Package 'WEGE'

get_edge

Description

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

Usage

get_edge(
  target_area,
  input,
  x,
  y,
  species = "binomial",
  ed = "ED",
  category = "category",
  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.
ed	name of the evolutionary distinctiveness 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.
res	grid-cell size to use to calculate the range of the species in case a georeferenced species list was provided.

Value

a value corresponding to the EDGE score of the provided target_area

Examples

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

species <- letters[1:26]
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(nrow(input),1,30)
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)))

get_edge(target_area = target_area,input = input,species = 'binomial',category = 'category')

---

Function to get the KBA criteria

Description

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

Usage

get_kba_criteria(
  target_area,
  input,
  x,
  y,
  species = "binomial",
  category = "category",
  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.
res	grid-cell size to use to calculate the range of the species in case a georeferenced species list was provided.

Value

a data.frame containing all the species that trigger KBA status as well as the criteria they trigger.

Examples

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

species <- letters[1:26]
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)

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)))
get_kba_criteria(target_area,input)

---

get_wege

Description

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

Usage

get_wege(
  target_area,
  input,
  x,
  y,
  species = "binomial",
  category = "category",
  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.
res	grid-cell size to use to calculate the range of the species in case a georeferenced species list was provided.

Value

a value corresponding to the WEGE index value of the provided target_area

Examples

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

species <- letters[1:26]
range_list <- list()
for (i in seq_along(species)){
  temp  <-  Polygon(cbind(runif(4,1,50),runif(4,1,50)))
  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)

target_area <- Polygon(cbind(runif(4,1,50),runif(4,1,50)))
target_area <- Polygons(list(target_area), ID = 'Target area')
target_area <- st_as_sf(SpatialPolygons(list(target_area)))
get_wege(target_area,input,species = 'binomial',category = 'category')

---

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)

---

WEGE: A new metric for ranking locations for biodiversity conservation

Description

WEGE is an R package that allows the user to calculate the WEGE index for a particular area. Additionally it also calculates rasters of KBA criteria (A1a, A1b, A1e, and B1) Weighted endemism, the EDGE score, Evolutionary Distinctiveness and Extinction risk.

---