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    山西高原主要林型生物量异速生长模型

    Biomass allometric model of main forest types in Shanxi Plateau

    • 摘要: 基于山西省10个生态站3种森林类型(落叶阔叶林(DBF)、温性针叶林(TCF)、寒温性针叶林(CCF))9个树种共97株解析木数据, 采用收获法测定各树种的组分(树干、树根、树冠)生物量, 利用解析木的胸径(D)和树高(H)及其组合构建各林型不同部位的生物量异速生长模型, 分析不同树种的生物量分配并比较不同模型的准确性。结果表明: 1)9个树种的树干、树冠和树根平均生物量占各自总生物量的比例分别为47.22%、25.59%和27.18%;除樟子松外, 其他树种的树干生物量占总生物量比例均最大; 9个树种根冠比在0.12~0.88之间, 侧柏最大, 樟子松最小。2)在树干生物量模型中, 以DH为共同变量建立的方程拟合效果较好, 其中以D2×H作为自变量的3种林型(DBF、TCF和CCF)模型的决定系数R2分别为0.82、0.97和0.96;以D+H作为自变量模型的决定系数R2分别为0.84、0.97和0.98;树冠和树根生物量模型与树干模型的拟合结果相似, 以DH作为自变量建立的模型同样可以很好地预测树冠和树干的生物量, 3种林型生物量回归方程的R2值树冠分别为0.67、0.75和0.88, 树根为0.61(DBF)和0.70(CF)。3)本研究建立的模型预测的生物量预测偏差显著低于中国森林模型的预测结果。总之, 以DH作为自变量建立的异速生长方程更能准确估算研究区不同森林类型的生物量。

       

      Abstract:
      Background The distribution pattern and estimation model of forest biomass differ greatly in different regions. It is necessary to establish a biomass growth model suitable for specific area and specific environmental conditions to accurately estimate regional forest biomass and reduce estimation errors. To establish biomass allometry models of different forest types in Shanxi Plateau is of scientific significance for forest productivity and carbon cycle research.
      Methods Based on the data of a total of 97 trees of 9 tree species, which was grouped into deciduous broad-leaved forest(DBF), temperate coniferous forest(TCF) and cold temperate coniferous forest(CCF), from 10 representative ecological stations in Shanxi province, as well as their biomass data of the each part of the species measured by harvest method, we established their biomass regression models by using diameter at breast height(D) and height(H) of a tree as the independent variables for the three forest types to compare the accuracy of the models.
      Results 1) The overall average proportion of total biomass in trunk, crown and root of the 9 tree species was 47.22%, 25.59% and 27.18%, respectively; except for Pinus sylvestris, the tree trunk biomass accounted for the largest proportion of the total biomass. The ratio of root to shoot of the all tree species ranged from 0.12-0.88, with a maximum and minimum ratio in both Platycladus orientalis and Pinus sylvestris. 2) Among trunk biomass models, the model including both D and H variables fitted well for all the species. The determination coefficient(R2) of the model for DBF, TCF and, CCF species, when both D and H was used as a combining variable(D2×H), reached 0.82, 0.97 and 0.96, respectively. The R2 of the model, when D and H were used as additive variable(D+H), were 0.84, 0.97 and 0.98, respectively, for DBF, TCF and CCF, respectively. For canopy and root biomass, the performance of the models was similar to those for the trunks, and both D and H could be well used to estimate their biomass. The R2 values of the fitted models for canopy biomass were 0.67, 0.75 and 0.88 for DBF, TCF, and CCF, respectively, and 0.61 and 0.70 for the roots biomass for both DBF and CF. 3) Comparing with the results from the Chinese Forest Model(CFM), the biomass prediction deviation from the current models was significantly less than those from the CFM.
      Conclusions The established allometric equations using both D and H as independent variables in our study are more suitable for biomass estimation of this area. In practical applications, a model that is applicable and meets the accuracy requirements should be selected for different sites.

       

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