Statistical methods available so far to analyze such data either assumed linear relationships or were restricted to regression analysis of the response of each species separately. The use of canonical ordination greatly improves he power to detect the specific effects one is interested in. One of these techniques, canonical correspondence analysis, escapes the assumption of linearity and is able to detect unimodal relationships between species and external variables. Such use is explained in separate sections in the manual. Most importantly, the program is easier to use for the novice to ordination.
Principal coordinates analysis and canonical variates analysis are also available.
A partial analysis allows one to display the residual variation in the species data and to relate the residual variation to the variables one is specifically interested in. Partial canonical correspondence analysis is the appropriate technique for the analysis of permanent plot data or for the joint analysis of data from several locations. At each step, a Monte Carlo statistical test can be carried out to judge the significance of the selected variable. The solution file of the analysis cannot only be used for graphics programs, but also be used as input for subsequent analyses. This possibility allows one, for example, to use principal components extracted from environmental data as input for a later canonical analysis of species data.