ABSTRACT

Globally, almost 2 billion cubic meters of industrial roundwood are harvested yearly. Two of the most common methods of harvest and extraction are cut-to-length (CTL) and full-tree or tree-length (FT/TL). The aim of this study was to compile data on annual volumes of industrial roundwood harvested by the main methods in forestry countries. To quantify the effect of potential explanatory variables, the data were subjected to linear regression analysis, using shares of roundwood volumes harvested by fully mechanized CTL and/or FT/TL as response variables. Generally, high diesel price and Gross Domestic Product appear to favor CTL, while high shares of steep terrain (>20°) in forest land decrease the leve l of both mechanization and CTL, and low Social Security Rate (SSR) favor FT/TL. Two models were created for CTL, one with an R² of 0.64 and another more complex with an R² of 0.75. A separate model for mechanization (CTL and FT/TL together) showed an R² 0.57. The CTL models could potentially be used to predict shares of roundwood volumes harvested by CTL in countries not included in this study. Predictions for countries with large harvested volumes, e.g. China and India, are presented here, but they require validation, as does the model’s applicability for countries with small harvested volumes. Countries with less than 10% of steep slope forests are almost exclusively mechanized according to the model. For FT/TL, the proposed model is probably not sufficiently robust for prediction, but it highlights SSR as one important explanatory variable.