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黑龙江省红松人工林枝条分布数量模拟

郑杨,董利虎,李凤日*   

  1. (东北林业大学林学院, 哈尔滨 150040)
  • 出版日期:2016-07-18

Branch quantity distribution simulation for Pinus koraiensis plantation in Heilongjiang Province, China.

ZHENG Yang, DONG Li-hu, LI Feng-ri*   

  1. (School of Forestry, Northeast Forestry University, Harbin 150040, China).
  • Online:2016-07-18

摘要: 基于黑龙江省佳木斯市孟家岗林场的12块样地65株人工红松解析木的955个枝解析数据,以Poisson回归模型和负二项回归模型作为备选模型,构建了人工红松二级枝条数量分布模型,并采用AIC、Pseudo-R2、均方根误差(RMSE)和Vuong检验对模型的拟合优度进行比较.结果表明: 每轮一级枝条分布数量集中在3~5个,均值为4个,一级枝条分布数量与人工红松自身的枝条属性相关.一级标准枝上二级枝条分布的离散程度较大,利用全部子回归技术构建二级枝条分布数量模型,最终选择以负二项回归模型为基础的E(Y)=exp(β0+β1lnRDINC+β2RDINC2+β3HT/DBH+β4CL+β5DBH)作为二级枝条分布数量最优预测模型(β为参数;RDINC为相对着枝深度;HT为树高;DBH为胸径;CL为冠长).最优模型的Pseudo-R2为0.79,平均偏差接近于0,平均绝对偏差<7.对于所建立的模型,lnRDINCCL和DBH的参数为正值,RDINC2和HT/DBH的为负值,随着RDINC增大,在树冠内二级枝条分布数量存在最大值.总的来说,所建立的人工红松二级枝条分布数量模型的预测精度为96.4%,可以很好地预估该研究区域人工红松二级枝条分布数量,为以后枝条的光合作用和生物量的研究提供了理论基础.

关键词: 红松林, Poisson回归模型, 一级枝条分布, 二级枝条分布, 负二项回归模型

Abstract: Based on the measurement of 955 branch samples of 65 Korean pine (Pinus koraiensis) trees in 12 plots from Mengjiagang forest farm, Heilongjiang Province, and by using Poisson model and negative binomial model, the second-order branch count models for Korean pine were developed in this paper. AIC, PseudoR2, RMSE and Vuong test were selected to compare the goodnessoffit statistics of the models. The results indicated that the first-order branch count in a whorl was 3 to 5, with mean value of 4, and the firstorder branch count in a whorl for Korean pine plantation associated with its own characteristics. The secondorder branch count of the firstorder standard branch had a large discrete degree. All subset regression techniques were used to develop the second-order branch count model. The negative binomial regression model E(Y)=exp(β0+β1lnRDINC+β2RDINC2+β3HT/DBH+β4CL+β5DBH) was selected as the optimal second-order branch count model (β represented the parameter, RDINC represented the relative depth into crown from tree apex, HT represented the  total tree height, DBH represented the tree diameter at breast height, CL represented the crown length). PseudoR2 of the optimal model was 0.79, the mean error was close to 0 and the mean absolute error was less than 7. For the developed model, the parameter values of lnRDINC, CL and DBH were negative, and the parameter values of RDINC2 and HT/DBH were positive. With the increase of RDINC, the number of second-order branch had a peak value in the tree crown. On the whole, the precision of the second-order branch count model for Korean pine plantation was 96.4%, which would be suitable for predicting the secondorder branch count for the study area and provide a theoretic basis for branch photosynthesis and biomass research.

Key words: second-order branch distribution, Pinus koraiensis, negative binomial regression model., first-order branch distribution, Poisson regression model