Predict Extinction Risk from IUCN status based on EDGE2 quantification

predict_extinction_risk_iucn_status.R

#' Extinction probablity based on IUCN status
#' 
#' This function returns an extinction probability based on a IUCN Red List
#' status. The extinction probability it returns is based on the EDGE2 metric as
#' defined by Gumbs et al. (2023) <doi:10.1371/journal.pbio.3001991>.
#' In particular, it returns the Global Endangerment 2 score (GE2).
#' See their Figure 1, Supplementary Info S1 for more information and the
#' underlying data with data sheet S4.
#' 
#' The idea is that each IUCN status is associated with a median extinction risk
#' with the risk doubling as going from least to most endangered species.
#' The function is than completed to be continuous and curved from 0.0001 to
#' 0.9999 (never assigning a extinction risk of 1).
#' To convey uncertainty, species are randomly assigned an extinction risk
#' within each status category in a way that the median probability is the one
#' assigned to the Red List status.
#' 
#' @param redlist_status `character(1)` defining the IUCN Red List status
#'   it can be:
#'     * `"LC"`, for Least Concern,
#'     * `"NT"`, for Near Threatened,
#'     * `"VU"`, for Vulnerable,
#'     * `"EN"`, for Endangered,
#'     * `"CR"`, for Critically Endangered,
#'     * `"EW"`, for Extinct in the Wild,
#'     * `"EX"`, for Extinct,
#'     * `"DD"`, for Data Deficient,
#'     * `"NE"` or `NA`, for Not evaluated species
extinction_risk_iucn_status = function(
    redlist_status = c("LC", "NT", "VU", "EN", "CR", "EW", "EX", "DD", "NE", NA)
) {
  
  redlist_status = match.arg(redlist_status)
  
  switch(
    redlist_status,
    `NA` = runif(1, min = 0.0001,    max = 0.9999),
    "DD" = runif(1, min = 0.0001,    max = 0.9999),
    "NE" = runif(1, min = 0.0001,    max = 0.9999),
    "LC" = runif(1, min = 0.0001,    max = 0.0909375),
    "NT" = runif(1, min = 0.0909375, max = 0.181875),
    "VU" = runif(1, min = 0.181875,  max = 0.36375),
    "EN" = runif(1, min = 0.36375,   max = 0.60625),
    "CR" = runif(1, min = 0.60625,   max = 0.9999)
  )
  
}

I'm not entirely sure of the bounds here, the medians seem off.
I've contacted Rikki Gumbs to know more about the function they used.
Let's see and revisit later.