Defining biogeographic regions based on phylogenetic turnover
calc_evoregions.RdDefining biogeographic regions based on phylogenetic turnover
Usage
calc_evoregions(
comm,
phy,
max.n.clust = NULL,
method.dist = "bray",
tresh.dist = 0.05,
method.clust = "kmeans",
stat.clust = "BIC",
n.iter.clust = 1e+07,
criterion.clust = "diffNgroup",
seed = NULL
)Arguments
- comm
Species occurrence matrix. Assemblages are rows and species are columns
- phy
phylogenetic tree of class
phylocontaining the species incomm.- max.n.clust
Integer value to be used in
find.clusters. Indicates the maximum number of clusters to be tried. If NULL (the default) the function usesoptimal_phyloregionfunction from phyloregion package to determine the optimal number of clusters. This function is based on the "elbow"/"knee" method. See details.- method.dist
Character. The method to be used to compute phyogenetic distances among assemblages. Dissimilarity index, as accepted by
vegdist(Default "bray").- tresh.dist
A scalar informing the threshold value to select eigenvectors based on the amount of variation of each eigenvector. Default is 0.05 (eigenvector with at least 5% of variation). See details.
- method.clust
Character indicating the grouping algorithm to be used in cluster analysis. Options avalible are "kmeans" (default) or "ward".
- stat.clust
Character to be used in
find.clustersindicating the statistic to be computed for each model. Can be "BIC" (default), "AIC" or "WSS".- n.iter.clust
Integer to be used in
find.clustersfunction of adegenet package to indicate the number of iterations to be used in each run of K-means algorithm- criterion.clust
Character string matching "diffNgroup" (default), "min", "goesup", "smoothNgoesup", or "goodfit", indicating the criterion for automatic selection of the optimal number of clusters. See
criterionargument infind.clustersfor an explanation of these procedures.- seed
default NULL. Set a seed to the
find.clusters, which provides the same names for cluster groups
Value
A list of length four containing:
PCPSA matrix with PCPS vectorscluster_evoregionsA vector indicating the region in which each assemblage was classified
Details
evoregions performs biogeographical regionalization based on phylogenetic turnover. Unlike other approaches, it uses a fuzzy‐set–based metric of phylogenetic dissimilarity that incorporates features of evolutionary history (e.g., tree imbalance). This allows evoregions to capture variation in lineage diversification and historical relationships that are not accounted for by conventional phylogenetic turnover metrics.
Some important details when running evoregions
See also
find_max_nclust to decide the maximum number of clusters to be
used
Examples
if (FALSE) { # \dontrun{
data(akodon_sites) # occurrence data
data(akodon_newick) # phylogenetic tree
akodon_pa <- akodon_sites %>%
dplyr::select(-LONG, -LAT)
spp_in_tree <- names(akodon_pa) %in% akodon_newick$tip.label
akodon_pa_tree <- akodon_pa[, spp_in_tree]
regions <- calc_evoregions(comm = akodon_pa_tree, phy = akodon_newick)
site_region <- regions$cluster_evoregions # classification of each community in regions
} # }