v. 1.0.1 (Comtois 2022), tidylog v. 1.0.2 (Elbers 2020), tidyverse v. 2.0.0 (Wickham et al. 2019), tnet v. 3.0.16 (Opsahl 2009).

Package citations

Allaire, JJ, Yihui Xie, Christophe Dervieux, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, et al. 2024. rmarkdown: Dynamic Documents for r. https://github.com/rstudio/rmarkdown.
Auguie, Baptiste. 2017. gridExtra: Miscellaneous Functions for “Grid” Graphics. https://CRAN.R-project.org/package=gridExtra.
Brooks, Mollie E., Kasper Kristensen, Koen J. van Benthem, Arni Magnusson, Casper W. Berg, Anders Nielsen, Hans J. Skaug, Martin Maechler, and Benjamin M. Bolker. 2017. “glmmTMB Balances Speed and Flexibility Among Packages for Zero-Inflated Generalized Linear Mixed Modeling.” The R Journal 9 (2): 378–400. https://doi.org/10.32614/RJ-2017-066.
Chao, Anne, Nicholas J. Gotelli, T. C. Hsieh, Elizabeth L. Sander, K. H. Ma, Robert K. Colwell, and Aaron M. Ellison. 2014. “Rarefaction and Extrapolation with Hill Numbers: A Framework for Sampling and Estimation in Species Diversity Studies.” Ecological Monographs 84: 45–67.
Comtois, Dominic. 2022. summarytools: Tools to Quickly and Neatly Summarize Data. https://CRAN.R-project.org/package=summarytools.
Csardi, Gabor, and Tamas Nepusz. 2006. “The Igraph Software Package for Complex Network Research.” InterJournal Complex Systems: 1695. https://igraph.org.
Csárdi, Gábor, Tamás Nepusz, Vincent Traag, Szabolcs Horvát, Fabio Zanini, Daniel Noom, and Kirill Müller. 2024. igraph: Network Analysis and Visualization in r. https://doi.org/10.5281/zenodo.7682609.
Dormann, Carsten F. 2011. “How to Be a Specialist? Quantifying Specialisation in Pollination Networks.” Network Biology 1 (1): 1–20.
Dormann, Carsten F., Jochen Fruend, Nico Bluethgen, and Bernd Gruber. 2009. “Indices, Graphs and Null Models: Analyzing Bipartite Ecological Networks.” The Open Ecology Journal 2: 7–24.
Dormann, Carsten F., Bernd Gruber, and Jochen Fruend. 2008. “Introducing the Bipartite Package: Analysing Ecological Networks.” R News 8 (2): 8–11.
Elbers, Benjamin. 2020. tidylog: Logging for “dplyr” and “tidyr” Functions. https://CRAN.R-project.org/package=tidylog.
Hartig, Florian. 2022. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. https://CRAN.R-project.org/package=DHARMa.
Horikoshi, Masaaki, and Yuan Tang. 2018. ggfortify: Data Visualization Tools for Statistical Analysis Results. https://CRAN.R-project.org/package=ggfortify.
Hsieh, T. C., K. H. Ma, and Anne Chao. 2024. iNEXT: Interpolation and Extrapolation for Species Diversity. http://chao.stat.nthu.edu.tw/wordpress/software_download/.
Hvitfeldt, Emil. 2021. paletteer: Comprehensive Collection of Color Palettes. https://github.com/EmilHvitfeldt/paletteer.
Jombart, T. 2008. “adegenet: A r Package for the Multivariate Analysis of Genetic Markers.” Bioinformatics 24: 1403–5. https://doi.org/10.1093/bioinformatics/btn129.
Jombart, T., and I. Ahmed. 2011. “Adegenet 1.3-1: New Tools for the Analysis of Genome-Wide SNP Data.” Bioinformatics. https://doi.org/10.1093/bioinformatics/btr521.
Kassambara, Alboukadel. 2023. ggcorrplot: Visualization of a Correlation Matrix Using “ggplot2”. https://CRAN.R-project.org/package=ggcorrplot.
Kay, Matthew. 2024a. ggdist: Visualizations of Distributions and Uncertainty. https://doi.org/10.5281/zenodo.3879620.
———. 2024b. “ggdist: Visualizations of Distributions and Uncertainty in the Grammar of Graphics.” IEEE Transactions on Visualization and Computer Graphics 30 (1): 414–24. https://doi.org/10.1109/TVCG.2023.3327195.
