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林业科学 ›› 2019, Vol. 55 ›› Issue (11): 1-8.doi: 10.11707/j.1001-7488.20191101

• 论文与研究报告 • 上一篇    下一篇

我国人工杨树生物量建模和生产力分析

曾伟生,陈新云,杨学云   

  1. 国家林业和草原局调查规划设计院 北京 100714
  • 收稿日期:2019-02-21 出版日期:2019-11-25 发布日期:2019-12-21
  • 基金资助:
    国家自然科学基金项目(31770676)

Biomass Modeling and Productivity Analysis of Planted Populus spp. in China

Weisheng Zeng,Xinyun Chen,Xueyun Yang   

  1. Academy of Forest Inventory and Planning, National Forestry and Grassland Administration Beijing 100714
  • Received:2019-02-21 Online:2019-11-25 Published:2019-12-21
  • Supported by:
    国家自然科学基金项目(31770676)

摘要:

目的: 建立人工杨树生物量模型,分析生产力与气候因子间的关系,为提升我国森林质量提供参考。方法: 基于在全国15个省(区、市)采集的450株人工杨树样木实测地上生物量和147株地下生物量数据,综合利用哑变量建模方法和误差变量联立方程组方法,建立一元和二元立木生物量联立方程组;基于样木胸径、树高和年龄的成对数据,建立与气候因子相关的单木生长模型。根据胸径和树高单木生长模型及二元立木生物量方程,分析气候因子对人工杨树单木生产力的影响。利用全国森林资源连续清查人工杨树林样地调查数据,计算每个样地的生物量和生产力,建立人工杨树林生产力与气候因子间的相关模型,进一步验证气候因子对生产力的影响。结果: 本研究建立的一元和二元人工杨树地上生物量方程,确定系数(R2)在0.90以上,平均预估误差(MPE)在5%以内;地下生物量方程的R2在0.83以上,MPE在10%以内;含气候因子的胸径和树高单木生长模型,R2均在0.70以上,MPE分别在5%和3%以内。人工杨树的胸径、树高生长均与年均气温显著相关,林木年龄为20年,年均气温20℃时的胸径、树高和总生物量分别是年均气温0℃时的2.4、2.4和9.5倍。连清样地数据验证结果表明,年均气温提高10℃,人工杨树林的平均生产力可以提高2.5 t·hm-2a-1;年均气温20℃时的人工杨树林,其平均生产力达到年均气温0℃时的7倍以上,与所建单木生长模型的可比推算结果完全一致。结论: 本研究建立的人工杨树立木地上和地下生物量方程及其相容的生物量转换因子和根茎比模型,达到相关技术规定的预估精度要求,可以推广应用;温度是影响人工杨树生产力的重要因素,随着年均气温升高,人工杨树生产力也相应提高。

关键词: 生物量, 生产力, 哑变量, 误差变量, 联立方程组

Abstract:

Objective: Improving forest quality is one of the main tasks of China's forestry construction in the new period, and biomass and productivity are the two important indicators of forest quality. Poplar(Populus spp.)is the most planted broad-leaved tree species in China. Developing biomass models and analyzing impact of climate factors to productivity of planted poplar trees has an important practical significance. Method: Based on the mensuration data of above- and below-ground biomass from 450 and 147 destructive sample trees of planted poplar, respectively, collected from 15 provinces in China, one- and two-variable simultaneous biomass equations were developed using dummy variable modeling approach and error-in-variable simultaneous equation approach; and based on the paired data of diameter, height, and age of sample trees, individual tree growth models with climate factors were established. According to the individual tree diameter and height growth models and two-variable biomass equations, effects of climate factors on productivity of planted poplar trees were analyzed. In addition, based on the data of planted poplar plots of national forest inventory(NFI), the biomass and productivity of each plot were calculated, and linear regression model between productivity of planted poplar forests and climate factors was developed, which would verify the effects of climate factors on productivity of trees. Result: The coefficients of determination(R2)of one- and two-variable aboveground biomass equations for planted poplar trees developed in this study were above 0.90, and the mean prediction errors(MPEs)were within 5%; whereas the R2 of belowground biomass equations were above 0.83, and MPEs were within 10%. The R2 of individual tree diameter and height growth models with climate factors were above 0.70, and MPEs were within 5% and 3%, respectively. The diameter and height growth of planted poplar trees were significantly related with mean annual temperature(T). The diameter at breast height, tree height, and total biomass of a 20-years-old planted poplar tree on site for T=20℃ are 2.4, 2.4, and 9.5 times of those on site for T=0℃, respectively. The verification result using the data of NFI plots show that average productivity of poplar plantations can increase 2.5 t·hm-2a-1 with an increase of 10℃ for mean annual temperature, and the productivity of poplar plantation on site for T=20℃ is more than 7 times of that on site for T=0℃, which is consistent with the comparable results from developed growth models. Conclusion: The above- and below-ground biomass equations and the compatible biomass conversion factor and root-to-shoot ratio models developed for planted poplar trees in this study could meet the needs of precision requirements to relevant regulation, and could be used in application. Temperature is an important factor affecting the productivity of planted poplar trees. With the increase of mean annual temperature, the productivity of planted poplar trees increases accordingly.

Key words: biomass, productivity, dummy variable, error-in-variable, simultaneous equations

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