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林业科学 ›› 2011, Vol. 47 ›› Issue (3): 96-101.doi: 10.11707/j.1001-7488.20110315

• 论文 • 上一篇    下一篇

贵州省人工马尾松立木材积和地上生物量方程研建

曾伟生1, 夏忠胜2, 朱松2, 罗洪章2   

  1. 1. 中国林业科学研究院资源信息研究所 北京100091;2. 贵州省森林资源管理站 贵阳550001
  • 收稿日期:2010-09-25 修回日期:2010-10-20 出版日期:2011-03-25 发布日期:2011-03-25

Establishment of Tree Volume and Aboveground Biomass Equations for Masson Pine Plantation in Guizhou Province

Zeng Weisheng1, Xia Zhongsheng2, Zhu Song2, Luo Hongzhang2   

  1. 1. Research Institute of Forest Resources Information Techniques, CAF Beijing 100091;2. Forest Resources Administration Office of Guizhou Province Guiyang 550001
  • Received:2010-09-25 Revised:2010-10-20 Online:2011-03-25 Published:2011-03-25

摘要:

以贵州省人工马尾松样木的立木材积和地上生物量数据为基础,建立省级总体平均模型和以区域作为特定参数的哑变量模型及线性混合模型,并对中心区和一般区2类区域性模型与省级总体平均模型之间的差异进行对比分析和预估效果检验。结果表明: 对立木材积和地上生物量估计而言,区域特定的模型与总体平均模型之间以及哑变量模型和线性混合模型之间并没有显著差异。本文所建模型为贵州省马尾松人工林的蓄积量和生物量监测评估提供计量依据,所用方法为建立其他含特定参数的通用性模型提供可行途径。

关键词: 立木材积, 地上生物量, 哑变量模型, 线性混合模型, 通用性模型, 马尾松

Abstract:

Based on the tree volume and above-ground biomass data of Masson Pine (Pinus massoniana) plantation of Guizhou Province in China, population average models for province-level estimation and region-specific dummy variable models and linear mixed models were established at first. Secondly, the differences between two specific models for central region and other region and population average models were compared and analyzed, and the predictions of various models were conducted on fit data and validation data. The results showed that the region-specific models and population average models were not significantly different for tree volume and above-ground biomass estimation, and dummy variable models and linear mixed models were not significantly different too. The models constructed in this study would provide quantitative basis for monitoring and assessment of forest stock and biomass of Masson Pine plantation, and the method used here might provide a feasible approach to construct generalized models with specific parameters.

Key words: tree volume, above-ground biomass, dummy variable model, linear mixed model, generalized model, Pinus massoniana

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