摘要
基于浙江天目山国家级自然保护区常绿落叶阔叶混交林1 hm2样地调查数据,采用空间代替时间和点格局分析法,探究了交让木种群的结构特征、不同生长阶段的空间分布格局及其相互关系.结果表明:(1)交让木种群的径级结构大体呈倒J型,属增长型种群.(2)排除生境异质性影响,交让木幼苗、幼树、中树以及整个种群在1~3 m尺度上呈现微弱的均匀分布格局,其他尺度上呈现随机分布格局.(3)交让木中树与幼树之间基本呈微弱的负相关或无关联性;幼树与幼苗在小尺度区域内呈负相关,随空间尺度增大负相关性减弱至无关联性;中树与幼苗之间呈相对明显的负相关,JazenConnell假说可能是这种格局形成的主要原因.
Population structure and spatial pattern are important characteristics of plant community which can reveal ecological characteristics of a species. In this study, a plot covering 1 hm^2 was established in a subtropical evergreen and deciduous broad-leaved mixed forest in the Tianmu Mountain National Nature Reserve. All trees with a diameter at breast height of at least 1 cm were mapped and the species were identified. Point pattern analysis was applied to analyze the influence of environmental heterogeneity on tree spatial distribution and association. We focused on one of the dominant species Daphniphyllum macropodum at different growth stages (i. e. saplings, juvenile and mature trees). We found that: (1) in the plot, the diameter-class structure of the population present an invert J shape, belonging to a stable-growth type. (2) Saplings, juvenile and mature trees are weakly regularity patterns at small-scale (1-3 m) and random distribution patterns at large-scale if the environmental heterogeneity effect is eliminated by the null model of a Heterogeneous Poisson process (HP). (3) The association of juvenile and mature trees tends to show no correlation at all scales. There is a negative correlation between juvenile trees and saplings at small scales, but their association tends to no correlation at large scales. A significant negative correlation is found between mature trees and saplings at all scales, which is probably attributed to the Janzen-Connell effect.
出处
《浙江大学学报(理学版)》
CAS
CSCD
北大核心
2015年第1期47-53,64,共8页
Journal of Zhejiang University(Science Edition)
基金
浙江省财政厅
浙江省环保厅<浙江省生态环境10年变化(2000~2010年)遥感调查与评估>项目资助
关键词
天目山
交让木
生境异质性
点格局分析
空间关联性
Tianmu Mountain
Daphniphyllum macropodum
environmental heterogeneity
point pattern analysis
spatial association