R: Method to Analyse a pair of tables : Environmental and...

niche {ade4} | R Documentation

## Method to Analyse a pair of tables : Environmental and Faunistic Data

### Description

performs a special multivariate analysis for ecological data.

### Usage

    niche(dudiX, Y, scannf = TRUE, nf = 2)
    ## S3 method for class 'niche'
    print(x, ...)
    ## S3 method for class 'niche'
    plot(x, xax = 1, yax = 2, ...)
    niche.param(x)
    ## S3 method for class 'niche'
    rtest(xtest,nrepet=99, ...)

### Arguments

`dudiX` | a duality diagram providing from a function `dudi.coa`, `dudi.pca`, ... using an array sites-variables
`Y` | a data frame sites-species according to `dudiX$tab` with no columns of zero
`scannf` | a logical value indicating whether the eigenvalues bar plot should be displayed
`nf` | if scannf FALSE, an integer indicating the number of kept axes
`x` | an object of class `niche`
`...` | further arguments passed to or from other methods
`xax, yax` | the numbers of the x-axis and the y-axis
`xtest` | an object of class `niche`
`nrepet` | the number of permutations for the testing procedure

### Value

Returns a list of the class `niche` (sub-class of `dudi`) containing :

`rank` | an integer indicating the rank of the studied matrix
`nf` | an integer indicating the number of kept axes
`RV` | a numeric value indicating the RV coefficient
`eig` | a numeric vector with the all eigenvalues
`lw` | a data frame with the row weigths (crossed array)
`tab` | a data frame with the crossed array (averaging species/sites)
`li` | a data frame with the species coordinates
`l1` | a data frame with the species normed scores
`co` | a data frame with the variable coordinates
`c1` | a data frame with the variable normed scores
`ls` | a data frame with the site coordinates
`as` | a data frame with the axis upon niche axis

### Author(s)

Daniel Chessel
Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr
Stéphane Dray stephane.dray@univ-lyon1.fr

### References

Dolédec, S., Chessel, D. and Gimaret, C. (2000) Niche separation in community analysis: a new method. Ecology, 81, 2914–1927.

### Examples

    data(doubs)
    dudi1 <- dudi.pca(doubs$env, scale = TRUE, scan = FALSE, nf = 3)
    nic1 <- niche(dudi1, doubs$fish, scann = FALSE)

    if(adegraphicsLoaded()) {
      g1 <- s.traject(dudi1$li, plab.cex = 0, plot = FALSE)
      g2 <- s.traject(nic1$ls, plab.cex = 0, plot = FALSE)
      g3 <- s.corcircle(nic1$as, plot = FALSE)
      g4 <- s.arrow(nic1$c1, plot = FALSE)
      G1 <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))

      glist <- list()
      for(i in 1:ncol(doubs$fish))
        glist[[i]] <- s.distri(nic1$ls, dfdistri = doubs$fish[, i], psub.text = names(doubs$fish)[i],
          plot = FALSE, storeData = TRUE)
      G2 <- ADEgS(glist, layout = c(5, 6))

      G3 <- s.arrow(nic1$li, plab.cex = 0.7)

    } else {
      par(mfrow = c(2, 2))
      s.traject(dudi1$li, clab = 0)
      s.traject(nic1$ls, clab = 0)
      s.corcircle(nic1$as)
      s.arrow(nic1$c1)

      par(mfrow = c(5, 6))
      for (i in 1:27) s.distri(nic1$ls, as.data.frame(doubs$fish[,i]),
        csub = 2, sub = names(doubs$fish)[i])

      par(mfrow = c(1, 1))
      s.arrow(nic1$li, clab = 0.7)

    }

    data(trichometeo)
    pca1 <- dudi.pca(trichometeo$meteo, scan = FALSE)
    nic1 <- niche(pca1, log(trichometeo$fau + 1), scan = FALSE)
    plot(nic1)
    niche.param(nic1)
    rtest(nic1,19)

    data(rpjdl)
    plot(niche(dudi.pca(rpjdl$mil, scan = FALSE), rpjdl$fau, scan = FALSE))

[Package ade4 version 1.7-15 Index]