betaUniqueness {adiv} | R Documentation |

The function `betaUniqueness`

calculates uniqueness and redundancy taking account of functional dissimilarities between species using equation 5 and 6 in Ricotta et al. (2021). Note that functional dissimilarities could be replaced by any other type of dissimilarities between species, including phylogenetic dissimilarities.

betaUniqueness(comm, dis, Nind = 10000)

`comm` |
a matrix containing the relative or absolute abundance of all species in plots. Columns are species and plots are rows. Column labels (species names) should be assigned as in |

`dis` |
a matrix or an object of class dist providing the functional dissimilarities between species (dissimilarities are nonnegative, symmetric, and the dissimilarity between a species and itself is zero). |

`Nind` |
an integer. The algorithmic index will be applied by assuming that each plot contains |

The function `betaUniqueness`

returns a list with the following objects:

- betaUniqueness: a matrix with the values of the proposed beta uniqueness (*Ubeta*=DKG/DR) for each pair of plots (Ricotta et al. (2021), eq. 6);

- betaRedundancy: a matrix with the values of the proposed beta redundancy (*Rbeta*=1-DKG/DR) for each pair of plots (Ricotta et al. (2021), eq. 5);

- dissimilarityGap: a matrix with the values of the dissimilarity gap index (DR-DKG) for each pair of plots;

- DR: a matrix with the values of the species-based (Rogers) dissimilarity index (DR) for each pair of plots (Ricotta et al. (2021), eq. 4);

- DKG: a matrix with the values of the algorithmic functional dissimilarity index (DKG) for each pair of plots (Ricotta et al. (2021), eq. 3).

Sandrine Pavoine sandrine.pavoine@mnhn.fr

Ricotta, C., Kosman, E., Laroche, F., Pavoine, S. (2021) Beta redundancy for functional ecology. *Methods in Ecology and Evolution*, **12**, 1062–1069. doi: 10.1111/2041-210X.13587

Gregorius, H.-R., Gillet, E.M., Ziehe, M. (2003) Measuring differences of trait distributions between populations. *Biometrical Journal*, **8**, 959–973. doi: 10.1002/bimj.200390063

`betaTreeUniqueness`

adapted to the use of phylogenetic trees with species as tips, `dislptransport`

for the algorithmic functional dissimilarity index (DKG in Ricotta et al. 2021), and `uniqueness`

for alpha uniqueness

## Not run: data(RutorGlacier) fundis <- dist(scale(RutorGlacier$Traits2[1:6])) fundis <- fundis/max(fundis) frameDKG <- betaUniqueness(RutorGlacier$Abund, fundis) f1 <- unlist(sapply(1:58, function(i) rep(RutorGlacier$Fac[i], 59-i))) f2 <- unlist(sapply(1:58, function(i) RutorGlacier$Fac[-(1:i)])) f <- paste(f1, f2, sep="-") F <- factor(f, levels=c("early-early", "mid-mid", "late-late", "early-mid", "mid-late", "early-late")) vbetaU_A <- as.vector(as.dist(frameDKG$betaUniqueness)) boxplot(vbetaU_A~F, ylab="Beta uniqueness", xlab="Compared successional stages") # See Ricotta et al. 2021 Electronic Appendix 3 for for details ## End(Not run)

[Package *adiv* version 2.1.1 Index]