ecospat (version 3.2)

ecospat.niche.dynIndexProjGeo: Projection of niche dynamic indices to the Geography

Description

Creates a raster in geography with each pixel containing a niche dynamic index (stability, expansion, or unfilling) extracted from 2 niches generated with ecospat.grid.clim.dyn.

Usage

ecospat.niche.dynIndexProjGeo(z1,z2,env,index)

Arguments

z1

Species 1 occurrence density grid created by ecospat.grid.clim.dyn.

z2

Species 2 occurrence density grid created by ecospat.grid.clim.dyn.

env

A RasterStack or RasterBrick of environmental variables corresponding to the background (glob in ecospat.grid.clim.dyn).

index

"stability", "unfilling" or "expansion"

Value

raster of class RasterLayer

Details

extracts the niche dynamic index of objects created by ecospat.niche.dyn.index for each point of the background (glob) using extract (package raster). The values are binded to the geographic coordinates of env and a raster is then recreated using rasterFromXYZ

References

Broennimann, O., M.C. Fitzpatrick, P.B. Pearman, B. Petitpierre, L. Pellissier, N.G. Yoccoz, W. Thuiller, M.J. Fortin, C. Randin, N.E. Zimmermann, C.H. Graham and A. Guisan. 2012. Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecology and Biogeography, 21:481-497.

Petitpierre, B., C. Kueffer, O. Broennimann, C. Randin, C. Daehler and A. Guisan. 2012. Climatic niche shifts are rare among terrestrial plant invaders. Science, 335:1344-1348.

See Also

ecospat.plot.niche.dyn,ecospat.niche.dyn.index, ecospat.niche.zProjGeo

Examples

# NOT RUN {
library(raster)

data(ecospat.testNiche)
spp <- ecospat.testNiche
xy.sp1<-subset(spp,species=="sp1")[2:3] #Bromus_erectus
xy.sp2<-subset(spp,species=="sp3")[2:3] #Daucus_carota

load(system.file("extdata", "ecospat.testEnvRaster.Rdata", package="ecospat"))

env.sp1<-extract(env,xy.sp1)
env.sp2<-extract(env,xy.sp2)
env.bkg<-na.exclude(values(env))

#################################### PCA-ENVIRONMENT ##################################

pca.cal <- dudi.pca(env.bkg, center = TRUE, scale = TRUE, scannf = FALSE, nf = 2)

# predict the scores on the axes
scores.bkg <- pca.cal$li  #scores for background climate
scores.sp1 <- suprow(pca.cal,env.sp1)$lisup				#scores for sp1
scores.sp2 <- suprow(pca.cal,env.sp2)$lisup				#scores for sp2

# calculation of occurence density (niche z)
  
z1 <- ecospat.grid.clim.dyn(scores.bkg, scores.bkg, scores.sp1,R=100)
z2 <- ecospat.grid.clim.dyn(scores.bkg, scores.bkg, scores.sp2,R=100)

plot(z1$z.uncor)
points(scores.sp1)

plot(z2$z.uncor)
points(scores.sp2)

ecospat.niche.overlap(z1,z2 ,cor = TRUE)

#################################### stability S in space ##################################

geozS<-ecospat.niche.dynIndexProjGeo(z1,z2,env,index="stability")

plot(geozS,main="Stability")
points(xy.sp1,col="red")
points(xy.sp2,col="blue")
# }