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林业科学 ›› 2016, Vol. 52 ›› Issue (2): 1-9.doi: 10.11707/j.1001-7488.20160201

• 论文与研究报告 • 上一篇    下一篇

树种和组织对树干非结构性碳水化合物储量估测的影响

成方妍, 王传宽   

  1. 东北林业大学生态研究中心 哈尔滨 150040
  • 收稿日期:2015-02-02 修回日期:2015-12-31 出版日期:2016-02-25 发布日期:2016-03-25
  • 通讯作者: 王传宽
  • 基金资助:
    "十二五"国家科技支撑计划项目(2011BAD37B01)和教育部长江学者和创新团队发展计划(IRT_15R09)。

Impacts of Tree Species and Tissue on Estimation of Nonstructural Carbohydrates Storage in Trunk

Cheng Fangyan, Wang Chuankuan   

  1. Center for Ecological Research, Northeast Forestry University Harbin 150040
  • Received:2015-02-02 Revised:2015-12-31 Online:2016-02-25 Published:2016-03-25

摘要: [目的] 树木非结构性碳水化合物(NSC)储量存在空间变异,但在树干NSC储量估算时却很少考虑这种变异性。本研究量化树种、组织和树干高度对树干NSC储量估算的影响,为构建温带森林碳循环模型提供数据和理论基础。[方法] 以黑龙江省帽儿山地区无孔材树种兴安落叶松、半环孔材树种胡桃楸和环孔材树种春榆为对象,每树种各选取优势木3株,在生长季后期伐倒后按1 m区分段截取圆盘(18~21个),采用国际通用方法测定生物量;同时按树皮、边材和心材分别取样,采用苯酚硫酸改进法测定样品的可溶性糖和淀粉含量;最后分析树种、组织和树干高度对NSC储量估算的影响。[结果] 树种、组织和树干高度对可溶性糖、淀粉和NSC(即可溶性糖与淀粉之和)含量的影响极显著(P<0.01,树干高度对淀粉的影响除外); 3个树种树皮NSC平均储量(8.3%)分别为边材和心材平均储量的3和5倍,心材NSC储量的种间差异不显著,兴安落叶松树皮的NSC储量(12.0%)最高,边材的NSC储量最低(1.9%); 3个树种各组织不同树干高度NSC储量的相对变化量为50%左右,其中树皮和整个树干的NSC储量均随树干高度升高而增大,而平均枝下高以下树干边材和心材的NSC储量多随高度升高而略有降低;区分树干NSC储量的变异来源后发现,树种对树干NSC储量相对误差的贡献率达32%,组织间差异的贡献率在25%以上,高度变异的贡献率为9%。[结论] 树种、组织及树干高度显著影响树干NSC储量估算,其影响程度为树种> 组织> 树干高度。

关键词: 非结构性碳水化合物, 树种, 树皮, 边材, 心材, 误差分析

Abstract: [Objective] Estimating nonstructural carbohydrates (NSC) storage in trunk is important because the NSC is the major buffer of carbon for survival and growth of trees, and also reflects dynamics in carbon balance between uptake and investment and the responsive capacity of trees to various stresses. The NSC concentration in trunk may vary among different species and different tissues, but their effects on estimation of NSC storage in trunk are rarely examined. The objective of this study was to assess the effects of inter-specific and inter-tissue variations in NSC concentrations on NSC storage in trunks of larch (Larix gmelinii, non-porous species), walnut (Juglans mandshurica, semi-ring-porous species), and elm (Ulmus japonica, ring-porous species).[Method] Three dominant trees of each species were randomly selected and harvested in late growing season. Once a sampled tree was fell, a 5 cm-thick disc was cut from each 1-m interval trunk (18 to 21 discs in total for each tree).The discs were then partitioned into bark, sapwood, and heartwood tissues for NSC concentration determination. The biomass of all tissues was measured with the standard methods. The concentrations of soluble sugar and starch were measured with a modified phenol-sulfuric acid method. The relative errors in the estimates of NSC storage in trunk induced by inter-specific, inter-tissue and vertical variations in NSC concentrations were quantified based on the measurements of NSC concentration and biomass.[Result] Species, stem tissue and trunk height significantly influenced the concentration of soluble sugar, starch and TNC (the sum of sugar and starch; P<0.01, except for the height effect on starch). The mean TNC concentration in bark of the three species (8.3%) was 3- and 5-times as much as that in sapwood and heartwood, respectively. The larch had the highest TNC concentration in bark (12.0%), but lowest TNC concentration in sapwood (1.9%). There was no significant difference in the TNC concentration in heartwood among the species. The relative vertical variations in TNC concentration of the tissues for the three species averaged at about 50%. The NSC concentration in bark and whole trunk increased with the increase of trunk length, while the NSC concentration in sapwood and heartwood of branchless trunk declined slightly with the increase of trunk length. Partitioning the variability in the trunk TNC storage estimation, we found that tree species contributed 32% of the variability, tissue contributed >25%, and trunk length variation alone contributed to 9%.[Conclusion] Species, tissue and trunk length significantly influenced the estimation of NSC storage in trunk, and the strength of the impact ranked as species> tissue> trunk length.

Key words: nonstructural carbohydrates, tree species, bark, sapwood, heartwood, error analysis

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