ecospat (version 3.5.1)

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)

Value

Raster of class RasterLayer, with cell values 0-3. 1: unfilling (habitat occupied by species 1); 2: expansion (habitat occupied only by species 2); 3: stability (habitat occupied by both species); and 0 (unoccupied habitat).

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).

Author

Olivier Broennimann , Tyler Smith

Details

Extracts the niche dynamic index of objects created by ecospat.niche.dyn.index for each background point (glob) using extract from the raster package. The values are projected to the geographic coordinates of env and returned as a raster layer.

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

# \donttest{

library(ade4)
library(raster)

data(ecospat.testNiche)
spp <- ecospat.testNiche
xy.sp1 <- subset(spp, species=="sp1")[2:3] #Bromus_erectus
xy.sp2 <- subset(spp, species=="sp4")[2:3] #Pritzelago_alpina

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, pch = 21, bg = "green")

plot(z2$z.uncor)
points(scores.sp2, pch = 21, bg = "red")

ecospat.plot.niche.dyn(z1, z2)
points(scores.sp1, pch = 21, bg = "green")
points(scores.sp2, pch = 21, bg = "red")
ecospat.niche.overlap(z1,z2 ,cor = TRUE)

##############################
## dynamic indices in space ##
##############################

geozS <- ecospat.niche.dynIndexProjGeo(z1, z2, env)

plot(geozS, col = c("grey", "green", "red", "blue"),
     legend = FALSE)
points(xy.sp1, bg = "green", pch = 21)
points(xy.sp2, bg = "red", pch = 21)
# }