基于林木分级的大兴安岭天然兴安落叶松树高曲线研究  

Height curve of natural Larix gmelinii in the Daxing’anling Mountains of northeastern China based on forest classification

作　　者：董灵波[1] 邵威威 田栋元 刘兆刚[1] Dong Lingbo;Shao Weiwei;Tian Dongyuan;Liu Zhaogang(Key Laboratory of Sustainable Forest Ecosystem Management of Ministry of Education,School of Forestry,Northeast Forestry University,Harbin 150040,Heilongjiang,China)

机构地区：[1]东北林业大学林学院森林生态系统可持续经营教育部重点实验室,黑龙江哈尔滨150040

出　　处：《北京林业大学学报》2023年第5期88-96,共9页Journal of Beijing Forestry University

基　　金：国家重点研发计划课题(2022YFD2200502);中央高校基本科研业务费专项(2572022CG07);黑龙江头雁创新团队计划项目(森林资源高效培育技术研发团队)。

摘　　要：【目的】基于林木分级构建大兴安岭地区兴安落叶松的树高曲线模型,为该地区兴安落叶松的生长规律提供理论依据及森林可持续经营提供技术支撑。【方法】以大兴安岭地区翠岗林场56块固定样地数据为基础,根据单木相对直径(d)把林木分为了优势木、平均木、被压木3个等级,依据调整决定系数(R^(2)_(adj))最大、均方根误差(RMSE)和赤池信息量(AIC)最小的标准筛选出天然兴安落叶松各等级林木的最优树高曲线基础模型,并进一步评价和比较分位数回归和哑变量回归对兴安落叶松不同等级林木树高曲线模型模拟精度的影响。【结果】天然兴安落叶松树高曲线的最优基础模型均为Wykoff方程;当将林分分级哑变量同时添加在Wykoff方程的参数a和b上时,模型的拟合效果最好,其中兴安落叶松树高曲线模型的调整系数(R^(2)_(adj))、均方根误差(RMSE)和赤池信息量(AIC)分别为0.8588、1.6424和2081.902;兴安落叶松中的不同等级林木对应的最优分位数模型与林分整体无差别,均表现为中位数模型最优(即τ=0.5),其树高曲线的3个统计量则依次为0.8498、1.6938和2211.037。经过比较分析可知,以林木分级为哑变量的树高曲线模型拟合效果最好。【结论】含林木分级哑变量的大兴安岭兴安落叶松的树高曲线模型拟合效果优于基础模型,并且具有较好的预测精度和适应性,能反映不同林木等级下的树高、胸径的生长差异,可以为大兴安岭地区兴安落叶松的经营和生长预估提供理论依据。[Objective]The tree height curve of main tree species was established based on tree classification,which provided reference for studying the growth law of Larix gmelinii,and provided technical support for forest sustainable management in Daxing’anling Mountains of northeastern China.[Method]Based on the data of 56 fixed sample plots in Cuigang Forest farm of Daxing’anling Mountains,trees were divided into three grades of dominant,average and crushed trees according to the relative diameter(d)of individual trees.Based on the maximum adjusted coefficient(R^(2)_(adj)),minimum root mean square error(RMSE)and the minimum red pool information(AIC),the optimal tree height curve basic model of different grades of natural Larix gmelinii was screened out,and the effects of quantile regression and dummy variable regression on the simulation accuracy of tree height curve models of different grades of Larix gmelinii were further evaluated and compared.[Result]The optimal basic model of Larix gmelinii height curves was Wykoff equation.When the dumb variables of stand classification were added to parameters a and b of Wykoff equation,the model had the best fitting effect.R^(2)_(adj),RMSE and AIC of Larix gmelinii tree species curve model were 0.8588,1.6424 and 2081.902,respectively.There was no difference between the optimal quantile model and the whole stand of Larix gmelinii,and the median model was optimal(τ=0.5).The three statistics of height curve of the deciduous pine were 0.8498,1.6938 and 2211.037,respectively.Through comparative analysis,the tree height curve model with tree classification as dummy variable had the best fitting effect.[Conclusion]The height curve model of Larix gmelinii in the Daxing’anling Mountains,which contains dummy variables for tree classification,has better fitting performance than the basic model,and has good prediction accuracy and adaptability.It can reflect the growth differences of tree height and DBH under different tree grades,and can provide a theoretical basis for the management

关 键 词：林木分级 分位数回归 哑变量 树高曲线 

分 类 号：S791.222[农业科学—林木遗传育种] S750[农业科学—林学]