Developing Biomass Growth Models for Chinese Fir Plantations Based on National Forest Inventory Data

The study aims to analyze comprehensive effects of site quality class (SQC), stand density index (SDI), and species composition (SC) on biomass growth. Based on 5872 observations from 2040 permanent sample plots of Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) plantations from successive national forest resource inventories, five classical growth equations were employed and nonlinear regression and dummy variables were used for modeling. A dominant height (DH) growth model was first developed to determine SQC, followed by a series of stand biomass (SB) growth models incorporating SQC, SDI, and SC (pure vs. mixed stands). Growth differences among different classes or categories were analyzed using inflection age and optimal rotation age. The results show that Korf equation performed best for both DH and SB growth models; SDI contributed the most to SB growth, followed by SQC, with their interaction accounting for over half of the total contribution. Mixed stands grew faster than pure stands; higher SQC was associated with faster growth and earlier attainment of inflection age and optimal rotation age. The productivity increased with rising SDI, but the rate of increase gradually diminished. Different optimal rotation ages should be determined for pure and mixed stands across different SQCs. Reasonable adjustment of harvesting age and control of stand density represent the greatest potential for improving forest productivity.