individual.based.communities.a {CNull}R Documentation

Produces a set of random communities from a given matrix, based on the individual-based null model (Stegen et al. 2013). These communities can be used for alpha diversity computations

Description

Given a matrix M and a number of repetitions k, the function produces k random communities based on the individual-based model. This is equivalent to shuffling M according to this model as many as k times , each time outputing only a certain row (e.g. the top one) of the shuffled matrix. An alpha diversity measure f can be applied on the output communities to determine the null distribution of f for a row in M. This distribution is the same for every row of M. This is because the examined null model produces the same distribution for all rows of M; after shuffling M, each row has the same probability to store a specific community as any other in the resulting matrix.

Usage

individual.based.communities.a(matrix, reps=1000)

Arguments

matrix

A matrix with integer values. The matrix should not contain any NA values.

reps

The number of randomizations. This argument is optional and its default value is set to one thousand.

Value

A matrix which stores communities generated based on the individual-based model. Each row of the matrix corresponds to a different randomized community. The number of columns, and the names of the columns in the output matrix are the same as in the input matrix. The output matrix is not a shuffled version of the input matrix.

Author(s)

Constantinos Tsirogiannis (tsirogiannis.c@gmail.com)

References

Stegen, J. C., Freestone, A. L., Crist, T. O., Anderson, M. J., Chase, J. M., Comita, L. S., Cornell, H. V., Davies, K. F., Harrison, S. P., Hurlbert, A. H., Inouye, B. D., Kraft, N. J. B., Myers, J. A., Sanders, N. J., Swenson, N. G., Vellend, M. (2013), Stochastic and Deterministic Drivers of Spatial and Temporal Turnover in Breeding Bird Communities. Global Ecology and Biogeography, 22:202-212.

Tsirogiannis, C., A. Kalvisa, B. Sandel and T. Conradi. Column-Shuffling Null Models Are Simpler Than You Thought. To appear.

See Also

individual.based.random.values.a

Examples

require(CNull)

#Create a random integer matrix
comm = matrix(sample(1:300),nrow=15,ncol=20)

#Use individual-based model to produce 2000 random communities 
individual.based.communities.a(comm,reps=2000)

[Package CNull version 1.0 Index]