The performance of 3-PG model in Chinese fir plantations with different initial densities in southern China

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) is the most widely distributed conifer species in the subtropical region of southern China. Due to its ecological and economic significance, accurate prediction of growth of Chinese fir plantations is crucial for forest management and industrial timber production. In this study, we employed a physiologically process-based model (3-PG) to simulate the growth dynamic of Chinese fir plantations under various initial planting densities in southern China. Calibration and validation results indicated that the model outputs have strong correlations with the observed data (R2 > 0.79, p < 0.01), except foliage biomass and root biomass. Self-thinning will occur earlier at higher initial planting densities, and stand DBH and height will increase dramatically afterwards. Sensitivity analysis further revealed that the FR (soil fertility rating), alphaCx and gammaN1 parameters were highly sensitive in the 3-PG model (p < 0.01), while their sensitivity was influenced by stand age and initial density variations. This study confirmed that the parameter-specific optimized 3-PG model could accurately predict the growth process of Chinese fir plantations under different densities. It will provide a scientific reference for regional-scale management of Chinese fir plantations.