Biogeographic Regionalization and Macroecology
Add arc labels to plotted phylogeny
Taxonomic (non-phylogenetic) beta diversity
Computes biodiversity coldspots and hotspots
Collapse nodes and ranges based on divergence times
Phyloregions for functional traits and phylogeny
Evolutionary Distinctiveness and Global Endangerment
Species' evolutionary distinctiveness
Create fishnet of regular grids
Fits Grade of membership models for biogeographic regionalization
Functional beta diversity for mixed-type functional traits
Get descendant nodes of phylogeny at a given time depth
Generate diverging colors in HCL colour space.
Top driving species in phyloregions
Conversion of community data
Map species' trait values in geographic space
Match taxa and in phylogeny and community matrix
Mean distance matrix from a set of distance matrices
Label phylogenetic nodes using pie
Determine optimal number of clusters
Phylogenetic diversity
Phylogenetic diversity standardized for species richness
Phylogenetic Endemism
Phylogenetic beta diversity
Phylogenetic beta diversity standardized for species beta diversity
Create a subtree with largest overlap from a species list.
Biogeographic regionalization and macroecology
Compute phylogenetic regionalization and evolutionary distinctiveness ...
Visualize biogeographic patterns
Create illustrative sparse matrix
Visualize biogeographic patterns using pie charts
Generate random species distributions in space
Convert raw input distribution data to community
Read in sparse community matrices
Objects exported from other packages
Species distribution models
Cluster algorithm selection and validation
Select polygon features from another layer and adds polygon attributes...
Slice phylogenetic tree at various time depths
UniFrac distance
Measure the distribution of narrow-ranged or endemic species.
Computational infrastructure for biogeography, community ecology, and biodiversity conservation (Daru et al. 2020) <doi:10.1111/2041-210X.13478>. It is based on the methods described in Daru et al. (2020) <doi:10.1038/s41467-020-15921-6>. The original conceptual work is described in Daru et al. (2017) <doi:10.1016/j.tree.2017.08.013> on patterns and processes of biogeographical regionalization. Additionally, the package contains fast and efficient functions to compute more standard conservation measures such as phylogenetic diversity, phylogenetic endemism, evolutionary distinctiveness and global endangerment, as well as compositional turnover (e.g., beta diversity).
Useful links