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林业资源管理 ›› 2013, Vol. 0 ›› Issue (6): 70-75.

• 科学研究 • 上一篇    下一篇

长白山区人工红松林蓄积生长模型研究

孙世仁1, 苏东凯1, 谢小魁1,2, 杨明1, 赵月1, 唐宇1, 李斌1   

  1. 1.中国吉林森林工业集团有限责任公司,长春 130021;
    2.湖南农业大学 资源环境学院,长沙 410128
  • 收稿日期:2013-08-27 修回日期:2013-11-25 出版日期:2013-12-28 发布日期:2020-11-23
  • 通讯作者: 谢小魁(1979-),男,湖南岳阳人,讲师,主要从事森林生态系统模型以及景观生态教学和研究工作。Email:xiexiaokui@139.com
  • 作者简介:孙世仁(1958-),男,吉林桦甸人,高工,主要从事森林资源管理以及企业管理工作。Email:slzyjyb@163.com
  • 基金资助:
    林业公益性行业科研专项经费项目(201104070)

Volume Growth Models for Korean Pine Plantations in the Changbai Mountain Region of Northeast China

SUN Shiren1, SU Dongkai1, XIE Xiaokui1,2, YANG Ming1, ZHAO Yue1, TANG Yu1, LI Bin1   

  1. 1. Jilin Forest Industry Group Limited Liability Company,Changchun 130021,China;
    2. College of Resources & Environment,Hunan Agricultural University,Changsha 410128,China
  • Received:2013-08-27 Revised:2013-11-25 Online:2013-12-28 Published:2020-11-23

摘要: 基于吉林省长白山区1 078块人工红松林小班的森林资源规划设计调查数据,选用12种3参数的生长模型对蓄积生长进行模拟,并用决定系数R2、均方根误差RMSE对模型精度进行检验,最后以模型外推检验其生物学意义。结果表明:人工红松林经历“缓慢—旺盛—缓慢”的生长阶段; 理论生长方程Richards模型和Gompertz模型能较好地模拟这个过程,拟合精度较高,生物学意义较好;拟合的生长曲线呈现慢生树种典型的“S”形。对蓄积生长模型求导计算出连年生长量模型,表明人工红松林分在29a附近时蓄积连年生长量达到最大值。蓄积生长模型能较好地模拟长白山区人工红松林的生长过程,可为森林生长预测和经营优化提供参考依据。

关键词: 生长和收获模型, 林业数据库, 森林资源规划设计调查, 小班

Abstract: Twelve growth models with 3 parameters were used to simulate the volume of Korean pine plantations in the Changbai Mountain region of Northeast China.Data for model construction was based on forest resource planning and design inventory of 1078 subcompartments in Jilin Province.The functions with the highest correlation coefficient (R2)and lowest root mean square error (RMSE)were used to compare the different models,enabling biological significance to be assessed via extrapolation.Results revealed a pattern of “slow-strong-slow” growth for Korean pine.Models developed by Richards and Gompertz proved to be superior to others in simulating the Korean pine growth with higher accuracy and better biological significance,yielding growth curves displaying a typical “S” shape characteristics of slow-growing tree species.Annual increment model was got by derivation on volume growth model and it showed that the annual increment of Korean pine plantations reached the maximum near the age of 29a.The effectiveness of volume growth models at depicting the growth process of Korean pine plantations suggest their utility for predicting forest growth as an aid to optimal forest management in Changbai Mountain region.

Key words: growth and yield modeling, forestry database, forest resource planning, design and inventory, subcompartment

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