labdsv (version 2.0-1)

compspec: Compositional Specificity Analysis

Description

Calculates the mean similarity of all plots in which each species occurs

Usage

compspec(comm, dis, numitr=100, drop=FALSE, progress=FALSE)
# S3 method for compspec
plot(x,spc=NULL,pch=1,type='p',col=1,...)

Value

a list with several data.frames: ‘vals’ with species name, mean similarity, number of occurrences, and probability of observing as high a mean similarity as observed, and ‘quantiles’ with the distribution of the quantiles of mean similarity for given numbers of occurrences. If drop=TRUE, results specific to dropping out each species in turn are added to the list by species name.

Arguments

comm

a data frame of community samples, samples as rows, species as columns

dis

an object of class ‘dist’ from dist, dsvdis or vegdist

numitr

the number of iterations to use to establish the quantiles of the distribution

drop

a switch to determine whether to drop species out when calculating their compspec value

progress

a switch to control printing out a progress bar

x

an object of class compspec

spc

an integer code to specify exactly which species drop-out to plot

pch

which glyph to plot for species

type

which type of plot

col

an integer or integer vector) to color the points

...

additional arguments to the plot function

Author

David W. Roberts http://ecology.msu.montana.edu/droberts/droberts.html

References

http://ecology.msu.montana.edu/labdsv/R

See Also

indval,isamic

Examples

data(bryceveg) # returns a vegetation data.frame
dis.bc <- dsvdis(bryceveg,'bray/curtis')
    # returns a Bray/Curtis dissimilarity matrix
compspec(bryceveg,dis.bc)