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Welcome to RMacoqui project!

RMacoqui develops a probability procedure for the identification of chorotypes, i.e. distribution patterns shared by a group of species, which can be operatively identified within an area (Baroni-Urbani et al., 1978).

The method was first published by Márquez et al. (1997), based on a prior proposal for detecting biogeographic boundaries (Real et al., 1992), and with a mathematic rationale derived from McCoy et al. (1986).

The method for chorotype identification was later enhanced by Muñoz et al. (2003) and Real et al. (2008), and was updated and contextualized under a fuzzy logic framework by Olivero et al. (2011).

RMacoqui outputs are also useful as the basis for delimiting biogeographic regions and transition zones with the support of fuzzy logic (Olivero et al. 2013).

Installing, loading and using RMacoqui

To install RMacoqui directly form R-Forge, paste the following command in the R console (while connected to the internet):

install.packages("RMacoqui", repos="http://R-Forge.R-project.org")

This should work if you have the latest version of R; otherwise, it may either fail (producing a message like "package 'RMacoqui' is not available for your R version") or install an older version of RMacoqui -- you can check the version that you have actually installed by typing citation(package="RMacoqui"). To make sure you install the latest RMacoqui version, you can either upgrade R or download the compressed package source files to your disk (.zip for Windows or .tar.gz for Linux and Mac, available here) and then install the package from the disk, e.g. with R menu "Packages - Install packages from local zip files" (Windows), or "Packages & Data - Package installer, Packages repository - Local source package" (Mac), or "Tools - Install packages - Install from: Package Archive File" (RStudio).

Here's a reference manual based on the package help files, and a very quick tutorial of the package; a more detailed one is in preparation.

The project summary page you can find here.


Baroni-Urbani C., Rufo S., Vigna-Taglianti A. (1978) Materiali per una biogeografia italiana fondata su alcuni generi di Coleotteri, Cicindelidi, Carabidi e Crisomelidi. Estratto della Memorie della Società Entomologica Italiana 56:35-92.

Márquez A.L., Real R., Vargas J.M., Salvo A.E. (1997) On identifying common distribution patterns and their causal factors: a probabilistic method applied to pteridophytes in the Iberian Peninsula. Journal of Biogeography 24:613-631.

McCoy E.D., Bell S.S., Waters K. (1986) Identifying biotic boundaries along environmental gradients. Ecology 67:749-759.

Muñoz A.R., Real R., Olivero J., Márquez A.L., Guerrero J.C., Barcena S.B., Vargas J.M. (2003) Biogeographical zonation of African hornbills and their biotic and geographic characterisations. Ostrich 74:39-47.

Olivero J., Real R., Márquez A.L. (2011) Fuzzy chorotypes as a conceptual tool to improve insight into biogeographic patterns. Systematic Biology 60:645-660.

Olivero J., Márquez A.L., Real R. (2013) Integrating fuzzy logic and statistics to improve the reliable delimitation of biogeographic regions and transition zones. Systematic Biology 62:1-21.

Real R., Olivero J., Vargas J.M. (2008) Using chorotypes to deconstruct biogeographical and biodiversity patterns: the case of breeding waterbirds in Europe. Global Ecology and Biogeography 17:735-746.

Real R., Vargas J.M., Guerrero J.C. (1992) Análisis biogeográfico de clasificación de áreas y especies. Monografías de Herpetología 2:73-84.