学术论文

      杉木不同龄组树冠形态模拟模型研究

      Simulation model of crown profile for Chinese fir (Cunninghamia lanceolata) in different age groups

      摘要:
      为了对杉木不同龄组树冠形态进行数学模拟,运用非线性回归筛选有效变量的方法将相对树冠半径( RCRj )和相对树冠长度( RCLj )确立为树冠形态模型的因变量和自变量。选取福建省顺昌县297株杉木标准木的1485个树冠半径测量值,基于8大类模型分别建立不同龄组的树冠最优模型。对最优模型进行误差和残差分析、模型检验、生物学意义评估,结果表明:幼龄林、中龄林和近成熟林时期拟合效果最优的模型分别是 Cubic、Poly4和GaussAmp。使用本文建立的树冠轮廓模型预估树冠形态时,只需测量全树高、最大树冠半径和最大树冠长度。树冠轮廓模型是生长和收获模型的重要组成部分,同时对于评价林木间的竞争、森林小气候和生物多样性也至关重要。
      Abstract:
      In order to model the crown profile by mathematical simulation for Chinese fir ( Cunninghamia lanceolata) in different age groups, this study utilized the nonlinear regression method to select the effective variables, i. e. the relative crown radius ( RCRj ) as the dependent variable and relative crown length ( RCLj ) as the independent variable for the crown profile model. Using data from 1 485 measurements of crown radius with 297 sample trees of Chinese fir at Shunchang County of Fujian Province, the optimal crown profile models in the different age groups were established based on 8 kinds of foundation models. The analysis of error and residual, model test and biological evaluation were carried out for the optimal crown profile models. Results showed that the optimal crown profile models of the young growth, half-mature, and near-mature and mature forests were the Cubic, Poly4 and GaussAmp, respectively. The crown profile models developed can be used to estimate the crown profile which only requires to measure the total tree height, the largest crown radius and length. Such models are important components of growth and yield models, and are also crucial for assessing the level of competition, forest microclimate and biodiversity.
      作者: 郭艳荣 [1] 吴保国 [1] 郑小贤 [2] 郑德祥 [3] 刘洋 [4] 董晨 [1] 张慕博 [5]
      Author: GUO Yan-rong [1] WU Bao-guo [1] ZHENG Xiao-xian [2] ZHENG De-xiang [3] LIU Yang [4] DONG Chen [1] ZHANG Mu-bo [5]
      作者单位: 北京林业大学信息学院 北京林业大学国家林业局森林资源与环境管理重点实验室 福建农林大学林学院 内蒙古农业大学林学院 中国林业科学研究院林业科技信息研究所
      刊 名: 北京林业大学学报 ISTICPKU
      年,卷(期): 2015, (2)
      分类号: S718.5
      在线出版日期: 2015年3月3日
      基金项目: 国家自然科学基金项目,“863”国家高技术研究发展计划项目(2012AA102003)。