R Stuff

Some R-codes, class notes and tutorials produced by our team and collaborators. 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.

• Package sads on CRAN

• Package site at GitHub

• R Package pse on CRAN
• Chalom, A. & Prado, P.I. 2012. Parameter space exploration of ecological models. http://arxiv.org/abs/1210.6278

• On line syllabus from our graduate course on using R in ecology. In portuguese.
• Tutorials on basic use of the R environment, from our graduate course on using R in ecology. In portuguese.
• quick R tutorial on model fiting by the maximum likelihood method. In portuguese.
• Our graduate course on statistical modelling: nice R tutorials and study notes. In portuguese.

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 code used by Ribeiro et al. (2008). Apart code fine-tuning, in this version average diversity indexes are not weighted (see Crist et al. 2003).

• R code - Sample-based partition test
• Test data: birds in Southern Bahia (Pardini et al. 2009).
• Results of analysis of test data
• An introductory tutorial in R of additive diversity partitioning, from a graduate course (in portuguese).

Compound generalized linear models of Pardini et al. (2010).

Different combinations of Poisson and negative binomial linear models were used to predict number of species (or individuals) of small mammals in three landscapes that differ in the remaining forest cover. Each of these combinations represents alternative hypotheses on the interaction between landscape context and patch-area in fragmented landscapes.

• R codes of the analysis
• Structure of the database used

[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.

[2010, article | www]

Pardini, R., de Bueno, A. A., Gardner, T. A., Prado, P. I., & Metzger, J. P. (2010). Beyond the Fragmentation Threshold Hypothesis: Regime Shifts in Biodiversity Across Fragmented Landscapes. PLoS ONE, 5(10), 13666.

[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.