ecospat.niche.zProjGeo {ecospat}R Documentation

Projection of Occurrence Densities to the Geography

Description

Creates a raster in geography with each pixel containing the occurrence densities extracted from a z object generated with ecospat.grid.clim.dyn.

Usage

ecospat.niche.zProjGeo(z1,env,cor)

Arguments

z1

Species 1 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).

cor

FALSE by default. If TRUE corrects the occurrence densities of each species by the prevalence of the environments in their range

Details

extracts the occurrence density of z objects created by ecospat.grid.clim.dyn 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

Value

raster of class RasterLayer

Author(s)

Olivier Broennimann olivier.broennimann@unil.ch

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.dynIndexProjGeo

Examples



library(ade4)
library(raster)

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

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

env.sp1<-extract(env,xy.sp1)
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

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

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

#################################### occurrence density in space ##################################

# sp1
geoz1<-ecospat.niche.zProjGeo(z1,env)
plot(geoz1,main="z1")
points(xy.sp1)

[Package ecospat version 3.4 Index]