Abstract: [Objective] Self-thinning line is an important curve for describing the tree death in a certain stand. The objective of this study was to provide a new idea for exploring self-thinning law using hierarchical Bayesian method based on the Chinese fir (Cunninghamia lanceolata) data with different initial densities in Fujian Province.[Method] Firstly, the maximum-size density equation was established according to the relationship between stand quadratic mean diameter and number of trees per hectare. For analyzing the effect of initial density on maximum-size density line, we introduced the hierarchical Bayesian models: 1) random effect on the intercept; 2) random effect on the slope; 3) random effects on the intercept and slope. [Result] The results showed that the hierarchical Bayesian models (R²=0.867 8) were better than non-hierarchical Bayesian model (R²=0.859 3). The random effects of initial density were not significant neither on the intercept (σ₀²=0.008,SD=0.029) nor on the slope (σ₁²=0.003,SD=0.016). In addition, the uncertainty of model predictions was mostly due to within-subject variability.[Conclusion] Hierarchical Bayesian method provided a reasonable explanation of the impact of other variables on maximum-size density line, which gave us the posterior distribution of parameters of maximum-size density line. The research of maximum-size density line could be benefit from the use of hierarchical Bayesian method and helpful for managing Chinese fir plantations.

Key words: hierarchical Bayesian method, Chinese fir plantation, maximum-size density line, initial planting density