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林业科学 ›› 2018, Vol. 54 ›› Issue (2): 81-89.doi: 10.11707/j.1001-7488.20180209

• 论文与研究报告 • 上一篇    下一篇

杉木单木和林分水平地下生物量模型的构建

赵嘉诚, 李海奎   

  1. 中国林业科学研究院资源信息研究所 北京 100091
  • 收稿日期:2016-05-17 修回日期:2016-12-17 出版日期:2018-02-25 发布日期:2018-03-30
  • 基金资助:
    国家自然科学基金项目"基于森林清查数据的大尺度森林碳储量监测方法研究"(31370634)。

Establishment of Below-Ground Biomass Equations for Chinese Fir at Tree and Stand Level

Zhao Jiacheng, Li Haikui   

  1. Research Institute of Forest Resource Information Techniques, CAF Beijing 100091
  • Received:2016-05-17 Revised:2016-12-17 Online:2018-02-25 Published:2018-03-30

摘要: [目的]利用一重样本和二重样本,构建单木地下生物量模型,比较抽样形式对单木模型的影响;在杉木主要分布区进行区域尺度扩展方法比较研究,探索不同形式林分模型的优劣,为在林分水平上估算地下生物量提供科学依据。[方法]以278株杉木地上生物量实测样本为一重样本,以其中88株有地下生物量的样本为二重样本,在只利用二重样本和两重样本相结合2种情况下,分独立模型、仅利用二重样本的兼容性模型和两重样本相结合的兼容性模型,构建3种单木地下生物量模型;分基于林分因子的地下生物量模型、固定根茎比模型和基于林分因子的根茎比模型,构建3种林分水平地下生物量模型,分别进行地下生物量从单木尺度向林分尺度的扩展。采用决定系数(R2)、均方根误差(RMSE)、平均系统误差(ASE)、平均相对误差绝对值(RMA)、总相对误差(TRE)以及平均预估精度(MPE)对模型拟合结果进行分析与评价,并对模型在三省的拟合参数以及与样本量的关系进行分析,同时与IPCC的根茎比模型的方法和参数进行比较。[结果]3种类型的单木模型拟合效果基本相同,决定系数(R2)均达到0.95以上,两重样本相结合的兼容模型取得了最优拟合效果;在区域尺度扩展时,基于林分因子的根茎比模型拟合效果明显优于固定根茎比模型(R2提高0.04~0.08,RMSE每公顷降低1 t左右);基于林分因子的地下生物量模型的拟合精度优于固定根茎比模型,但弱于基于林分因子的根茎比模型;地下生物量估测误差在三省之间表现出地域差异性,同一套方法在不同地区进行估计时无一致性规律。[结论]两重样本相结合的方法可提高单木地下生物量模型的拟合精度;增加林分调查因子能显著提高林分模型的拟合效果。固定根茎比模型形式简单,使用方便,在进行地下生物量大尺度扩展时可以取得较好效果。研究结果有助于单木地下生物量最优模型的筛选、构建,可为单木模型区域尺度扩展提供准确、科学的方法。

关键词: 杉木, 地下生物量, 双重抽样, 根茎比

Abstract: [Objective] In order to provide a scientific basis for below-ground biomass estimation at stand level, heavy sample and second sample were used, below-ground biomass equations were constructed and fitted to compare the effect of sampling forms on the individual tree biomass equations. In the main distribution area of Chinese fir(Cunninghamia lanceolata), the study on expanding below-ground biomass from individual tree to regional scale was conducted and the advantage and disadvantage of the different forms of below-ground biomass equations at stand level was explored.[Method] 278 trees of Chinese fir(C. lanceolata) with measured above-ground biomass were taken as a heavy sample, 88 trees of which with measured below-ground biomass as second sample. The models at individual level included single independent model, the simultaneous equations compatible with above-ground biomass, which only used second sample, and the simultaneous equations compatible with above-ground biomass, which combines a heavy sample and second sample. Choosing the below-ground biomass equation based on stand description factors, fixed root-shoot ratio equation and the root-shoot ratio equation based on stand description factors, the expansion method from tree level to regional scale on below-ground biomass were studied in Fujian, Jiangxi and Guangdong provinces. Coefficient of determination(R2), root mean square error(RMSE), average system error(ASE), relatively mean absolute error(RMA),relatively total error(TRE)and mean prediction error(MPE) were used to evaluate the model fitness. The model parameters in different provinces were compared and the relationship between stability of parameter estimates and sample size were analyzed. Meanwhile, parameter estimates were also compared with the root-shoot ratios recommended by IPCC.[Result] All three types of individual tree equations basically performed the same efficiency with R2 reaching to 0.95,the compatible equation combing a heavy sample and second sample performed best. The root-shoot ratio equation based on stand description factors had a significantly better fitting than the fixed root-shoot ratio equation(R2 improved 0.04-0.08, RMSE reduced 1 t·hm-2) when expanding to regional scale. The below-ground biomass equation based on stand description factors performed better than the fixed root-shoot ratio equation but inferior to the root-shoot ratio equation based on stand description factors. The prediction error had geography diversity and the same method on predicting error in different provinces failed to give a consistent law.[Conclusion] Combining a heavy sample and second sample contributes to model fitting at tree level. Adding stand description factors into below-ground biomass stand model significantly increases model fitness. As the form of fixed root-shoot ratio equation is sample, it could be conveniently used to conduct below-ground biomass expansion. The research result contribute to the selection and establishment of the best individual tree below-ground biomass equation, and provide an accurate and scientific method for tree-level biomass expansion to regional scale.

Key words: Cunninghamia lanceolata, below-ground biomass, double sampling, root-shoot ratio

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