ESTIMATION OF WOOD VOLUME UNDER BARK USING THE BARK FACTOR OF PINUS BRUTIA TEN. GROWN NATURALLY IN ZAWITA FOREST

This study aimed to estimate the under-bark wood volume of Pinus brutia Ten. naturally growing in the Zawita region of Dohuk Governorate, Kurdistan Region of Iraq. This research matters because timber is typically marketed after bark removal, while the bark itself also has considerable economic value in the chemical and pharmaceutical industries. Field data were collected from 50 carefully selected trees, including measurements of diameter at breast height (dbh), total and commercial height, and bark thickness at different points along the stem. Mathematical and statistical models were applied, including Mayer’s method to calculate the bark factor (k) and regression models to estimate bark thickness based on dbh. The results showed that. The best model for predicting bark thickness was a simple nonlinear regression model based on dbh. The bark factor value for Pinus brutia Ten. in Zawita was 0.88. Standard under-bark volume tables were developed using dbh and merchantable height, allowing accurate estimation of net wood volume without felling the trees. The study concludes that integrating the bark factor with regression-based models offers a practical and efficient approach for estimating both wood and bark volumes, supporting sustainable forest management and the economic assessment of timber resources in accordance with market standards.