R/fd_fdis.R

In Bisaloo/fundiversity: Easy Computation of Functional Diversity Indices

#' Compute Functional Dispersion (FDis)
#'
#' This function computes Functional Dispersion (FDis) following Laliberté &
#' Legendre (2010). NB: when a site contains no species FDis is equal to 0.
#'
#' @inheritParams fd_fdiv
#'
#' @inheritSection fd_fric Parallelization
#'
#' @examples
#' data(traits_birds)
#' data(site_sp_birds)
#' fd_fdis(traits_birds, site_sp_birds)
#'
#' @return a data.frame with two columns:
#' * `site` the names of the sites as the row names of the input `sp_com`,
#' * `FDis` the values of functional dispersion at each site.
#'
#' ```{r child = "man/rmdchunks/no_row_names.Rmd"}
#' ```
#'
#' NB: when a site contains no species FDis is equal to 0.
#'
#' @references
#' Laliberté, E., & Legendre, P. (2010). A distance-based framework for
#' measuring functional diversity from multiple traits. Ecology, 91(1),
#' 299–305. \doi{10.1890/08-2244.1}
#'
#' @importFrom future.apply future_apply
#' @export
fd_fdis <- function(traits, sp_com) {

  if (missing(traits) || is.null(traits)) {
    stop("Please provide a trait dataset", call. = FALSE)
  }

  if (is.data.frame(traits) || is.vector(traits)) {
    traits <- as.matrix(traits)
  }

  if (!is.numeric(traits)) {
    stop("Non-continuous trait data found in input traits. ",
         "Please provide only continuous trait data", call. = FALSE)
  }

  traits <- remove_species_without_trait(traits)

  if (!missing(sp_com)) {

    common_species <- species_in_common(traits, sp_com)

    traits <- traits[common_species,, drop = FALSE]
    sp_com <- sp_com[, common_species, drop = FALSE]

  } else {

    sp_com <- matrix(1, ncol = nrow(traits),
                     dimnames = list("s1", rownames(traits)))

  }

  if (is.data.frame(sp_com)) {

    sp_com <- as.matrix(sp_com)

  }

  if (is.null(rownames(sp_com))) {

    rownames(sp_com) <- paste0("s", seq_len(nrow(sp_com)))

  }

  # Standardize abundance per site
  site_abundances <- rowSums(sp_com, na.rm = TRUE)
  site_abundances[site_abundances == 0] <- 1  # Account for site with no species
  sp_com <- sp_com / site_abundances

  centros <- sp_com %*% traits

  dists_centro <- future_apply(
    centros, 1, function(centro) {

    sqrt(colSums((t(traits) - centro)^2))

    }, future.globals = FALSE
  )

  fdis_site <- diag(sp_com %*% dists_centro)

  data.frame(site = rownames(sp_com), FDis = fdis_site, row.names = NULL)
}