Skip to contents

A function to check for and count potential spelling variations of the same taxon. Spelling variations are checked within alphabetical groups (default), or within higher taxonomic groups if provided.


  name = "genus",
  group = NULL,
  dis = 0.05,
  start = 1,
  verbose = TRUE



dataframe. A dataframe with named columns containing taxon names (e.g. "species", "genus"). An optional column containing the groups (e.g. "family", "order") which taxon names belong to may also be provided (see group for details). NA values or empty strings in the name and group columns (i.e. "" and " ") are ignored.


character. The column name of the taxon names you wish to check (e.g. "genus").


character. The column name of the higher taxonomic assignments in taxdf you wish to group by. If NULL (default), name comparison will be conducted within alphabetical groups.


numeric. The dissimilarity threshold: a value greater than 0 (completely dissimilar), and less than 1 (completely similar). Potential synonyms above this threshold are not returned. This value is set to 0.05 by default, but the user might wish to experiment with this value for their specific data.


numeric. The number of shared characters at the beginning of potential synonyms that should match. Potential synonyms below this value will not be returned. By default this value is set to 1 (i.e. the first letter of synonyms must match).


logical. Should the results of the non-letter character check be reported to the user? If TRUE, the result will only be reported if such characters are detected in the taxon names.


If verbose = TRUE (default), a list with three elements. The first element in the list (synonyms) is a data.frame with each row reporting a pair of potential synonyms. The first column "group" contains the higher group in which they occur (alphabetical groupings if group is not provided). The second column "greater" contains the most common synonym in each pair. The third column "lesser" contains the least common synonym in each pair. The third and fourth column (count_greater, count_lesser) contain the respective counts of each synonym in a pair. If no matches were found for the filtering arguments, this element is NULL instead. The second element (non_letter_name) is a vector of taxon names which contain non-letter characters, or NULL if none were detected. The third element (non_letter_group) is a vector of taxon groups which contain non-letter characters, or NULL if none were detected. If verbose = FALSE, a data.frame as described above is returned, or NULL if no matches were found.


When higher taxonomy is provided, but some entries are missing, comparisons will still be made within alphabetical groups of taxa which lack higher taxonomic affiliations. The function also performs a check for non-letter characters which are not expected to be present in correctly-formatted taxon names. This detection may be made available to the user via the verbose argument. Comparisons are performed using the Jaro dissimilarity metric via stringdist::stringdistmatrix().

As all string distance metrics rely on approximate string matching, different metrics can produce different results. This function uses Jaro distance as it was designed with short, typed strings in mind, but good practice should include comparisons using multiple metrics, and ultimately specific taxonomic vetting where possible. A more complete implementation and workflow for cleaning taxonomic occurrence data is available in the fossilbrush R package on CRAN.


van der Loo, M. P. J. (2014). The stringdist package for approximate string matching. The R Journal 6, 111-122.


Joseph T. Flannery-Sutherland & Lewis A. Jones


Lewis A. Jones, Kilian Eichenseer & Christopher D. Dean


# load occurrence data
# Check taxon names alphabetically
ex1 <- tax_check(taxdf = tetrapods, name = "genus", dis = 0.1)
# Check taxon names by group
ex2 <- tax_check(taxdf = tetrapods, name = "genus",
                 group = "family", dis = 0.1)
#> Warning: Non-letter characters present in the group names