atlas: Small Ecological Dataset

In ade4: Analysis of Ecological Data : Exploratory and Euclidean Methods in Environmental Sciences

Description

atlas is a list containing three kinds of information about 23 regions (The French Alps) :
geographical coordinates, meteorology and bird presences.

Usage

data(atlas)

Format

This list contains the following objects:

area

is a convex hull of 23 geographical regions.

xy

are the coordinates of the region centers and altitude (in meters).

names.district

is a vector of region names.

meteo

is a data frame with 7 variables: min and max temperature in january; min and max temperature in july; january, july and total rainfalls.

birds

is a data frame with 15 variables (species).

alti

is a data frame with 3 variables altitude in percentage [0,800], ]800,1500] and ]1500,5000].

Source

Extract from:
Lebreton, Ph. (1977) Les oiseaux nicheurs rhonalpins. Atlas ornithologique Rhone-Alpes. Centre Ornithologique Rhone-Alpes, Universite Lyon 1, 69621 Villeurbanne. Direction de la Protection de la Nature, Ministere de la Qualite de la Vie. 1–354.

Examples

data(atlas)
if(adegraphicsLoaded()) {
  if(requireNamespace("sp", quiet = TRUE)) {
    g11 <- s.Spatial(atlas$Spatial, pSp.col = "white", plot = FALSE)
    g12 <- s.label(atlas$area[, 2:3], plabels.cex = 0, plot = FALSE)
    g1 <- superpose(g11, g12, plot = FALSE)
    g2 <- s.label(atlas$xy, lab = atlas$names.district, Sp = atlas$Spatial, 
      pgrid.dra = FALSE, pSp.col = "white", plot = FALSE)
    obj3 <- sp::SpatialPolygonsDataFrame(Sr = atlas$Spatial, data = atlas$meteo)
    g3 <- s.Spatial(obj3[, 1], nclass = 12, psub = list(position = "topleft", 
      text = "Temp Mini January", cex = 2), plot = FALSE)
    g4 <- s.corcircle((dudi.pca(atlas$meteo, scann = FALSE)$co), plabels.cex = 1, plot = FALSE)
    G1 <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
  
    obj5 <- sp::SpatialPolygonsDataFrame(Sr = atlas$Spatial, 
      data = dudi.pca(atlas$meteo, scann = FALSE)$li)
    g5 <- s.Spatial(obj5[, 1], nclass = 12, psub = list(position = "topleft", 
      text = "Principal Component Analysis analysis", cex = 1.5), plot = FALSE)
    coa1 <- dudi.coa(atlas$birds, scann = FALSE, nf = 1)
    obj6 <- sp::SpatialPolygonsDataFrame(Sr = atlas$Spatial, data = coa1$li)
    g6 <- s.Spatial(obj6[, 1], nclass = 12, psub = list(position = "topleft", 
      text = "Correspondence analysis", cex = 1.5), plot = FALSE)
    g7 <- s.value(atlas$xy, coa1$li$Axis1, Sp = atlas$Spatial.contour, ppoints.cex = 2, 
      porigin.include = FALSE, paxes.draw = FALSE, pSp.col = "white", plot = FALSE)
    g8 <- triangle.label(atlas$alti, plabels.cex = 0, plot = FALSE)
    G2 <- ADEgS(list(g5, g6, g7, g8), layout = c(2, 2))
  
  }
} else {
  op <- par(no.readonly = TRUE) 
  par(mfrow = c(2,2))
  area.plot(atlas$area, cpoin = 1.5)
  area.plot(atlas$area, lab = atlas$names.district, clab = 1)
  x <- atlas$meteo$mini.jan
  
  names(x) <- row.names(atlas$meteo)
  area.plot(atlas$area, val = x, ncl = 12, sub = "Temp Mini January", 
      csub = 2, cleg = 1)
  s.corcircle((dudi.pca(atlas$meteo, scann = FALSE)$co), 
      clab = 1)
  
  area.plot(atlas$area, val = dudi.pca(atlas$meteo,scann=FALSE)$li[,1], 
      ncl = 12, sub = "Principal Component Analysis analysis", csub = 1.5, 
      cleg = 1)
  birds.coa <- dudi.coa(atlas$birds, sca = FALSE, nf = 1)
  x <- birds.coa$li$Axis1
  area.plot(atlas$area, val = x, ncl = 12, 
      sub = "Correspondence analysis", csub = 1.5, cleg = 1)
  
  s.value(atlas$xy, x, contour = atlas$contour, csi = 2, 
      incl = FALSE, addax = FALSE)
  triangle.plot(atlas$alti)
  par(op)
  par(mfrow=c(1,1))}

Example output

ade4 documentation built on May 2, 2019, 5:50 p.m.