Predicting volumes by log grades in standing sugar maple and yellow birch trees in southern Quebec, Canada

Abstract

Modelling volumes by log grades in standing hardwood trees is often hindered by the nature of the response variable. In this paper, we used a two-part conditional model to account for the excess of zero responses for some log grades. Moreover, this approach was used as a framework to compare three different tree classifications in their ability to predict volumes by log grades in standing yellow birch ( Betula alleghaniensis Britton) and sugar maple ( Acer saccharum Marsh.) trees. A tree grade classification was compared with two preharvest tree classifications based on mortality risk assessment. A cross-validation was also carried out to evaluate the two parts of the model. The results showed that the two-part conditional approach was efficient in this case study. Compared with a general model, the three classifications improved the maximum likelihood. According to the Akaike and Bayesian information criteria, the tree grade classification was the “best” one. All three classifications proved to be better able to distinguish log grade occurrence than log grade volume. Although it implies additional cost, the implementation of the tree grade classification into the preharvest inventories would improve the prediction of volumes by log grades for yellow birch and sugar maple trees.