Description Usage Arguments Value Author(s) References See Also Examples
coldspots
map areas or grid cells with lowest values for a biodiversity metric e.g.
species richness, species endemism or degree of threat.
1 |
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 |
... |
Further arguments passed to or from other methods. |
|
Integers of 1s and 0s with 1 corresponding to the coldspots |
Barnabas H. Daru darunabas@gmail.com
myers2000biodiversitybioregion
\insertReforme2005globalbioregion
\insertRefCeballos19374bioregion
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | 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)
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