hotspots: Computes biodiversity hotspots

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

Description

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

Usage

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

Arguments

x	A data frame
values	Variable in the dataframe on which to compute hotspots analysis
prob	The threshold quantile for representing the highest 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

values

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

Author(s)

Barnabas H. Daru [e-mail]

References

\insertRef

myers2000biodiversitybioregion

\insertRef

orme2005globalbioregion

\insertRef

Ceballos19374bioregion

See Also

coldspots

Examples

require(raster); require(colorRamps); require(data.table)

s <- readRDS(system.file("nigeria/NG_comm.rds", package= "bioregion"))
Endm <- weighted.endemism(s)
H <- hotspots(Endm, values = Endm$V1)

## To plot hotspots on the map, first create a polygon shapefile
gr <- readRDS(system.file("nigeria/NG_grids.rds", package= "bioregion"))
m <- merge(gr, H, 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="red", add=TRUE, border=NA)
title("Hotspots of Weighted Endemism", line = 1, cex=1, adj=0.05)

k=10
COLOUR <- blue2green2red(k)
y = choropleth(m, values = m$V1)
 
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.