betapart-package: Partitioning beta diversity into turnover and nestedness...
In betapart: Partitioning Beta Diversity into Turnover and Nestedness Components
Description
Details
Author(s)
References
Description
betapart allows computing pair-wise dissimilarities (distance matrices) and multiple-site dissimilarities, separating the turnover and nestedness-resultant components of taxonomic (incidence and abundance based), functional and phylogenetic beta diversity.
Details
The partitioning of incidence-based dissimilarity can be performed for two different families of indices:
Sorensen and Jaccard. The pairwise function beta.pair yields 3 distance matrices accounting
for the spatial turnover and the nestedness components of beta-diversity. The third distance
matrix accounts for the sum of both componentes, i.e. totaal dissimilarity (a monotonic transoformation
of beta diversity.
The multiple site function beta.multi yields the spatial turnover and the nestedness components of
overall dissimilarity, and the sum of both components, total dissimilarity. The basic calculations for all these
multiple-site measures and pairwise dissimilarity matrices can be computed using the function betapart.core,
which returns an object of class betapart. This is useful for large datasets as the consuming calculations
are done only once, and its result can then be used for computing many indices.
The multiple-site values can be randomly sampled a specified number of times for a specified number of sites using
the function beta.sample.
The aforementioned indices used for assessing spatial patterns can also be used for measuring temporal changes in community composition with the
function beta.temp.
Likewise, an analogous framework has been implemented for separating the two components of abundance-based
dissimilarity (balanced changes in abundance vs. abundance gradients) using commands beta.pair.abund, beta.multi.abund, betapart.core.abund, and beta.sample.abund.
The framework has been extended for functional beta diversity with commands functional.betapart.core,
functional.beta.pair and functional.beta.multi, and for phylogenetic beta diversity with commands phylo.betapart.core,
phylo.beta.pair and phylo.beta.multi.
Author(s)
Andrés Baselga, David Orme, Sébastien Villeger, Julien De Bortoli and Fabien Leprieur
References
Baselga, A. 2010. Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography 19:134-143
Baselga, A. 2012. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness.
Global Ecology and Biogeography 21, 1223-1232
Baselga, A. 2013. Separating the two components of abundance-based dissimilarity: balanced changes in abundance vs.
abundance gradients. Methods in Ecology and Evolution, 4: 552-557
Baselga, A. 2017. Partitioning abundance-based multiple-site dissimilarity into components: balanced variation in abundance and
abundance gradients. Methods in Ecology and Evolution, in press
Baselga A, Leprieur, F. 2015. Comparing methods to separate components of beta diversity. Methods in Ecology and Evolution 6: 1069-1079
Baselga A, Orme CDL. 2012. betapart: an R package for the study of beta diversity. Methods Ecol. Evol. 3: 808-812
Legendre P. 2014. Interpreting the replacement and richness difference components of beta diversity. Global Ecology and Biogeography, 23: 1324–1334
Leprieur F, Albouy C, De Bortoli J, Cowman PF, Belwood DR, Mouillot D. 2012. Quantifying phylogenetic beta diversity:
distinguishing between "true" turnover of lineages and phylogenetic diversity gradients. PLoS One 7(8): e42760
Villéger, S. Grenouillet, G., Brosse, S. 2013. Decomposing functional beta-diversity reveals that low functional
beta-diversity is driven by low functional turnover in European fish assemblages. Global Ecology and Biogeography, 22: 671-681
betapart documentation built on May 2, 2019, 6:10 p.m.
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Description Details Author(s) References
Description
betapart allows computing pair-wise dissimilarities (distance matrices) and multiple-site dissimilarities, separating the turnover and nestedness-resultant components of taxonomic (incidence and abundance based), functional and phylogenetic beta diversity.
Details
The partitioning of incidence-based dissimilarity can be performed for two different families of indices:
Sorensen and Jaccard. The pairwise function beta.pair yields 3 distance matrices accounting
for the spatial turnover and the nestedness components of beta-diversity. The third distance
matrix accounts for the sum of both componentes, i.e. totaal dissimilarity (a monotonic transoformation
of beta diversity.
The multiple site function beta.multi yields the spatial turnover and the nestedness components of
overall dissimilarity, and the sum of both components, total dissimilarity. The basic calculations for all these
multiple-site measures and pairwise dissimilarity matrices can be computed using the function betapart.core,
which returns an object of class betapart. This is useful for large datasets as the consuming calculations
are done only once, and its result can then be used for computing many indices.
The multiple-site values can be randomly sampled a specified number of times for a specified number of sites using
the function beta.sample.
The aforementioned indices used for assessing spatial patterns can also be used for measuring temporal changes in community composition with the
function beta.temp.
Likewise, an analogous framework has been implemented for separating the two components of abundance-based
dissimilarity (balanced changes in abundance vs. abundance gradients) using commands beta.pair.abund, beta.multi.abund, betapart.core.abund, and beta.sample.abund.
The framework has been extended for functional beta diversity with commands functional.betapart.core,
functional.beta.pair and functional.beta.multi, and for phylogenetic beta diversity with commands phylo.betapart.core,
phylo.beta.pair and phylo.beta.multi.
Author(s)
Andrés Baselga, David Orme, Sébastien Villeger, Julien De Bortoli and Fabien Leprieur
References
Baselga, A. 2010. Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography 19:134-143
Baselga, A. 2012. The relationship between species replacement, dissimilarity derived from nestedness, and nestedness. Global Ecology and Biogeography 21, 1223-1232
Baselga, A. 2013. Separating the two components of abundance-based dissimilarity: balanced changes in abundance vs. abundance gradients. Methods in Ecology and Evolution, 4: 552-557
Baselga, A. 2017. Partitioning abundance-based multiple-site dissimilarity into components: balanced variation in abundance and abundance gradients. Methods in Ecology and Evolution, in press
Baselga A, Leprieur, F. 2015. Comparing methods to separate components of beta diversity. Methods in Ecology and Evolution 6: 1069-1079
Baselga A, Orme CDL. 2012. betapart: an R package for the study of beta diversity. Methods Ecol. Evol. 3: 808-812
Legendre P. 2014. Interpreting the replacement and richness difference components of beta diversity. Global Ecology and Biogeography, 23: 1324–1334
Leprieur F, Albouy C, De Bortoli J, Cowman PF, Belwood DR, Mouillot D. 2012. Quantifying phylogenetic beta diversity: distinguishing between "true" turnover of lineages and phylogenetic diversity gradients. PLoS One 7(8): e42760
Villéger, S. Grenouillet, G., Brosse, S. 2013. Decomposing functional beta-diversity reveals that low functional beta-diversity is driven by low functional turnover in European fish assemblages. Global Ecology and Biogeography, 22: 671-681
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