Studying beta diversity: ecological variation partitioning by multiple regression and canonical analysis

Aims: Beta diversity is the variation in species composition amongsites in a geographic region. Beta diversity is a key conceptfor understanding the functioning of ecosystems, for the conservationof biodiversity and for ecosystem management. The present reportdescribes how to analyse beta diversity from community compositionand associated environmental and spatial data tables. Methods: Beta diversity can be studied by computing diversity indicesfor each site and testing hypotheses about the factors thatmay explain the variation among sites. Alternatively, one cancarry out a direct analysis of the community composition datatable over the study sites, as a function of sets of environmentaland spatial variables. These analyses are carried out by thestatistical method of partitioning the variation of the diversityindices or the community composition data table with respectto environmental and spatial variables. Variation partitioningis briefly described herein. Important findings: Variation partitioning is a method of choice for the interpretationof beta diversity using tables of environmental and spatialvariables. Beta diversity is an interesting ‘currency’for ecologists to compare either different sampling areas ordifferent ecological communities co-occurring in an area. Partitioningmust be based upon unbiased estimates of the variation of thecommunity composition data table that is explained by the varioustables of explanatory variables. The adjusted coefficient ofdetermination provides such an unbiased estimate in both multipleregression and canonical redundancy analysis. After partitioning,one can test the significance of the fractions of interest andplot maps of the fitted values corresponding to these fractions.