DAISIEprep is an R package that enables the extraction and formatting
of phylogenetic data on island species for the inference model DAISIE (Dynamic Assembly
of Island biota through Speciation, Immigration and Extinction). The
central function, DAISIEprep::extract_island_species()
,
uses data from phylogenetic trees and species island endemicity statuses
(i.e. endemic to the island, non-endemic, or not present on the island).
The phylogenetic and endemicity data are handled together using the
phylo4d
S4 class from the phylobase
R package.
DAISIEprep fills the niche of standardised, reproducible data
processing for the suite of DAISIE inference models. Unlike other
phylogenetic methods implemented in R, DAISIE has yet to have a defined
methodological framework to extract and format data prior to analysis.
While other phylogenetic models in R commonly use the phylo
S3 data structure, defined by the R package ape
,
DAISIE has an idiosynchratic data structure that will be unfamiliar to
new users. This package provides a set of tools for those users to
facilitate the application of DAISIE’s models for research. The package
also opens the possibility of extracting island data from ‘big data’
macrophylogenies (>5,000 species) which would have impeded
researchers who would have previously had to extract this data
manually.
There are two algorithms to extract the data the min
algorithm or asr
(ancestral state reconstruction)
algorithm. The former is based on the rules/assumptions of the DAISIE
inference model of colonisation of species from mainland source pool,
speciation on the island through cladogenesis or anagenensis, and island
extinction. Therefore, this algorithm assumes no back-colonisation from
the island to the mainland or mainland evolutionary processes. If the
data seems to conform to these assumptions (by visual inspection) then
this is a good method to choose
(DAISIEprep::extract_island_species(..., extraction_method = “min”
).
Alternatively, the data may violate these assumptions, by, for example
having species within an island radiation migrate back to the mainland.
In these, and other cases the asr
algorithm provides a
method to extract data based on the most probable reconstruction of the
species ranges (i.e. island presence/absence) and then can extract
clades that may have non-island species
(DAISIEprep::extract_island_species(..., extraction_method = “asr”
).
The asr
algorithm utilises ancestral state reconstruction
methods from other packages (e.g. castor
),
but the package is flexible to users extending this to incorporate other
models which may better suit their data set.
Install DAISIEprep from CRAN:
install.packages("DAISIEprep")
The development version of DAISIEprep can be installed from GitHub:
if (!requireNamespace("remotes", quietly = TRUE)) install.packages("remotes")
::install_github("joshwlambert/DAISIEprep") remotes
See tutorial.
To report a bug please open an issue or email at j.w.l.lambert@rug.nl.
The DAISIE team always welcomes contributions to any of its packages. If you would like to contribute to this package please follow the contributing guidelines
Please note that the DAISIEprep project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.