Freshwater fish zoogeography in west Africa

Description

This data set contains informations about faunal similarities between river basins in West africa.

Usage

data(westafrica)

Format

westafrica is a list containing the following objects :

tab

: a data frame with absence/presence of 268 species (rows) at 33 embouchures (columns)

spe.names

: a vector of string of characters with the name of species

spe.binames

: a data frame with the genus and species (columns) of the 256 species (rows)

riv.names

: a vector of string of characters with the name of rivers

atlantic

: a data frame with the coordinates of a polygon that represents the limits of atlantic (see example)

riv.xy

: a data frame with the coordinates of embouchures

lines

: a data frame with the coordinates of lines to complete the representation (see example)

cadre

: a data frame with the coordinates of points used to make the representation (see example)

Source

Data provided by B. Hugueny hugueny@mnhn.fr.

Paugy, D., Traor?, K. and Diouf, P.F. (1994) Faune ichtyologique des eaux douces d'Afrique de l'Ouest. In Diversit? biologique des poissons des eaux douces et saum?tres d'Afrique. Synth?ses g?ographiques, Teugels, G.G., Gu?gan, J.F. and Albaret, J.J. (Editors). Annales du Mus?e Royal de l'Afrique Centrale, Zoologie, 275, Tervuren, Belgique, 35–66.

Hugueny, B. (1989) Biog?ographie et structure des peuplements de Poissons d'eau douce de l'Afrique de l'ouest : approches quantitatives. Th?se de doctorat, Universit? Paris 7.

References

Hugueny, B., and L?v?que, C. (1994) Freshwater fish zoogeography in west Africa: faunal similarities between river basins. Environmental Biology of Fishes, 39, 365–380.

Examples

data(westafrica)

if(!adegraphicsLoaded()) {
  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$tab))
afri.dist <- dist.binary(afri.w,1)
afri.pco <- dudi.pco(afri.dist, scan = FALSE, nf = 3)
if(adegraphicsLoaded()) {
  G1 <- s1d.barchart(afri.pco$li[, 1:3], p1d.hori = F, plab.cex = 0)
} else {
  par(mfrow = c(3, 1))
  barplot(afri.pco$li[, 1])
  barplot(afri.pco$li[, 2])
  barplot(afri.pco$li[, 3])
}

if(requireNamespace("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)
  
  if(adegraphicsLoaded()) {
    G2 <- s1d.barchart(afri.ms$li[, 1:3], p1d.hori = F, plab.cex = 0)
    
    g31 <- s.label(afri.ms$li, plab.cex = 0.75, ppoi.cex = 0, nb = afri.nb, plot = F)
    g32 <- s.value(afri.ms$li, afri.ms$li[, 3], plot = F)
    g33 <- s.value(afri.ms$li, afri.ms$li[, 4], plot = F)
    g34 <- s.value(afri.ms$li, afri.ms$li[, 5], plot = F)
    G3 <- ADEgS(list(g31, g32, g33, g34), layout = c(2, 2))
    
  } else {
    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.D"), h = -0.2)