| westafrica {ade4} | R Documentation |
This data set contains informations about faunal similarities between river basins in West africa.
data(westafrica)
westafrica is a list containing the following objects :
Data provided by B. Hugueny hugueny@biomserv.univ-lyon1.fr.
Paugy, D., Traoré, K. and Diouf, P.F. (1994) Faune ichtyologique des eaux douces d'Afrique de l'Ouest. In Diversité biologique des poissons des eaux douces et saumâtres d'Afrique. Synthèses géographiques, Teugels, G.G., Guégan, J.F. and Albaret, J.J. (Editors). Annales du Musée Royal de l'Afrique Centrale, Zoologie, 275, Tervuren, Belgique, 35–66.
Hugueny, B. (1989) Biogéographie et structure des peuplements de Poissons d'eau douce de l'Afrique de l'ouest : approches quantitatives. Thèse de doctorat, Université Paris 7.
Hugueny, B., and Lévêque, C. (1994) Freshwater fish zoogeography in west Africa: faunal similarities between river basins. Environmental Biology of Fishes, 39, 365–380.
data(westafrica)
s.label(westafrica$cadre, xlim = c(30,500), ylim = c(50,290),
cpoi = 0, clab = 0, grid = FALSE, addax = 0)
old.par <- par(no.readonly = TRUE)
par(mar = c(0.1, 0.1, 0.1, 0.1))
rect(30,0,500,290)
polygon(westafrica$atlantic,col = "lightblue")
points(westafrica$riv.xy, pch = 20, cex = 1.5)
apply(westafrica$lines, 1, function(x) segments(x[1], x[2], x[3],
x[4], lwd = 1))
apply(westafrica$riv.xy,1, function(x) segments(x[1], x[2], x[3],
x[4], lwd = 1))
text(c(175,260,460,420), c(275,200,250,100), c("Senegal","Niger",
"Niger","Volta"))
par(srt = 270)
text(westafrica$riv.xy$x2, westafrica$riv.xy$y2-10,
westafrica$riv.names, adj = 0, cex = 0.75)
par(old.par)
rm(old.par)
# multivariate analysis
afri.w <- data.frame(t(westafrica$tab))
afri.dist <- dist.binary(afri.w,1)
afri.pco <- dudi.pco(afri.dist, scan = FALSE, nf = 3)
par(mfrow = c(3,1))
barplot(afri.pco$li[,1])
barplot(afri.pco$li[,2])
barplot(afri.pco$li[,3])
if (require(spdep, quiet = TRUE)){
#multivariate spatial analysis
afri.neig <- neig(n.line = 33)
afri.nb <- neig2nb(afri.neig)
afri.listw <- nb2listw(afri.nb)
afri.ms <- multispati(afri.pco, afri.listw, scan = FALSE,
nfposi = 6, nfnega = 0)
par(mfrow = c(3,1))
barplot(afri.ms$li[,1])
barplot(afri.ms$li[,2])
barplot(afri.ms$li[,3])
par(mfrow = c(2,2))
s.label(afri.ms$li, clab = 0.75, cpoi = 0, neig = afri.neig,
cneig = 1.5)
s.value(afri.ms$li, afri.ms$li[,3])
s.value(afri.ms$li, afri.ms$li[,4])
s.value(afri.ms$li, afri.ms$li[,5])
summary(afri.ms)
}
par(mfrow = c(1,1))
plot(hclust(afri.dist,"ward"),h=-0.2)
> library(ade4) > ### Name: westafrica > ### Title: Freshwater fish zoogeography in west Africa > ### Aliases: westafrica > ### Keywords: datasets > > ### ** Examples > > data(westafrica) > > s.label(westafrica$cadre, xlim = c(30,500), ylim = c(50,290), + cpoi = 0, clab = 0, grid = FALSE, addax = 0)

> old.par <- par(no.readonly = TRUE) > par(mar = c(0.1, 0.1, 0.1, 0.1)) > rect(30,0,500,290)

> polygon(westafrica$atlantic,col = "lightblue")

> points(westafrica$riv.xy, pch = 20, cex = 1.5)

> apply(westafrica$lines, 1, function(x) segments(x[1], x[2], x[3], + x[4], lwd = 1)) NULL

> apply(westafrica$riv.xy,1, function(x) segments(x[1], x[2], x[3], + x[4], lwd = 1)) NULL

> text(c(175,260,460,420), c(275,200,250,100), c("Senegal","Niger",
+ "Niger","Volta"))

> par(srt = 270) > text(westafrica$riv.xy$x2, westafrica$riv.xy$y2-10, + westafrica$riv.names, adj = 0, cex = 0.75)

> par(old.par) > rm(old.par) > > # multivariate analysis > afri.w <- data.frame(t(westafrica$tab)) > afri.dist <- dist.binary(afri.w,1) > afri.pco <- dudi.pco(afri.dist, scan = FALSE, nf = 3) > par(mfrow = c(3,1)) > barplot(afri.pco$li[,1])

> barplot(afri.pco$li[,2])

> barplot(afri.pco$li[,3])

>
> if (require(spdep, quiet = TRUE)){
+ #multivariate spatial analysis
+ afri.neig <- neig(n.line = 33)
+ afri.nb <- neig2nb(afri.neig)
+ afri.listw <- nb2listw(afri.nb)
+ afri.ms <- multispati(afri.pco, afri.listw, scan = FALSE,
+ nfposi = 6, nfnega = 0)
+ par(mfrow = c(3,1))
+ barplot(afri.ms$li[,1])
+ barplot(afri.ms$li[,2])
+ barplot(afri.ms$li[,3])

+
+ par(mfrow = c(2,2))
+ s.label(afri.ms$li, clab = 0.75, cpoi = 0, neig = afri.neig,
+ cneig = 1.5)
+ s.value(afri.ms$li, afri.ms$li[,3])
+ s.value(afri.ms$li, afri.ms$li[,4])
+ s.value(afri.ms$li, afri.ms$li[,5])
+ summary(afri.ms)
+ }
deldir 0.0-12
Please note: The process for determining duplicated points
has changed from that used in version 0.0-9 (and previously).
Multivariate Spatial Analysis
Call: multispati(dudi = afri.pco, listw = afri.listw, scannf = FALSE,
nfposi = 6, nfnega = 0)
Scores from the initial duality diagramm:
var cum ratio moran
RS1 0.05660710 0.05660710 0.1635437 0.9598444
RS2 0.03641095 0.09301805 0.2687386 0.7372155
RS3 0.02776793 0.12078598 0.3489629 0.6735561
Multispati eigenvalues decomposition:
eig var moran
CS1 0.05455534 0.05641792 0.9669861
CS2 0.03084339 0.03406832 0.9053395
CS3 0.02052642 0.02544985 0.8065439
CS4 0.01671907 0.01891409 0.8839480
CS5 0.01342381 0.01539323 0.8720593
CS6 0.01043363 0.01371212 0.7609053

> > par(mfrow = c(1,1)) > plot(hclust(afri.dist,"ward"),h=-0.2)

> > > >