R: Distribution of Alpine plants in Aravo (Valloire, France)

aravo {ade4} | R Documentation

## Distribution of Alpine plants in Aravo (Valloire, France)

### Description

This dataset describe the distribution of 82 species of Alpine plants in 75 sites. Species traits and environmental variables are also measured.

### Usage

    data(aravo)

### Format

`aravo` is a list containing the following objects :

spe

  is a data.frame with the abundance values of 82 species (columns) in 75 sites (rows).

env

  is a data.frame with the measurements of 6 environmental variables for the sites.

traits

  is data.frame with the measurements of 8 traits for the species.

spe.names

  is a vector with full species names.

### Details

The environmental variables are:

Aspect | Relative south aspect (opposite of the sine of aspect with flat coded 0)
Slope | Slope inclination (degrees)
Form | Microtopographic landform index: 1 (convexity); 2 (convex slope); 3 (right slope); 4 (concave slope); 5 (concavity)
Snow | Mean snowmelt date (Julian day) averaged over 1997-1999
PhysD | Physical disturbance, i.e., percentage of unvegetated soil due to physical processes
ZoogD | Zoogenic disturbance, i.e., quantity of unvegetated soil due to marmot activity: no; some; high

The species traits for the plants are:

Height | Vegetative height (cm)
Spread | Maximum lateral spread of clonal plants (cm)
Angle | Leaf elevation angle estimated at the middle of the lamina
Area | Area of a single leaf
Thick | Maximum thickness of a leaf cross section (avoiding the midrib)
SLA | Specific leaf area
Nmass | Mass-based leaf nitrogen content
Seed | Seed mass

### Source

Choler, P. (2005) Consistent shifts in Alpine plant traits along a mesotopographical gradient. Arctic, Antarctic, and Alpine Research, 37,444–453.

### Examples

    data(aravo)
    coa1 <- dudi.coa(aravo$spe, scannf = FALSE, nf = 2)
    dudienv <- dudi.hillsmith(aravo$env, scannf = FALSE, nf = 2, row.w = coa1$lw)
    duditrait <- dudi.pca(aravo$traits, scannf = FALSE, nf = 2, row.w = coa1$cw)
    rlq1 <- rlq(dudienv, coa1, duditrait, scannf = FALSE, nf = 2)
    plot(rlq1)

[Package ade4 version 1.7-18 Index]