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云龙天池云南松自然种群分布格局分析
引用本文:黄小波,李帅锋,苏建荣,刘万德,郎学东.云龙天池云南松自然种群分布格局分析[J].林业科学研究,2018,31(4):47-52.
作者姓名:黄小波  李帅锋  苏建荣  刘万德  郎学东
作者单位:中国林业科学研究院资源昆虫研究所云南普洱森林生态系统国家定位观测研究站
基金项目:中国林科院基本科研业务费专项(CAFYBB2017ZX002)和林业公益性行业专项(201404211)
摘    要:目的]对云南松种群年龄结构和空间分布格局的变化以及不同生长阶段个体的空间分布格局及空间关联性进行了研究,从空间格局角度深入认识云南松林群落结构和分布格局及其形成的内在机制。方法]基于云南省云龙县天池自然保护区云南松天然林的样地调查数据,基于云南松的种群径级结构,采用Ripley’s L函数点格局方法,对云南松自然种群的龄级结构、空间分布格局及其不同生长阶段空间关联性进行了系统分析。结果]云南松自然种群径级和高度级结构完整,分布呈倒"J"型;云南松自然种群整体上在0 40 m的空间尺度上呈"聚集-随机"的分布格局;云南松自然种群个体在幼树和小树阶段,在较大的尺度上呈聚集分布,随着尺度的增加转变为随机分布,而在中树阶段完全呈聚集分布,随着龄级的递增,大树阶段的空间分布格局呈随机分布;云南松自然种群不同生长阶段个体间空间关联在所有尺度上基本都呈显著正相关。结论]云南松自然种群结构属增长型种群;云南松自然种群不同生长阶段的个体呈现不同的分布格局,表现出强烈的空间动态特性;云南松种群各生长阶段间正向的关系,有利于种群的维持。

关 键 词:云南松  种群结构  点格局分析  空间分布  空间关联性
收稿时间:2017/12/25 0:00:00

Distribution of Pinus yunnanensis Natural Population in Yunlong Tianchi National Nature Reserve
HUANG Xiao-bo,LI Shuai-feng,SU Jian-rong,LIU Wan-de and LANG Xue-dong.Distribution of Pinus yunnanensis Natural Population in Yunlong Tianchi National Nature Reserve[J].Forest Research,2018,31(4):47-52.
Authors:HUANG Xiao-bo  LI Shuai-feng  SU Jian-rong  LIU Wan-de and LANG Xue-dong
Institution:Research Institute of Resource Insects, Chinese Academy of Forestry, the Pu''er Forest Ecosystem Research Station, State Forestry Administration, Kunming 650224, Yunnan, China,Research Institute of Resource Insects, Chinese Academy of Forestry, the Pu''er Forest Ecosystem Research Station, State Forestry Administration, Kunming 650224, Yunnan, China,Research Institute of Resource Insects, Chinese Academy of Forestry, the Pu''er Forest Ecosystem Research Station, State Forestry Administration, Kunming 650224, Yunnan, China,Research Institute of Resource Insects, Chinese Academy of Forestry, the Pu''er Forest Ecosystem Research Station, State Forestry Administration, Kunming 650224, Yunnan, China and Research Institute of Resource Insects, Chinese Academy of Forestry, the Pu''er Forest Ecosystem Research Station, State Forestry Administration, Kunming 650224, Yunnan, China
Abstract:Objective] To study the variations of age structure and spatial distribution pattern of Pinus yunnanensis forest as well as the spatial distribution pattern and spatial association of individuals in different growth stages, so as to further understand the intrinsic mechanism of the P. yunnanensis population structure and distribution pattern and its formation from the view point of spatial pattern.Method] This study is based on data from sampling plots of P. yunnanensis natural population in Tianchi Nature Reserve of Yunlong County, Yunnan Province. The method of substituting space for time and Ripley''s L function (based on the derivatives of Ripley''s K function) was used to analyze the structure, spatial distribution patterns and spatial association at different growth stages under different scales of a P. yunnanensis natural forest population.Result] The results showed that the DBH class and height class structure of P. yunnanensis natural population were complete, presented an invert J shape. With the scale increased, the distribution of P. yunnanensis natural population presented an "aggregate-random" type. At juvenile and small tree stages, the spatial distribution pattern presented an aggregate distribution at large scales, transformed into a random distribution with the scale increased. At medium tree stage, the spatial distribution pattern presented an aggregate distribution. To the stage of large tree, the spatial distribution pattern presented a random distribution. The different growth stages of P. yunnanensis natural population was significantly positively correlated at all scales.Conclusion] The structure of P. yunnanensis natural population belonged to a increasing type. P. yunnanensis natural population at different growth stages presents different distribution pattern, indicating a strong spatial dynamic characteristic. The positive relationship between the growth stages of P. yunnanensis natural population has the advantage for population maintenance.
Keywords:Pinus yunnanensis  population structure  point pattern analysis  spatial distribution  spatial association
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