speciesRarity.RdThis function takes in data for a recorder and calculates the recorder's rarity metrics.
speciesRarity(recorder_name, data, sp_col = "preferred_taxon", recorder_col = "recorders")
| recorder_name | the name of the recorder for whom you want to calculate the metrics |
|---|---|
| data | the data.frame of recording information |
| sp_col | the name of the column that contains the species names |
| recorder_col | the name of the column that contains the recorder names |
A data.frame with seven columns
recorder - The name of the recorder, as given in the recorder_name argument
median_rarity - The median rarity of all observations made by the recorder
median_diff_rarity - The median rarity of an recorders observations subtracted from the median rarity across all observers. Negative numbers mean a recorder is recording more common species than the population of recorders as a whole. Positive numbers mean the recorder is recording more rare species than the population of recorders as a whole.
stdev - The standard deviation of the rarity ranks of a recorders observations
n - The total number of observations made by this recorder
This function examines the rarity of the species that a recorder observes and compares this to the rarity of species recorded across all recorders. First all species are ranked by rarity across all observations from all recorders. These ranks are then scaled to 100 so that the metrics are independent of the number of species in the group. Each observation, in the entire dataset is then assigned a value for the ranked rarity of the species observed and a median is calculated. This median is therefore the median ranked rarity of species observed, where 1 is the most common species and 100 the rarest (ranks are scaled to 100). The median rarity for the individual recorder is calculated in the same way, but using the species' rank values from the overall dataset.
# NOT RUN { # load example data head(cit_sci_data) # Run for a single recorder SR <- speciesRarity(recorder_name = 3007, data = cit_sci_data, sp_col = 'species', recorder_col = 'recorder') # Run the metric for all recorders SR_all <- lapply(unique(cit_sci_data$recorder), FUN = speciesRarity, data = cit_sci_data, sp_col = 'species', recorder_col = 'recorder') # summarise as one table SR_all_sum <- do.call(rbind, SR_all) hist(SR_all_sum$median_diff_rarity, breaks = 20) # }