coldspots: Computes biodiversity coldspots

In darunabas/bioregion: an R package for mapping biodiversity and conservation

Description

coldspots map areas or grid cells with lowest values for a biodiversity metric e.g. species richness, species endemism or degree of threat.

Usage

coldspots(x, values, prob = 2.5, ...)

Arguments

x	A data frame
values	Variable in the dataframe on which to compute coldspots analysis
prob	The threshold quantile for representing the lowest proportion of biodiversity in an area. By default, the threshold is set to prob = 2.5 percent.
...	Further arguments passed to or from other methods.

Value

Integers of 1s and 0s with 1 corresponding to the coldspots

Author(s)

Barnabas H. Daru [e-mail]

References

\insertRef

myers2000biodiversitybioregion

\insertRef

orme2005globalbioregion

\insertRef

Ceballos19374bioregion

See Also

hotspots

Examples

x <- c("raster", "colorRamps", "data.table")
lapply(x, require, character.only = TRUE)
 
s <- readRDS(system.file("nigeria/NG_comm.rds", package= "bioregion"))
Endm <- weighted.endemism(s)
C <- coldspots(Endm, values = Endm$V1, prob = 5)

## To plot coldspots on the map, first create a polygon shapefile
gr <- readRDS(system.file("nigeria/NG_grids.rds", package= "bioregion"))
m <- merge(gr, C, by="grids")
m <- m[!is.na(m@data$values),]

pol <- readRDS(system.file("nigeria/nigeria.rds", package= "bioregion"))

par(mfrow = c(2,1))
plot(pol, border="grey", col="lightgrey"); 
plot(m[(m@data$values==1),], col="blue", add=TRUE, border=NA); 
title("Top 2.5% Coldpsot of Weighted Endemism", line = 1, cex=1, adj=0.05)

k=10
COLOUR <- blue2green2red(k)
y = choropleth(m, values = m$V1, k)
 
## Not run: 
plot(y, col=COLOUR[y$values], border = NA); 
title("Overall Weighted Endemism", line = 1, cex=1, adj=0.05)

darunabas/bioregion documentation built on Oct. 27, 2019, 6:57 a.m.