Adds columns to a traitdata object containing accepted species names and relates to globally unique taxon identifiers via URI.

standardize.taxonomy(x, method = get_gbif_taxonomy, subspecies = TRUE,
fuzzy = TRUE, verbose = FALSE, return = c("kingdom", "phylum", "class",
"order", "family"), ...)

## Arguments

x a traitdata object (as returned by as.traitdata()) or a data table containing at least the column scientificName. only option is get_gbif_taxonomy. In principle, takes any function that maps the species names in x to produce a taxonomy lookup table (i.e. mapping user-provided scientificName to taxonID and other taxon-level information). Will allow to chose from different sources of taxonomic reference. logical. If TRUE (default), the given name is resolved to subspecies epithet, otherwise it will be mapped to species level. if set to FALSE (default mode), this disables fuzzy matching if problems with ambiguous species names arise. (see ?get_gbif_testing()) has currently no effect. a character vector containing the informatoin that should be extracted into the output. Valid entries are the column names returned by function get_gbif_taxonomy(). See 'Details'.

## Details

Taxonomic standardisation is an enormous challenge for biodiversity data management and research. Constant changes in species and higher taxa, refinements of phylogenetic trees and changing attribution to original authors, moving species into other genera or difficulties to place species into the Linean nomenclature results in highly fluctuent taxonomic definitions.

As a consequence, there is not one reference for accepted species names and dependin on the field of resaerch and taxonomic focus other authorities will be employed.

For reasons of simplicity and because of its high coverage of taxa, the function standardize.taxonomy() uses the GBIF Backbone Taxonomy as its reference system and resolves all provided species names to the accepted name according to GBIF (resolving misspellings and synonyms in the process). We invite pull requests to make this function more general and enable a choice of a taxonomic reference.

## Examples



pulldata("carabids")#> The dataset 'carabids' is now available for use!
dataset1 <- as.traitdata(carabids,
taxa = "name_correct",
traits = c("body_length", "antenna_length", "metafemur_length"),
units = "mm",
keep = c(datasetID = "source_measurement", measurementRemark = "note"),
dataset1Std <- standardize.taxonomy(dataset1)`