| 鹅掌楸天然林物种组成与林分空间结构特征研究 |
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| 引用本文： | 薛卫星,郭秋菊,艾训儒,姚兰,朱江,黄阳祥,李玮宜,罗西,刘毅. 鹅掌楸天然林物种组成与林分空间结构特征研究[J]. 林业科学研究, 2021, 34(2): 166-173. DOI: 10.13275/j.cnki.lykxyj.2021.02.018 |
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| 作者姓名： | 薛卫星 郭秋菊 艾训儒 姚兰 朱江 黄阳祥 李玮宜 罗西 刘毅 |
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| 作者单位： | 1.湖北民族大学生物资源保护与利用湖北省重点实验室，湖北 恩施 445000;2.湖北民族大学林学园艺学院，湖北 恩施 445000;3.湖北星斗山国家级自然保护区管理局，湖北 恩施 445000 |
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| 基金项目： | 生态环境部生物多样性调查、观测与评估项目;博士启动基金;生物资源保护与利用湖北省重点实验室开放基金;恩施州特色植物资源种质工程技术研究中心建设项目 |
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| 摘 要： | 目的 以湖北省恩施土家族苗族自治州鹤峰县鹅掌楸（Liriodendron chinense）天然林为研究对象，通过分析其物种组成与林分空间结构，直观、精准的描述其林分结构特征，为我国珍稀植物鹅掌楸的可持续经营提供理论依据。 方法 在两个鹅掌楸典型分布区域共建立40个20 m × 20 m调查样地，进行每木定位与检尺调查，利用Winkelmass软件与R 3.5.1计算胸径（DBH） ≥ 5 cm的林木个体的角尺度（W）、大小比（U）、混交度（M）与密集度（C），分析其一元分布、二元分布及四元分布特征。 结果 群落中物种总计251种，其中乔木88种、灌木61种、草本77种、木质藤本25种，隶属于76科172属，鹅掌楸为该群落的优势种群，但优势不明显。鹅掌楸天然林林分角尺度均值为0.566，整体呈现轻微团状分布，林木生长处于中庸状态（U = 0.508），各树种呈现高度混交状态（M = 0.742），林分郁闭度较高，密集度均值为0.865。角尺度对大小比数、混交度与密集度均有一定影响，且林木混交状态与林分密集程度呈现相互促进的状态。 结论 研究区鹅掌楸天然林各树种高度混交，正处于森林自然演替的中后期阶段。森林经营过程中应调整林木个体之间的竞争关系，减少同种聚集现象，选择性地伐除处于绝对劣势且弱度混交的林木个体，改善林内环境，增加林下光照，促进鹅掌楸天然更新，以维持森林结构的稳定与可持续发展。
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| 关 键 词： | 林分空间结构 物种组成 一元分布 二元分布 四元分布 |
| 收稿时间： | 2020-05-28 |
Community Composition and Stand Spatial Structure of Liriodendron chinense Natural Forest |
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| XUE Wei-xing,GUO Qiu-ju,AI Xun-ru,YAO Lan,ZHU Jiang,HUANG Yang-xiang,LI Wei-yi,LUO Xi,LIU Yi. Community Composition and Stand Spatial Structure of Liriodendron chinense Natural Forest[J]. Forest Research, 2021, 34(2): 166-173. DOI: 10.13275/j.cnki.lykxyj.2021.02.018 |
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| Authors: | XUE Wei-xing GUO Qiu-ju AI Xun-ru YAO Lan ZHU Jiang HUANG Yang-xiang LI Wei-yi LUO Xi LIU Yi |
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| Affiliation: | 1. Key Laboratory of Biological Resources Protection and Utilization of Hubei Province, Hubei Minzu University, Enshi 445000, Hubei, China;2. School of Forestry and Horticulture, Hubei Minzu University, Enshi 445000, Hubei, China;3. Bureau of Xingdoushan National Nature Reserve, Enshi 445000, Hubei, China |
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| Abstract: | Objective Taking Liriodendron chinense natural forest in Hefeng county, Enshi Tujia and Miao Autonomous Prefecture, Hubei Province as the research object, to analyze the species composition and stand space structure were analyzed, and describe the forest structure characteristics of L. chinense. Method Forty L. chinense plots of 20 m × 20 m were established in two typical distribution areas, respectively, each tree in the plots was positioned and measured. The Winkelmass software and R 3.5.1 were used to calculate the uniform angle index (W), dominance (U), mingling (M) and crowding degree (C) for trees with DBH ≥ 5 cm, the distribution of univariate distribution, the bivariate distribution and quadrivariate distribution characteristics were presented and analyzed. Result There were a total of 251 species in the L. chinense community, including 88 species of trees, 61 species of shrubs, 77 species of herbs and 25 species of woody lianas, belonging to 172 genera of 76 families. L. chinense population was the dominant population in the community, but the dominance was not obvious. The uniform angle index of the L. chinense natural forest was 0.566, and the overall distribution was slightly aggregated. The tree growth was in a neutral state (U = 0.508), the tree species were in a highly mixed state (M = 0.742), the stand density was high, and the mean crowding degree was 0.865. The uniform angle index had a certain influence on the dominance, mingling and crowding degree, and the mixing state and stand density were mutually promoting. Conclusion The species of L. chinense natural forest in the study area are highly mixed and estimated during the middle and late stage of natural forest succession. The competition relationships between individual trees should be adjusted in the process of forest management, in order to maintain the stability and sustainable development of the forest structure. It is necessary to reduce the phenomenon of the aggregation of same species, to selectively remove individual trees at absolute disadvantage and weak mixed degree, so as to improve the forest environment, and promote natural regeneration. |
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| Keywords: | spatial structure species composition univariate distribution bivariate distribution quadrivariate distribution |
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