Maechler, Martin, Peter Rousseeuw, Anja Struyf, Mia Hubert, and Kurt Hornik. 2023. cluster: Cluster Analysis Basics and Extensions. https://CRAN.R-project.org/package=cluster.
Makowski, Dominique, Mattan S. Ben-Shachar, and Daniel Lüdecke. 2019. “bayestestR: Describing Effects and Their Uncertainty, Existence and Significance Within the Bayesian Framework.” Journal of Open Source Software 4 (40): 1541. https://doi.org/10.21105/joss.01541.
Makowski, Dominique, Mattan S. Ben-Shachar, Indrajeet Patil, and Daniel Lüdecke. 2020. “Estimation of Model-Based Predictions, Contrasts and Means.” CRAN. https://github.com/easystats/modelbased.
Mills, Blake Robert. 2022. MetBrewer: Color Palettes Inspired by Works at the Metropolitan Museum of Art. https://CRAN.R-project.org/package=MetBrewer.
Müller, Kirill. 2020. here: A Simpler Way to Find Your Files. https://CRAN.R-project.org/package=here.
Nakazawa, Minato. 2024. fmsb: Functions for Medical Statistics Book with Some Demographic Data. https://CRAN.R-project.org/package=fmsb.
Nowosad, Jakub. 2018. “CARTOColors” Palettes. https://jakubnowosad.com/rcartocolor/.
Opsahl, Tore. 2009. Structure and Evolution of Weighted Networks. University of London (Queen Mary College), London, UK. http://toreopsahl.com/publications/thesis/.
Pedersen, Thomas Lin. 2024. patchwork: The Composer of Plots. https://CRAN.R-project.org/package=patchwork.
R Core Team. 2024. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Rodriguez-Sanchez, Francisco. 2024. network.tools: Tools to Analyse and Visualise Bipartite Networks. https://github.com/Pakillo/network.tools.
Rodriguez-Sanchez, Francisco, and Jean-Gabriel Young. 2024. BayesianNetworks: Bayesian Modelling of Bipartite Networks. https://github.com/Pakillo/BayesianNetworks.
Schloerke, Barret, Di Cook, Joseph Larmarange, Francois Briatte, Moritz Marbach, Edwin Thoen, Amos Elberg, and Jason Crowley. 2024. GGally: Extension to “ggplot2”. https://CRAN.R-project.org/package=GGally.
Slowikowski, Kamil. 2024. ggrepel: Automatically Position Non-Overlapping Text Labels with “ggplot2”. https://CRAN.R-project.org/package=ggrepel.
Tang, Yuan, Masaaki Horikoshi, and Wenxuan Li. 2016. “ggfortify: Unified Interface to Visualize Statistical Result of Popular r Packages.” The R Journal 8 (2): 474–85. https://doi.org/10.32614/RJ-2016-060.
Ushey, Kevin, and Hadley Wickham. 2024. renv: Project Environments. https://CRAN.R-project.org/package=renv.
van den Brand, Teun. 2024. Ggh4x: Hacks for “ggplot2”. https://CRAN.R-project.org/package=ggh4x.
Wickham, Hadley. 2007. “Reshaping Data with the reshape Package.” Journal of Statistical Software 21 (12): 1–20. http://www.jstatsoft.org/v21/i12/.
Wickham, Hadley, Mara Averick, Jennifer Bryan, Winston Chang, Lucy D’Agostino McGowan, Romain François, Garrett Grolemund, et al. 2019. “Welcome to the tidyverse.” Journal of Open Source Software 4 (43): 1686. https://doi.org/10.21105/joss.01686.
Wickham, Hadley, Thomas Lin Pedersen, and Dana Seidel. 2023. scales: Scale Functions for Visualization. https://CRAN.R-project.org/package=scales.
Wilke, Claus O. 2024. ggridges: Ridgeline Plots in “ggplot2”. https://CRAN.R-project.org/package=ggridges.
William Revelle. 2024. psych: Procedures for Psychological, Psychometric, and Personality Research. Evanston, Illinois: Northwestern University. https://CRAN.R-project.org/package=psych.
Xie, Yihui. 2014. “knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC.
———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.
———. 2024. knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.
Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2018. R Markdown: The Definitive Guide. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown.
Xie, Yihui, Christophe Dervieux, and Emily Riederer. 2020. R Markdown Cookbook. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown-cookbook.