摘要
【目的】选择7种模型拟合同一立地条件下马尾松和杉木人工林与天然林的树高生长曲线,并从中选出最优模型,为福建省马尾松和杉木人工林与天然林的合理经营奠定基础。【方法】基于福建省第7次森林资源一类清查数据,以同一立地条件下639株(人工林326株、天然林313株)马尾松标准木及687株(人工林498株、天然林189株)杉木标准木为研究对象,利用二次项方程、幂函数方程、对数方程、S曲线方程4种经验方程及Richards模型、Logistic模型、单分子式模型3种理论方程,拟合马尾松人工林和天然林、杉木人工林和天然林4种林分类型的树高曲线,并以调整决定系数、均方根误差、总相对误差和预估精度为评价指标,选择4种林分类型的最优树高模型。【结果】马尾松人工林与天然林分别以幂函数方程、二次项方程拟合效果较好,预估精度分别达到96.812%和96.474%;杉木人工林和天然林用Richards模型拟合效果最好,预估精度分别达到96.742%和96.495%。【结论】通过比较分析,获得了最适合模拟马尾松和杉木人工林与天然林的树高生长曲线模型。
[Objective] This study used 7 models to fit tree height growth curves of natural and artifi- cial Pinus massoniana Lamb and Cunningharnia lanceolata forest with the same site conditions to select the best fitting models and improve the rational management in Fujian. [Method] Based on the seventh for- est survey data,tree height curves were fitted with 639（326 artificial plants and 313 natural plants） stand- ard Pinus massoniana Lamb plants and 687 （498 artificial plants and 189 natural plants） standard Cun- ningharnia lanceolata plants using 4 empirical equations including Quadratic term curve,Power curve, Log- arithmic curve,and S curve, and 3 theoretical equations including Richards, Logistic, and Mitscherlicb. The optimal models were selected through an overall evaluation of adjusted determination coefficient,root mean square error, relative error and estimation accuracy. [Result] Power curve and Quadratic curve were best for artificial and natural Pinus massoniana Lamb plants with accuracies of 96. 812% and 96. 474% ,respectire. Richards model was the best for both artificial and natural Cunninghamia lanceolata plants with accu- racies of 96. 742% and 96. 495%, respectively. [Conclusion] Best fitting models for artificial and natural Pinus massoniana Lamb and Cunninghamia lanceolata plants were obtained.
出处
《西北农林科技大学学报（自然科学版）》
CSCD
北大核心
2014年第1期57-64,共8页
Journal of Northwest A&F University(Natural Science Edition)
基金
北京市教育委员会科学研究与科研基地建设项目(省部共建重点实验室)
国家"863"高技术研究发展计划项目(2012AA12A306)
关键词
马尾松
杉木
人工林
天然林
树高曲线
树高模型
Pinus massoniana Lamb
Cunninghamia lanceolata
plantations
natural forests
tree height curve
tree height models
