check_names: Check species names for inconsistencies

Description

Check species names for inconsistencies

Usage

check_names(
  data,
  colsp = NULL,
  verbose = FALSE,
  pct = 90,
  merge = FALSE,
  sn = FALSE,
  ecosystem = FALSE,
  rm_duplicates = FALSE
)

Value

Data frame or names of corrected or cleaned species names.

Arguments

data: dataframe. Data frame with species names to checked from FishBase.
colsp: string. A column in the data with the species column names.
verbose: logical. To indicate the merges during checking of names. The default is FALSE not to show whether the species are in Fish base or not found.
pct: numeric. The percentage similarity used to assign a relatively similar name from FishBase if the exact match is absent. Default 90 The higher the values, the higher percentage similarity are considered to replace a species name that is cheeked from Fishbase.
merge: logical. Default is FALSE, not to merge the cleaned species column on to the data frame but rather only two columns returned.
sn: logical. Whether to consider synonyms. Default FALSE so accepted names will be considered from FishBase database.
ecosystem: logical Returns whether the species is freshwater, marine , or brackish or a combination for for estuarine loving species.
rm_duplicates: logical. If TRUE, removes all duplicate species names especially when a dataframe is is the output from the function.

Details

The function produces a data set with species names corresponding with Fishase. If synonym is provided in the data set, the function will by defualt return the accepted name. However, if the synoymn is desired, then set the sn parameter to TRUE. The function also check for spellings of species names and returns a name that is closer to the one in FishBase with a particular degree of similarity set with pct parameter. pct of 1 indicates the name must 100 The user can iterate with different pct and decide if the return name is right or wrong. This function is not necessary if the species names are clean and also for other taxa.

Examples

Run this code


if (FALSE) {

data(jdsdata)

data(efidata)

#step 1. match and bind datasets if more than one datasets

matchdata <- match_datasets(datasets = list(jds = jdsdata, efi = efidata),
                          lats = 'lat',
                          lons = 'lon',
                          species = c('speciesname','scientificName'),
                          country=c('JDS4_site_ID'),
                          date=c('Date', 'sampling_date'))

#clean species names to produce one dataset.

datafull <- check_names(data= matchdata, colsp='species', pct = 90, merge = TRUE)

data2col <- check_names(data = matchdata, colsp='species', pct = 90) #two columns generated

cleansp_name <- check_names(data= 'slamo trutta', pct=90) #wrong names vs FB suggestion

clean_sp_epithet <- check_names(data = 'Salmo trutta fario') #Salmo trutta will be returned

speciesepithet2 <- check_names(data = 'Salmo trutta lacustris', pct=90)

}