Baselga A, Orme CDL, Villéger S, De Bortoli J, Leprieur F., Logez M. 2020. betapart: Partitioning beta diversity into turnover and nestedness components. R package version 1.5.2. Available at: http://CRAN.R-project.org/package=betapart
To install this package directly within R type:
The reference manual can be downloaded from the CRAN server.
To read more about betapart see Baselga and Orme 2012 (Methods Ecol. Evol. 3: 808-8012), and references below.
betapart 1.5.2 (2020-sep-09) New!
Version betapart 1.5.2 includes an updated functional.betapart.core() function to allow internal parallel computing, and a new function beta.para.control() to customize parameters for the internal parallel computing. A very relevant contribution by Maxime Logez and Sebastien Villéger.
betapart 1.5.1 (2018-oct-17)
Version betapart 1.5.1 comes with an updated, faster functional.betapart.core() function that now allows parallel computing. It is a very useful contribution by Maxime Logez and Renato Henriques-Silva (https://github.com/RenatoHS).
betapart 1.5.0 (2018-feb-22)
Version betapart 1.5.0 includes new functions to fit, plot and bootstrap distance-decay patterns: decay.model() fits a negative-exponential or power law function describing the decay of assemblage similarity with sptatial distance; plot.decay() allows plotting the curves fitted with decay.model(); and boot.coefs.decay() bootstraps the parameters of the functions fitted with decay.model(). The methods are fully described in Gómez-Rodríguez & Baselga 2018 (Ecography)
betapart 1.4 (2017-jan-24)
Version betapart 1.4 extends the partitioning framework to abundance-based multiple-site dissimilarity. The functions betapart.core.abund(), beta.pair.abund(), beta.multi.abund(), and beta.sample.abund() allow the decomposition of the multiple-site versions of Bray-Curtis and Ruzicka indices of dissimilarity into two separate components accounting for (i) the dissimilarity derived from balanced variation in abundance between sites, and (ii) the dissimilarity derived from unidirectional abundance gradients. The methods are fully described in Baselga 2017 (Methods Ecol. Evol. 8: 799-808)
betapart 1.3 (2013-dec-12)
Version betapart 1.3 extends the partitioning framework to phylogenetic beta diversity. The functions phylo.betapart.core(), phylo.beta.pair(), and phylo.beta.multi() allow the partition of the dissimilarity in phylogenetic composition between communities into a phylogenetic turnover and a phylogenetic nestedness-resultant component. This method is fully described in Leprieur et al. 2012 (PLoS ONE 7(8): e42760).
betapart 1.2 (2013-feb-12)
Version betapart 1.2 extends the partitioning framework to functional beta diversity. The functions functional.betapart.core(), functional.beta.pair(), and functional.beta.multi() allow the partition of the dissimilarity in functional composition between communities into a functional turnover and a functional nestedness-resultant component. This method is fully described in Villeger et al. 2013 (Global Ecol. Biogeogr. 22: 671–681).
Moreover, version betapart 1.2 also provides an analogous partition for the pairwise abundance-based Bray-Curtis dissimilarity. The new function bray.part() allows the decomposition of the popular Bray-Curtis index of dissimilarity into two separate components accounting for (i) the dissimilarity derived from balanced variation in abundance between sites, and (ii) the dissimilarity derived from unidirectional abundance gradients. This method is fully described in Baselga 2013 (Methods Ecol. Evol. 4: 552–557).
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