R/get_wege_function.R

In WEGE: A Metric to Rank Locations for Biodiversity Conservation

#' @title get_wege
#' @description A function to get the WEGE index value for a provided polygon.
#' @param target_area  Either a sp or sf object to which to calculate the WEGE index.
#' @param input Species ranges, either from a shapefile or from a georeferenced species list with a column for species, two columns for coordinates and one for 
#' the IUCN category.
#' @param x name of the longitude column.
#' @param y name of the latitude column.
#' @param  species name of the species column.
#' @param  category name of IUCN the category column. Terminology must be as follows: DD for Data Deficient, LC for Least Concern, NT for Near Threatened, 
#' EN, for Endangered, CR for Critically Endangered, EW for Extinct in the wild 
#' and EX for Extinct.
#' @param  res grid-cell size to use to calculate the range of the species in 
#' 
#' case a georeferenced species list was provided.
#' @example examples/get_wege_function.R
#'
#'@importFrom sf st_as_sf
#'@importFrom sf st_geometry
#'@importFrom sf st_crs
#'@importFrom sf st_intersection
#'@importFrom raster extent
#'@importFrom sp CRS
#'@importFrom raster raster
#'@importFrom raster ncell
#'@importFrom graphics plot
#'@importFrom utils stack
#' @export
#' @return a value corresponding to the WEGE index value of the provided target_area
get_wege <- function(target_area,input,x,y,species='binomial',category = 
                       'category',res = 1) {

  
  if(is.null(input[[species]])){
    stop(paste0("No column found with the name - ",paste(species)))
  }
  if(is.null(input[[category]])){
    stop(paste0("No column found with the name - ",paste(category)))
  }

  if (any(class(input) %in% "sf")) {
    input_cl <- 'sf_ob'}else {input_cl <- 'df_ob'}

  if (any(class(target_area) %in% 'SpatialPolygonsDataFrame')) {
    target_area <- sf::st_as_sf(target_area)
  }
  if (any(class(input) %in% 'SpatialPolygonsDataFrame')) {
    input <- sf::st_as_sf(input)
    if (!sf::st_crs(target_area) == sf::st_crs(input)) {
      stop("Inputs have a different projection")
    }
  }
  if (any(class(input) %in% 'SpatialPolygonsDataFrame')) {
    input <- sf::st_as_sf(input)
    if (!sf::st_crs(target_area) == sf::st_crs(input)) {
      stop("Inputs have a different projection")
    }
  }
  if (any(class(input) %in% "data.frame")) {
    crs_ta <- sf::st_crs(target_area)
    input <-  sf::st_as_sf(x = input,coords = c(x,y),crs = crs_ta)
  }

  sps_grid <- sf::st_intersects(input,target_area)
  intersected_object_t <- t(sps_grid)
  sp_numbers <- unlist(intersected_object_t[1:nrow(target_area)])
  sp <- unique(input[[species]][sp_numbers])
  if (identical(sp, character(0))) {
    message("No species found in selected area")
  }else{

  if (input_cl == 'df_ob') {

    rgrid  <-  raster(raster::extent(input), resolution = res,crs = sp::CRS(crs_ta$proj4string))
    rgrid[] <- 1:raster::ncell(rgrid)
    rgrid <- sf::st_as_sf(raster::rasterToPolygons(rgrid))

    iucn_to_grid_range <- function(iucn_shp,grid_to_use) {
      r_grid_sf <- grid_to_use
      sf_to_intersect <- iucn_shp
      sf::st_crs(r_grid_sf) <- sf::st_crs(sf_to_intersect)
      sps_grid <- sf::st_intersects(sf_to_intersect,r_grid_sf)
      intersected_object <- sps_grid



      area <- unlist(lapply(intersected_object,length))

      sp_range_df <- cbind.data.frame(species = iucn_shp[[species]],area/(res*res*10000))

      return(sp_range_df)
    }
    input <- input[input[[species]] %in% sp,]
    input_combined <- stats::aggregate(input,
                                by = list(input$BINOMIAL),
                                FUN = mean)
    input_combined <- input_combined[,c('Group.1','geometry')]
    colnames(input_combined)[1] <- species

    tmp <- iucn_to_grid_range(iucn_shp = input_combined,grid_to_use = rgrid)


  }else {

    area_input <- function(input,sp) {
      temp <- sf::st_area(input[input[[species]] %in% sp,])
      attributes(temp) <- NULL
      temp <- sum(temp)
      return(temp <- temp/1000000)
    }
    all_area <- lapply(sp,area_input,input = input)
    tmp <- cbind.data.frame(species = sp,area = unlist(all_area))
  }

  tmp <- merge(tmp,input[,c(species,'category')],by.x = 'species',by.y = species)
  tmp <- tmp[,-4]
  er_df <- cbind.data.frame(status = c('DD','LC','NT','VU','EN','CR','EW','EX'),ER = c(0.0513,0.0009,0.0071,0.0513,0.4276,0.9688,1,1))

  tmp <- unique(tmp)
  tmp <- merge(tmp, er_df, by.x = category, by.y = 'status', sort = TRUE)

  return(unlist(lapply(1, function(x) sum(sqrt(1/tmp$area)*tmp$ER))))
  }
  }