betapart: Partitioning beta diversity into turnover and nestedness components
Description
betapart allows computing pair-wise dissimilarities (distance matrices),
multiple-site dissimilarities and temporal changes in comunity composition,
separating the turnover and nestedness components of beta diversity as described in Baselga (2010).Details
The partitioning of beta diversity 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. beta diversity. The multiple site function beta.multi
yields the spatial turnover and the nestedness components of overall beta diversity, and the sum
of both components, i.e. beta diversity. The basic calculations for all these multiple-site measures and 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.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, in press