Widagdo Faris Rafi Almay, Dong Lihu, Li Fengri
Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin 150040, China.
Plants (Basel). 2021 Jan 21;10(2):201. doi: 10.3390/plants10020201.
The population of natural Korean pine () in northeast China has sharply declined due to massive utilization for its high-quality timber, while this is vice versa for Korean pine plantations after various intensive afforestation schemes applied by China's central authority. Hence, more comprehensive models are needed to appropriately understand the allometric relationship variations between the two origins. In this study, we destructively sampled from several natural and plantation sites in northeast China to investigate the origin's effect on biomass equations. Nonlinear seemingly unrelated regression with weighted functions was used to present the additivity property and homogenize the model residuals in our two newly developed origin-free (population average) and origin-based (dummy variable) biomass functions. Variations in biomass allocations, carbon content, and root-to-shoot ratio between the samples obtained from plantations and natural stands were also investigated. The results showed that (1) involving the origin's effect in dummy variable models brought significant improvement in model performances compared to the population average models; (2) incorporating tree total height (H) as an additional predictor to diameter at breast height (D) consistently increase the models' accuracy compared to using D only as of the sole predictors for both model systems; (3) stems accounted for the highest partitioning proportions and foliage had the highest carbon content among all biomass components; (4) the root-to-shoot ratio ranged from 0.18-0.35, with plantations (0.28 ± 0.04) had slightly higher average value (±SD) compared to natural forests (0.25 ± 0.03). Our origin-based models can deliver more accurate individual tree biomass estimations for , particularly for the National Forest Inventory of China.
由于优质木材的大量采伐,中国东北天然红松()种群数量急剧下降,而在中国中央政府实施各种集约造林计划后,红松人工林的情况则相反。因此,需要更全面的模型来恰当理解这两种来源之间的异速生长关系变化。在本研究中,我们从中国东北的几个天然林和人工林地点进行破坏性采样,以研究来源对生物量方程的影响。我们使用带加权函数的非线性看似不相关回归来呈现加性属性,并使我们新开发的两个无来源(种群平均)和基于来源(虚拟变量)生物量函数中的模型残差均匀化。我们还研究了人工林和天然林样本之间生物量分配、碳含量和根冠比的变化。结果表明:(1)与种群平均模型相比,在虚拟变量模型中纳入来源效应可显著提高模型性能;(2)与仅使用胸径(D)作为唯一预测变量相比,将树高(H)作为胸径(D)的额外预测变量始终能提高两个模型系统的准确性;(3)在所有生物量组分中,树干所占分配比例最高,树叶的碳含量最高;(4)根冠比在0.18 - 0.35之间,人工林(0.28±0.04)的平均值(±标准差)略高于天然林(0.25±0.03)。我们基于来源的模型能够为红松提供更准确的单株生物量估计,特别是对于中国的国家森林资源清查。