R/functional_dissimilarity.R

In allanecology/multiFunBetadivLuiGDM: Testing effects of multitrophic beta-diversity and land-use intensity (LUI) on ecosystem multifunctionality

#' Convert To Presence-Absence
#'
#' Converts a continuous numeric vector into a presence-
#' absence vector.
#' Two methods can be chosen from : "max5" (Soliveres, 2016) and "quantile".
#' The first calculates the mean of the top five values. From that new maximum, 
#' the threshold percentage is taken, e.g. if threshold = 0.5, half of
#' the newly calculated maximum serves as threshold. All values higher than
#' that new threshold are considered to be present (1) and all values
#' below are considered to be absent (0). Limitation : is influenced by outliers, 
#' however for the use of multifunctionality, this makes sense, because it is 
#' possible that a given function is only present at high levels in very few
#' plots, while all other plots show low levels.
#' The "quantile" method takes the threshold-quantile, e.g. the 
#' 50% quantile if the threshold = 0.5. All values above are considered to 
#' be present, all below are considered to be absent. Limitation: will 
#' always classify the same amount of values to be present than to be 
#' absent - inherent to quantile function.
#'
#' @param x input vector
#' @param threshold the threshold for calculation, between 0 and 1, e.g. 0.5
#' @param type is either "max5" or "quantile". "max5" calculates the mean of the
#' maximum 5 values, whereas "quantile" calculates the threshold - quantile.
#' @return a vector of scaled values to be between 0 and 1.
#' 
#' @examples
#' x <- c(0,0.1,0.4,0.5,0.8,0.9,1)
#' calc_presenceabsence(x,treshold=0.3)
#' 
#' @export
calc_presenceabsence <- function(x, threshold = 0.5, type = "max5"){
  # x is a vector
  if(type == "max5"){
    upper <- mean(sort(x,decreasing = T, na.last=T)[1:5])
  } else if(type == "quantile"){
    upper <- quantile(x, probs = threshold)
  } else {
    print("Error : type must be either 'max5' or 'quantile'.")
  }
  new_vector <- x>(upper*threshold)
  return(new_vector)
}

NULL