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作 者:韦海航 韦铄星[1] 韩俊学 黄玲 黄彩船 WEI Haihang;WEI Shuoxing;HAN Junxue;HUANG Ling;HUANG Caichuan(Guangxi Forestry Research Institute/Guangxi Key Laboratory of Superior Timber Trees Resource Cultivation,Baise,Guangxi 533000,China;Guangxi State Owned Yachang Forest Farm,Baise,Guangxi 533000,China)
机构地区:[1]广西壮族自治区林业科学研究院/广西优良用材林资源培育重点实验室,广西百色533000 [2]广西国有雅长林场,广西百色533000
出 处:《热带农业科学》2022年第11期108-113,共6页Chinese Journal of Tropical Agriculture
基 金:广西优良用材林资源培育重点实验室开放课题(No.2020-A-04-04);广西林业科技项目(No.桂林科字[2016]第3号)。
摘 要:以雅长林场2019年森林资源二类调查数据为基础数据,借助Microsoft Office Excel软件,在全面分析雅长林场生态公益林资源结构特点的基础上,选取林分起源、立地类型、优势树种(组)、经营目的 4个因子为划分因子,开展雅长林场生态公益林经营类型划分研究。结果表明:雅长林场林公益林以天然林为主,林分质量偏低,林种结构单一,仅有水土保持林和水源涵养林2种,主要分布在“中山阳中”和“中山阴中”两种立地类型上,杂木、栎类和马尾松类为研究区生态公益林的三大优势树种(组);采用层次压缩法进行经营类型划分,将雅长林场生态公益林划分为29种经营类型,划分结果符合研究区生态公益林实际经营情况,划分方法简便且有效降低主观因素的影响。Based on the second-class survey data of forest resources in Yachang forest farm in 2019,,on the basis of a comprehensive analysis of the structural characteristics of ecological public welfare forest resources in Yachang forest farm, the forest origin, site type, dominant tree species(group), management purpose were selected as division factors to analyze the division of no-commercial forest management types in Yachang forest farm by Microsoft Office Excel software.The results showed that theno-commercial forest of Yachang forest farm were mainly natural forests, with low stand quality and single forest species structure. There were only two types of forests: soil and water conservation forests and water conservation forests, which were mainly distributed in two site types: “Zhongshan Yangzhong” and “Zhongshan Yinzhong”. Weeds, Quercus and masson pine were the three dominant tree species(groups) of no-commercial forest in the study area;, the no-commercial forest of Yachang forest farm was divided into 29 management types by hierarchical compression method. The classification results were in line with the actual management of no-commercial forest in the study area. The classification method was simple and could effectively reduce the influence of subjective factors.
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