Canonical correspondence analysis for forest site classification. A case study

Abstract

Canonical correspondence analysis (CCA) is an exploratory statistical method that can be applied to the investigation of vegetation-environment relationships and to forest site classification studies. This paper illustrates with a case study some of its advantages over other widely used methods - ecological profiles and correspondence analysis of species abundance data: i) CCA is a global method adapted to the frequent situation characterized by many species and several ecological variables; ii) it makes it possible to underscore the influence of the ecological gradients leg, water and nutrient availability) on species distribution while eliminating undesirable side effects (eg, the silvigenetic state of the stands); iii) it helps in selecting the ecological variables that are relevant for site classification; iv) it can be used to define synthetic indexes of the ecological optimum and amplitude of plant species and thus to obtain information on good bioindicator species.