Using the Canoco for Windows 4.5 package
Jan Lepš, Petr Šmilauer · Cambridge University Press eBooks · 2003
Overview of the package The Canoco for Windows package is composed of several programs. In this section we summarize the role of each program in data analysis and in the interpretation of results. The following sections then deal with some typical aspects of this software use. This chapter is not meant to replace the documentation distributed with the Canoco for Windows package, but provides a starting point for efficient use of this software. Canoco for Windows 4.5 This is the central piece of the package. Here you specify the data you want to use, the ordination model to apply, and the analysis options. You can also select subsets of the explained and explanatory variables to use in the analysis or change the weights for the individual samples. All these choices are collected in a CANOCO project. Canoco for Windows allows one to use quite a wide range of ordination methods. The central ones are the linear methods (principal components analysis, PCA, and redundancy analysis, RDA) and the unimodal methods (correspondence analysis, CA, detrended correspondence analysis, DCA, and canonical correspondence analysis, CCA), but based on them you can use CANOCO to apply other methods such as multiple discriminant analysis (canonical variate analysis, CVA) or metric multidimensional scaling (principal coordinates analysis, PCoA) to your data set. From the widely used ordination methods, only non-metric multidimensional scaling (NMDS) is missing. CANOCO 4.5 This program can be used as a less user-friendly, but slightly more powerful alternative to the Canoco for Windows program.