Tests of Distance-Dependent Competition Indices for Predicting Growth of Japanese Larch Trees

Abstract

We examined the usefulness of distance-dependent competition indices for predicting individual tree basal area growth in a mature Japanese larch plantation. Using data from a permanent sample plot, we calculated several traditional distance-dependent competition indices and constructed individual growth prediction models. Results of regression analyses suggested that tree size could explain a large part of variation in tree growth much better than distance-dependent competition indices. We also used local indicators of spatial association to detect “hot spots,” or clusters of similar-sized trees, and “cold spots,” or clusters of trees of varying sizes within sample plots. Relationships between basal area growth and diameter of trees in “hot spots” and “cold spots” were analyzed.