摘要
测定了来自不同地理种源和不同演替群落的四川大头茶(Gordoniaacuminata(Pritz)Chang)8个居群112株个体各50枚种子的10项形态指标,同时测定了各居群所在群落的4项环境指标;然后,通过主成分分析、主因子分析及聚类分析等数量分析方法研究了各形态指标和各环境指标的关系;结果表明:来自不同演替群落的四川大头茶居群间存在着极明显的种子形态分化,来自相同演替群落的居群间存在着极大的种子形态相似性;环境因子在四川大头茶居群种子形态分化过程中起着非常重要的作用;但不同的环境因子在不同居群的种子形态分化中所起的作用不同;群落演替类型对四川大头茶种子形态分化起非常重要作用的同时,地理种源却对该物种的种子形态分化影响不大.
At first we measured 10 kinds of seeds morphological indices in 112 individuals of 8 populations which collected from different geographical provenances and successiving communities.With the help of the multivariate techniques,E.G.Principal component analysis(PCA),Principal factor analysis(PFA),Clusterig analysis(CA),and WPGMA,We studied the morphological differentiation of seeds among populations and individuals of Godornia acuminata from different geographical and successiving communities.The Results reveals that: 1 The populations and individuals from the same type of successive communities show high similarities in seeds morphological characters,wihle populations and individuals from different successiving communities exhibit obvious dissimilarities.For example,there is stronger differentiation among populations and individuals from the pure Gordonia acuminata forest,the repencedrymion and evergreen broad leaved forest. 2 The geographical provenances have no stronger use in the progress of seeds morphological differentation.The populations which come from same geographical provenances take on scattering distribution,e.g.Xing Wen provenance and Jin Yun Mt.provenance. 3 The differentiation of seeds from every populations is assumed to be correleted with their distributive patterns,reproductive features,a well as enviromental factors,e.g.soil acid and pH,population altitude,soil types,soil organotrophes.
出处
《西南师范大学学报(自然科学版)》
CAS
CSCD
北大核心
1999年第2期207-213,共7页
Journal of Southwest China Normal University(Natural Science Edition)
基金
国家自然科学基金重点项目<植物种群适应机理>的子课题 !(批准号 :3 93 3 0 0 5 0 )
关键词
地理种源
演替群落
大头茶
种子形态分化
居群
geographical provenances
succession community
brassica juncea
seeds morphological differentiation
quantitative analysis
environment factors