spat_ras {WEGE}

spat_ras

Description

A function to get the WEGE index value for a provided polygon.

Usage

spat_ras(
  target_area,
  input,
  x,
  y,
  species = "binomial",
  category = "category",
  show_progress = FALSE,
  ed,
  res = 1
)

Arguments

target_area

Either a sp or sf object to which to calculate the WEGE index.

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.

x

name of the longitude column.

y

name of the latitude column.

species

name of the species column.

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.

show_progress

Progress of the analysis by showing the number of the grid where the function is calculating the different indices.

ed

name of the evolutionary distinctiveness column.

res

grid-cell size to use to calculate the range of the species in case a georeferenced species list was provided.

Value

A RasterStack with rasters for each KBA criteria (A1a,A1b,A1e,B1) and indices calculated (GE,ED,EDGE,WEGE)

Examples

library(WEGE)
library(sp)
library(sf)
library(raster)

 species <- sample(letters, 10)
 range_list <- list()
 for (i in seq_along(species)) {
   temp0 <- cbind(runif(3,1,50),runif(3,1,50))
   temp <- Polygon(rbind(temp0,temp0[1,]))
   range_list[[i]] <- Polygons(list(temp), ID = c(species[i]))
   }
 input <- st_as_sf(SpatialPolygons(range_list))
 categories <- c('LC','NT','VU','EN','CR')
 input$binomial <- species
 input$category <- sample(size = nrow(input),x = categories,replace = TRUE)
 
 input$ed <- runif(runif(10,1,50))
 temp0 <- cbind(runif(3,1,50),runif(3,1,50))
 target_area <- Polygon(rbind(temp0,temp0[1,]))
 target_area <- Polygons(list(target_area), ID = 'Target area')
 target_area <- st_as_sf(SpatialPolygons(list(target_area)))
 spat_ras(target_area,input,species = 'binomial',ed='ed', res = 1)