Comparison of Bioregionalization Methods R package bioregion version 1.4.0 The main purpose of this package is to propose a transparent methodological framework to compare bioregionalization methods based on hierarchical and non-hierarchical clustering algorithms (Kreft & Jetz (2010) <doi:10.1111/j.1365-2699.2010.02375.x>) and network algorithms (Lenormand et al. (2019) <doi:10.1002/ece3.4718> and Leroy et al. (2019) <doi:10.1111/jbi.13674>). Software Depends: R (>= 4.0.0) Imports: ape, apcluster, bipartite, cluster, data.table, dbscan, dynamicTreeCut, fastcluster, fastkmedoids, ggplot2, grDevices, httr, igraph, mathjaxr, Matrix, phangorn, rcartocolor, Rdpack, rlang, rmarkdown, segmented, sf, stats, tidyr, utils LinkingTo: Rcpp Suggests: ade4, adespatial, betapart, dplyr, ecodist, knitr, microbenchmark, rnaturalearth, rnaturalearthdata, terra, testthat (>= 3.0.0), vegan Maxime Lenormand <maxime.lenormand@inrae.fr> Comprehensive R Archive Network (CRAN) Maxime Lenormand [aut, cre] (ORCID: <https://orcid.org/0000-0001-6362-3473>), Boris Leroy [aut] (ORCID: <https://orcid.org/0000-0002-7686-4302>), Pierre Denelle [aut] (ORCID: <https://orcid.org/0000-0001-5037-2281>) GPL-3 2026-03-29 application/tgz https://CRAN.R-project.org/package=bioregion doi:10.32614/CRAN.package.bioregion