| 孙红召,任军战,李伟波,乔王铁,刘晓良,黄新峰.白皮松幼树生物量分配格局及模型构建[J].林业调查规划,2026,51(2):8-16 |
| 白皮松幼树生物量分配格局及模型构建 |
| Biomass Allocation Patterns and Models Construction forYoung Pinus bungeana |
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| DOI： |
| 中文关键词: 白皮松 幼树生物量 分配格局 模型构建 异速生长模型 |
| 英文关键词: Pinus bungeana sapling biomass allocation pattern model construction allometric growth model |
| 基金项目:河南省省级财政科技兴林项目(YLK202301). |
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| 中文摘要: |
| 为了掌握白皮松幼树生物量分配特征,构建各组分的最优生物量模型,2024年7月在河南济源太行山区选取生长状态良好的幼树进行整株取样,共收集测定49株样木的叶、枝、干和根生物量及其分配比例,计算地上部分、整株生物量。以基径、树高及其不同组合形式为自变量构建叶、枝、干、地上部分、根和整株的一元线性、二元线性和非线性生物量模型,使用留一交叉验证法对模型进行检验,通过调整决定系数、均方根误差、赤池信息准则等指标筛选最优生物量模型。结果表明,白皮松幼树呈干生物量占比最高(40.1%~48.8%),叶生物量次之(18.3%~24.1%),根生物量(18.3%~18.6%)随后,枝生物量最低(14.8%~17.4%)的分配格局。随着基径增长,干生物量占比逐步下降,叶和枝生物量占比逐渐上升,根生物量占比缓慢增加。平均根冠比为0.24。样地总生物量为293.0 kg/hm2。以D或D2为自变量的一元方程拟合精度优于以H或H2为自变量的一元方程,二元线性方程并未提高模型拟合效果,非线性方程拟合效果优于线性方程,D2H和DbHc是拟合效果最佳的组合形式。叶、枝和根以方程M=β0Dβ1为最优,干和整株以方程M=β0Dβ1Hβ2为最优,地上部分以方程M=β0(D2H)β1为最优。方程拟合效果以干的拟合精度最高,其他依次为整株、根、地上部分、叶和枝。所建立的异速生长模型可用于白皮松幼树的生物量估计。 |
| 英文摘要: |
| To understand the biomass allocation characteristics of Pinus bungeana saplings and construct optimal biomass models for their components, a whole-plant sampling of healthy saplings was conducted in July 2024 in the Taihang Mountain region of Jiyuan, Henan Province. A total of 49 sample trees were collected, and the biomass of leaves, branches, stems, and roots, along with their allocation ratios, were measured. Aboveground and whole-plant biomass were subsequently calculated. Univariate linear, bivariate linear, and nonlinear biomass models were developed for leaves, branches, stems, aboveground parts, roots, and whole plants, using basal diameter (D), tree height (H), and their combinations as independent variables. The models were evaluated via leave-one-out cross-validation, with optimal models selected based on adjusted coefficient of determination, root mean square error, and Akaike′s information criterion. The results revealed the following biomass allocation patterns in P.bungeana saplings: stems accounted for the highest proportion (40.1%-48.8%), followed by leaves (18.3%-24.1%), roots (18.3%-18.6%), and branches (14.8%-17.4%). As basal diameter increased, the stem biomass proportion gradually decreased, while leaf and branch proportions increased, and root biomass exhibited a slight rise. The root-to-shoot ratio was 0.24, and the average biomass per hectare was 293.0 kg. Univariate equations using D or D2 as independent variables outperformed those based on H or H2. Bivariate linear equations did not improve model accuracy, whereas nonlinear equations yielded better fits than linear ones. The combinations D2H and DbHc showed the highest predictive performance. The optimal model form for leaf, branch, and root biomass was M=β0Dβ1, for stem and whole-plant biomass, it was M=β0Dβ1Hβ2, and for aboveground biomass, it was M=β0(D2H)β1. Regarding model fitting accuracy, the stem biomass model showed the highest precision, followed (in descending order) by the whole-plant, root, aboveground, leaf, and branch biomass models. The developed allometric growth models can be used for biomass estimation in P.bungeana saplings. |
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