Make taxonomy lookups

Usage

make_gbif_taxonomy(
  df,
  taxa_col = "original_name",
  taxonomy_file,
  target_rank = "species",
  limit = TRUE,
  fixes = NULL,
  overrides = NULL,
  ...
)

Arguments

df: Dataframe with taxa_col.
taxa_col: Character. Name of column in df with taxa names
taxonomy_file: Character. Path to results from envClean::get_taxonomy()
target_rank: Character. Default is 'species'. At what level of the taxonomic hierarchy are results desired. This is the most detailed taxonomy returned. i.e. if genus is the target_rank, no taxa below genus are returned. See envClean::lurank rank column.
limit: Logical. If true (default), the output taxonomy will be limited to the input names in df. Otherwise, all taxa found in taxonomy_file will be returned.
fixes: Data frame with columns resolved_to and prefer. Any taxa result in lutaxa that matches a name in resolved_to will be changed to prefer. Mainly used where legitimate names are used in areas where they do not exist. e.g. Eastern osprey Pandion cristatus does not occur in South Australia but records of this species in South Australia are assumed to be legitimate Osprey (Pandion haliaetus) records.
overrides: Data frame with columns original and prefer. Any original_name result in lutaxa that matches a name in original will be have its corresponding taxa changed to prefer. Useful where GBIF Backbone Taxonomy provides a spurious result. e.g. The GBIF Backbone Taxonomy changes Thinornis rubricollis to Phalaropus lobatus rather than the preferred Charadrius cucullatus.
...: Passed to envClean::get_taxonomy()

Value

named list with elements:

lutaxa: Dataframe. For each unique name in taxa_col, the best taxa to use (taking into account target_rank)
taxonomy: Dataframe. For each taxa in lutaxa a row of taxonomic hierarchy and matching gbif usageKeys