Empirical Relationships of the Characteristics of Standing Trees with the Dynamic Modulus of Elasticity of Japanese Cedar (Cryptomeria japonica) Logs: Case Study in the Kyoto Prefecture

With growing worldwide interest in constructing larger and taller wooden buildings, wood properties, such as the dynamic modulus of elasticity (MOEdyn), have become increasingly important. However, the MOEdyn of trees and logs has rarely been considered in forest management because a method for estimating the MOEdyn of logs based on standing tree characteristics has been lacking. Herein, we explored the multiple relationships between the MOEdyn of logs and standing tree characteristics of Japanese cedar (Cryptomeria japonica) such as tree height, diameter at breast height (DBH), and tree age, including the stress-wave velocity of the tree, which is known to be correlated with the MOEdyn of logs. The relationship between the MOEdyn of logs and standing tree characteristics was investigated by considering the bucking position. Different trends between the bottom logs and upper logs were found for all characteristics, showing a multiple trend of tree characteristics with the MOEdyn of logs based on the bucking position. The top three generalised linear mixed models for the prediction of the MOEdyn of logs showed relatively high accuracies when the bucking position was considered as a random effect. Although the contribution of the stress-wave velocity of the tree was relatively high, adding tree age improved the accuracy of the model, and this model was selected as the top model. The model for the bottom log, utilising the stress-wave velocity and age of the tree as explanatory variables, was highly explanatory (R2 = 0.70); however, the best model for upper logs was only moderately explanatory (R2 = 0.44). In addition, tree height and DBH were selected as explanatory variables along with tree age in the second and third models, which suggested the importance of growth rate rather than tree size. Therefore, adding correlates associated to characteristics related to height growth, such as site index, and DBH growth, such as stand density, is expected to improve model accuracy.