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Plant Diversity ›› 2011, Vol. 33 ›› Issue (3): 357-363.DOI: 10.3724/SP.J.1143.2011.10192

• 研究论文 • 上一篇    


 郎荣1、2, 许建初1, Timm Tennigkeit1, 杨雪飞1, 毕迎凤1、2   

  1. 1 中国科学院昆明植物研究所山地生态系统研究中心,云南 昆明650204;
    2 中国科学院研究生院,北京100049
  • 收稿日期:2010-11-05 出版日期:2011-06-25 发布日期:2011-01-20
  • 基金资助:


A Study of Stand Growth Model for Pinus yunnanensis (Pinaceae) Based on Plots Data——A Case Study in Yangliu Township, Baoshan, Yunnan Province

 LANG  Rong-1、2, XIU  Jian-Chu-1, Timm  Tennigkeit1, YANG  Xue-Fei-1, BI  Ying-Feng-1、2   

  1. 1 Centre for Mountain Ecosystem Studies, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650204, China;
    2 Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2010-11-05 Online:2011-06-25 Published:2011-01-20



关键词: 云南松, 林分生长模型, 非线性拟合


Pinus yunnanensis is one of most important timber species in Yunnan Province, and widely distributed in southwest China. Studies on growth model have been reported, however, most of which focused on a specific part of growth model. To build detailed, easily used and accurate empirical stand growth model from the same dataset, a case study was conducted in Yangliu Township, Baoshan, Yunnan Province. A total of 86 sample plots data were collected using two stages sampling design. Several popular non-linear growth functions were fitted and compared, including Chapman-Richards, Mitscherlich, Schumacher, Gompertz, Logistic, Korf and Allometric function. Models of site index, density index, average diameter at breast height (DBH) and stock volume growth model were fitted respectively. The different models performed more or less similarly in terms of coefficients of determination and root mean square error (RMSE). However, empirical growth function “Schumacher” had lower coefficient of variation for all parameters than other models. Schumacher function was the most suitable one for site index, average DBH and stock volume growth model in all alternative functions.

Key words: Pinus yunnanensis, Stand growth model, Nonlinear curve fitting