Methods and Practices for Analyzing Vegetation Shift Using Phytosociological Hierarchical Data

Abstract

We introduce a procedure to predict the vegetation shift using traditional phytosociological survey (cover data). The cover value is generally obtained for each layer of the layered plant community, but usually maximum cover value over the layers used for the vegetation classification and recognition (C-max procedure). As an ameliorate procedure, we propose the procedure of every coverage of all layers used to evaluate vegetation shift (C-all procedure). The C-all procedure enables us to embrace the information on vertical gradient of species distribution in the surveyed communities. In the case of our observations and analyses, tree species with smaller (or no) cover in the upper layer but greater cover in the lower layer can be dominant in the upper layer in the future, resulting in vegetation shift (changes in dominant species of the community). Every general community analysis (cluster analysis, INSPAN, and TWINSPAN) followed by C-all procedure supports such prediction for some types of Japanese forests. In the forests, changes in species composition have been conventionally predicted by measuring the trunk diameter and height of trees. Our proposal suggests that traditional phytosociological survey is also convenient for studying forest succession and regeneration.