Learn R Programming

bipartite (version 2.18)

r2dexternal: Generates null models for network analysis by considering external abundances

Description

An extension of r2dtable (and vaznull, respectively) which rescales marginal totals according to independent data

Usage

r2dexternal(N, web, abun.higher=NULL, abun.lower=NULL)

vaznullexternal(N, web, abun.higher=NULL, abun.lower=NULL)

Value

Returns a list of N null model-generated networks. Species names are (obviously) dropped.

Arguments

N

number of null models to be generated.

web

Web is a matrix representing the interactions observed between higher level species (columns) and lower level species (rows).

abun.higher

Optional vector of externally measured abundances of the higher level. If missing (NULL) it will be replaced by column totals.

abun.lower

Optional vector of externally measured abundances of the lower level. If missing (NULL) it will be replaced by row totals.

Author

Carsten F. Dormann carsten.dormann@biom.uni-freiburg.de

Details

The underlying functions are r2dtable and vaznull, which require a vector of row and column totals or a web, respectively. In function nullmodel, these marginal totals are computed from the observed interaction matrix. Here, external abundances can be provided. These will be rescaled and combined with the observed marginal total to construct new row and column vectors for r2dtable.

If neither row nor column abundances are provided this function will be identical to r2dtable and vaznull, respectively.

See Also

nullmodel, vaznull, mgen, vegan::simulate and r2dtable

Examples

Run this code
if (FALSE) {
	abun.lower <- c(15,5,2,7,4,8,6,0.01,6)
	 set.seed(2)
	(abun.higher <- rpois(27, lambda=4))
	abun.higher[1] <- 0.001
	sum(ext.polls)
	## note: external abundances do not sum up; this is intentional!!
	r2dexternal(2, Safariland, abun.higher=abun.higher, abun.lower=abun.lower)
	r2dexternal(2, Safariland, abun.higher=abun.higher)

  vaznullexternal(2, Safariland, abun.higher=abun.higher, abun.lower=abun.lower)
	}

Run the code above in your browser using DataLab