Korean pine (Pinus koraiensis Sieb. et Zucc.) is the most important forest vegetation in northeast China. The timber quality of this tree species is largely driven by branch growth and distribution within the crown. Thus, developing branch diameter and length models, especially those that include competition indices, is essential. A total of 48 Korean pine trees were selected to conduct destructive measurements of branch characteristics. This was carried out on all live branches, and a branch diameter and length model was developed. Various indices, including the absolute depth into the branch base (DINC) from tree tip, were used. The equation with the largest R_adj² and smallest root mean square error (RMSE) values was selected as the best model. Each parameter from the best model was reparameterized to the tree variables and competition indices. Finally, the branch diameter model that included diameter at the breast height (DBH), tree height (HT), and the crown length index (CLI), and the branch length model that included DBH and HT exhibited the best performance. The R_adj² and RMSE values were 0.42 and 4 mm, respectively, for the branch diameter model, and 0.77 and 63 cm, respectively, for the branch length model. Branch diameter and length increased as DBH increased and decreased as HT increased. Furthermore, branch diameter decreased as the CLI increased.

Korean pine is an important component species of forest vegetation in northeastern China. Research on the diameter increment of Korean pine is of great significance for future forest management. In this study, 48 Korean pine trees were destructively sampled, and the diameter increment was measured at three positions along the tree bole: breast height, crown base, and maximum crown width. Age, tree size, competition, and site factors were used as candidate variables. Thirteen candidate models were fitted, and the successfully converged models were compared using the adjusted determination coefficient (R²_adj), root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). M11 (logarithmic function) performed best at breast height, whereas M12 (quadratic function) performed best at the crown base and maximum crown width. Based on this, re-parameterization was applied to incorporate additional variables. The final models retained the ratio of HT to DBH (HDR), the height to the crown base (HCB), and crown length (CL) at breast height, and HDR and HCB at both the crown base and maximum crown width. Overall, the final models showed good fitting performance, explaining 61.9%–70.1% of the variation in diameter increment models across the three positions. The models developed in this study can accurately predict growth at different positions along the tree bole and provide support for the precision management of Korean pine plantations.