Quantifying the impact of
competition on individual tree biomass and its distribution pattern can provide a basis for improving the prediction accuracy of forest biomass models. To accurately quantify the effects of
competition factors on individual biomass and its distribution, we constructed three different individual biomass models by using nonlinear coupling equations based on the biomass survey data of 50 Larix gmelinii from 18 plots of Pangu Forest Farm in Daxing\'an Mountains. M-1 was a traditional singly additive biomass model. M-2 and M-3 were models taking the distance dependent simple
competition index (CI) and distance independent relative diameter (Rd) into account, respectively. Those models were used to reveal the influence of
competition factors on the prediction accuracy and distribution pattern of single tree biomass model of L. gmelinii. The results showed that the adjusted R2 of three additive models ranged from 0.694 to 0.974, mean prediction errors ranged from -0.017 to 0.021, and mean absolute errors ranged from 0.152 to 0.357. The introduction of Rd could improve the fitting degree and prediction accuracy of most biomass models, but CI did not affect the model fitting effect and prediction ability. Among the three models, M-3 model had the best performance, with good fitting degree and prediction accuracy of the biomass of each part, which could accurately estimate the single tree biomass of L. gmelinii. Further simulation results showed that the variation of biomass with DBH was mainly affected by CI and Rd grade, and the influence of Rd was stronger than CI. CI had greater influence on root and dry biomass, but less influence on branch and leaf biomass. Rd had a more significant effect on biomass of branch and leaf than on that of root and trunk.
量化竞争对单木生物量及其分配格局的影响,可以为提高林木生物量模型预估精度提供基础。本研究以大兴安岭地区盘古林场18块固定样地中50株兴安落叶松的生物量调查数据为基础,采用非线性联立方程组构建含不同竞争因子(与距离有关的简单竞争指标CI和与距离无关的林木相对直径Rd)的对数尺度单木聚合型二元可加性生物量模型M-2和M-3,并与传统一元可加性生物量模型M-1进行比较,量化竞争因子对兴安落叶松天然林单木生物量模型预估精度及其分配格局的影响。结果表明: 3种可加性模型的调整后确定系数为0.694~0.974,平均预测误差为-0.017~0.021,平均绝对误差为0.152~0.357。引入Rd可以提高绝大多数生物量模型的拟合效果和预测能力,而引入CI对绝大多数生物量模型拟合效果和预测能力的影响不显著。3种模型中,M-3对各部分生物量具有较好的拟合效果和预测能力,可以对兴安落叶松单木生物量进行较好的估计。模拟结果显示,生物量随胸径的变化受CI、Rd等级的影响,其中Rd较CI影响更大;CI对树根和树干生物量影响较大,对树枝、树叶生物量影响较小;Rd对树枝、树叶生物量的影响较树根、树干生物量更大。.