The PCA index for measuring functional diversity and its application to Juglans mandshurica communities in the Beijing mountains, China

Abstract

Methods for measuring functional diversity are essential for functional studies of plant communities. A useful method, the PCA index, based on principal component analysis ordination of functional trait data was introduced and applied to functional diversity analysis of Juglans mandshurica communities in the Beijing Mountains. Thirty-five [Formula: see text] quadrats were established in Juglans mandshurica communities. Species composition, functional traits and environmental factors were measured and recorded. The four common indices, FAD, MFAD, FDp and FDc, were used and compared with the PCA index in the analysis. The results showed that the PCA index was successful in quantifying functional diversity and describing its relationships with environmental variables; therefore, it was an effective index in functional diversity analyses. Functional diversity in Juglans mandshuricacommunities varied widely. Elevation and aspect were the key factors affecting functional diversity in communities. Functional diversity increased with elevation increases and with the change in aspect from North to South. Functional diversity was significantly correlated with species richness and heterogeneity.