betapart {betapart} | R Documentation |

## Partitioning beta diversity into turnover and nestedness components

### 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 components, i.e. total dissimilarity (a monotonic transformation
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`

.
The package also allows fitting negative exponential, power law or Gompertz distance-decay models for assessing the relationship between assemblage (dis)similarity and spatial (or other) distance. `decay.model`

fits the nonlinear distance-decay function via the minpack.lm package, `plot.decay`

plots the distance-decay pattern and the fitted model, `boot.coefs.decay`

bootstraps the paramaters of the distance-decay model, and `zdep`

assesses the differences between parameters of two distance-decay models.

### Author(s)

Andres Baselga, David Orme, Sebastien Villéger, Julien De Bortoli, Fabien Leprieur, Maxime Logez, Sara Martínez-Santalla, Ramiro Martín-Devasa, Carola Gómez-Rodríguez, and Rosa M. Crujeiras

### 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 8: 799-808

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

Gómez-Rodríguez, C. & Baselga, A. 2018. Variation among European beetle taxa in patterns of distance decay of similarity suggests a major role of dispersal processes. Ecography, in press

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

Martín-Devasa R, Martínez-Santalla S, Gómez-Rodríguez C, Crujeiras RM, Baselga A. 2022. Species range size shapes distance decay in community similarity. Diversity and Distributions 28: 1348-1357

Martín-Devasa R, Martínez-Santalla S, Gómez-Rodríguez C, Crujeiras RM, Baselga A. 2022. Comparing distance-decay parameters: a novel test under pairwise dependence. Ecological Informatics 72: 101894

Martínez-Santalla S, Martín-Devasa R, Gómez-Rodríguez C, Crujeiras RM, Baselga A. 2022. Assessing the non-linear decay of community similarity: permutation and site-block resampling significance tests. Journal of Biogeography 49: 968-978

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*version 1.6 Index]