Objective This paper explores the influence of different methods of competing trees on the calculation of neighborhood competition index, analyzes the corresponding rules of Larix olgensis biomass on neighborhood competition, so as to provide a theoretical basis for the research on competition mechanism of planted forests.

Method Based on the analytical wood data of 147 sample trees of L. olgensis in Mengjiagang Forest Farm, Heilongjiang Province of northeastern China, this study analyzed the effects of neighborhood competition on the biomass and its allocation of tree wood, bark, branch, leaf and root. Four methods for selecting competing trees (fixed radius method, dynamic radius method, adjacent tree method and control tree number method) were adoped. Based on the existing nine competition indexes (CI₁−CI₉), through correlation analysis and random forest importance ranking, the optimal neighborhood competition index was screened, and the relationship between biomass of L. olgensis and its distribution and neighborhood competition was analyzed.

Result The optimal competition index varied with different methods. When the fixed radius method was used to select competing trees, the competition index (CI₃) related to the object trees and DBH of competing trees had the strongest correlation with biomass. When the dynamic radius method was adopted, the competition index (CI₁) related to DBH of competing trees and the object trees, as well as the distance between them had the strongest correlation with biomass. When the adjacent tree method was adopted, the competition index (CI₉) related to DBH and tree height of the object trees and competing trees, as well as the distance between them had the strongest correlation with biomass. When the method of controlling the number of plants was adopted, the correlation between competition index CI₁ and biomass was the strongest. The results of random forests showed that the competition index selected by method of controlling the number of plants had the strongest correlation with biomass of L. olgensis. There was a significant negative correlation between biomass of each component of L. olgensis and neighborhood competition index (P < 0.001). The biomass distribution ratio of each component was wood (63.6%) > root (17.8%) > branch (10.0%) > bark (6.6%) > leaf (2.0%). The neighborhood competition index was significantly negatively correlated with biomass allocation ratios of tree wood and root (P < 0.001), while it was significantly positively correlated with biomass allocation ratios of bark, branch and leaf (P < 0.001).

Conclusion Neighborhood competition significantly affects the biomass and distribution of each component of L. olgensis. The influence of competition should be considered in the biomass model estimation. This study provides theoretical support for accurate estimation of biomass of L. olgensis plantation in northeastern China.