R: Maximum Likelihood Models for Species Abundance Distributions

sads-package {sads} | R Documentation

## Maximum Likelihood Models for Species Abundance Distributions

### Description

Maximum likelihood tools to fit and compare models of species abundance distributions and of species rank-abundance distributions.

### Details

The distribution of abundances of species is one of the basic patterns of ecological communities. The empirical distributions of abundances (SADs) or their ranks (RADs) are traditionally modelled through probability distributions. Hence, the maximum likelihood method can be used to fit and compare competing models for SADs and RADs. The sads package provides functions, classes and methods to:

- Fit classic SAD models: log-series, lognormal, broken-stick, ... ;

- Fit classic rank-abundance (RADs) models: geometric, broken-stick, Zipf, Zipf-Mandelbrodt, ... ;

- Tools for quick diagnostic and comparison of models;

- Tools to simulate Poisson and Negative Binomial samples from abundances in communities.

### Author(s)

Paulo I. Prado, Murilo Dantas Miranda and Andre Chalom

Maintainer: Paulo I. Prado <prado@ib.usp.br>

### References

Magurran, A.E. 2004. Measuring Biological Diversity. Blackwell.

Magurran, A.E. and McGill, B.J. 2011. Biological Diversity – Frontiers in measurement and assessment. Oxford University Press.

May, R.M. 1975. Patterns of Species Abundance and Diversity. In M. L. Cody and J. M. Diamond (Eds.), (pp. 81–120). Harvard University Press.

Green,J. and Plotkin, J.B. 2007 A statistical theory for sampling species abundances. Ecology Letters 10:1037–1045.

Saether, B.E., Engen, S. and Grotan, V. 2013. Species diversity and community similarity in fluctuating environments: parametric approaches using species abundance distributions. Journal of Animal Ecology, 82(4): 721–738.

### See Also

vignettes of sads; `vegan-package` and `poilog-package`

### Examples

    ## Rank-abundance plot
    plot( rad(moths) )
    ## Preston's plots
    plot (octav(moths) )
    ## Fit logseries model
    moths.ls <-  fitsad(moths, sad = 'ls')
    ## Diagnostic plots
    par(mfrow=c(2,2))
    plot(moths.ls)
    par(mfrow = c(1,1))
    ## Model summary
    summary(moths.ls)
    ## Confidence interval
    confint(moths.ls)

[Package sads version 0.4.2 Index]