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R Stuff

Some R-codes, class notes and tutorials produced by our team and collaborators. Hopefully part of them will become R-packages and printed publications in a near future.

Meanwhile we are glad to share them as they are, of course without any warranty that they are all running properly.

Your feedback is very welcome.

R programing and modelling

Species Abundance Distributions

These codes are part of an ongoing research project on developing a protocol to fit by maximum likelihood and to compare by model selection different SAD models.

Fisher Logseries

The original numerical recipe proposed by Fisher et al. (1943) to fit the Fisher logseries to abundance data is a maximum likelihood method (Alonso et al 2008). Above functions to fit the logseries which return the likelihood and AIC. Also funtions for ploting the predicted abundances in a rank-abundance plot, and for the PDF (original discrete form and the continuous approximation by Green & Plotkin 2007) and CDF of the logseries.

Lognormal

Codes to CDFs and PDFs of the truncated lognormal and their resulting random sampling model, the Poisson-Lognormal (Bulmer 1974), which takes advantage of the poilog R package (Grøtan & Engen, 2008).

Niche-Partitioning models

Currently just simple functions for the expected abundances for the i-th species in a rank-abundance plot for the Geometric (Motomura 1932) and Broken-Stick (MacArthur 1960) models.

Rank-abundance Plots

outuput of the ''radplot'' function  These functions plot rank-abundance plots and allow to compare visually the fit of the four classical models.

Supporting Documentation

Additive Diversity Partitioning

The R package vegan has functions for individual-based permutation tests of additive diversity partitioning (sensu Crist et al. 2003).

Here we provide a code for the sample-based tests (Crist et al. 2003), where sample units of a given level are shuffled within units of the level above.

This code is an improved version of those used by Ribeiro et al. (2008). Apart code fine-tuning, the main change is that the average diversity indexes are not weighted (see Crist et al. 2003).

References

[2008, article | www]
Alonso, D., Ostling, A., & Etienne, R. S. (2008). The implicit assumption of symmetry and the species abundance distribution. Ecology Letters, 11, 93-105.
[1974, article]
Bulmer, M. G. (1974). On fitting the Poisson lognormal distribution to species abundance data. Biometrics, 30, 651-660.
[2003, article]
Crist, T. O., Veech, J. A., Gering, J. C., & Summerville, K. S. (2003). Partitioning species diversity across landscapes and regions: a hierarchical analysis of $$\alpha$$, $$\beta$$, and $$\gamma$$ diversity. The American Naturalist, 162, 734-743.
[1943, article]
Fisher, R. A., Corbet, A. S., & Williams, C. B. (1943). The relation between the number of the species and the number of individuals in a random sample from animal population. Journal of Animal Ecology, 12, 42-58.
[2007, article | www]
Green, J. L., & Plotkin, J. B. (2007). A statistical theory for sampling species abundances. Ecology Letters, 10, 1037-1045.
[2008, manual | www]
Grøtan, V., & Engen, S. (2008). Poilog: Poisson lognormal and bivariate Poisson lognormal distribution.
[1960, article]
MacArthur, R. H. (1960). On the relative abundance of species. American Naturalist, 94, 25-36.
[1932, article]
Motomura, I. (1932). On the statistical treatment of communities. Zoological Magazine, Tokyo, 44, 379-383.
[2009, article]
Pardini, R., Faria, D., Accacio, G. M., Laps, R. R., Mariano-Neto, E., & Paciencia, M. L. B., et al. (2009). The challenge of maintaining Atlantic forest biodiversity: A multi-taxa conservation assessment of specialist and generalist species in an agro-forestry mosaic in southern Bahia. Biological Conservation, 142(6), 1178-1190.
[2008, article | ribeiro2008.pdf]
Ribeiro, D. B., Prado, P. I., Brown Jr, K. S., & Freitas, A. V. L. (2008). Additive partitioning of butterfly diversity in a fragmented landscape: importance of scale and implications for conservation. Diversity and Distributions, 14(6), 961-968.

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