Error Analysis on the Five Stand Biomass Growth Estimation Methods for a Sub-Alpine Natural Pine Forest in Yunnan, Southwestern China

Forest biomass measurement or estimation is critical for forest monitoring at the stand scale, but errors among different estimations in investigation are unclear. Thus, Pinus densata natural Shangri-La City, southwestern China, was selected as research object to investigate of 84 plots and 100 samples P. densata. The calculated using five methods: growth with age (SBA), stem combined expansion factors (SB+BEF), volume conversion (SV+BCEF), individual tree diameter structure (IB+SDS), density (IB+SD). methods were then analyzed. results showed that suitable estimating SB+BEF, M+BCEF, IB+SDS. When these three (SB+BEF, SV+BCEF, IB+SDS) estimate components, wood SB+BEF unsuitable, root employing IB+SDS method not preferred. SV+BCEF better estimation. Except branches, mean relative error (MRE) other components presented minor estimation, while MRE lower than range from −0.11%–28.93%. more appealing branches its only 0.31% SV+BCEF. strongly correlated BEF, BCEF, structure, age, factors. Hence, model system established this study effectively predicted dynamics provided a theoretical basis practical support accurately growth.