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作 者:迟媛 郑皓 米文韬 任卫波 CHI Yuan;ZHENG Hao;MI Wentao;REN Weibo(School of Ecology and Environment,Inner Mongolia University,Hohhot 010021,China)
机构地区:[1]内蒙古大学生态与环境学院,内蒙古呼和浩特010021
出 处:《中国草地学报》2025年第2期21-29,共9页Chinese Journal of Grassland
基 金:内蒙古自治区科技计划项目(No.2021ZD00804,2022JBGS0040,2023JBGS0008,2023YFSH0025);内蒙古自治区教育厅高等院校创新团队项目(No.NMGIRT2316)。
摘 要:本研究以采自内蒙古自治区、山西省境内的59份野生百里香为对象,对其茎和叶的8个功能性状指标进行测定,采用描述性统计、相关性分析、主成分分析和聚类分析研究不同地区百里香功能性状差异及其与环境因子的关系,以期揭示野生百里香性状变异特征及其与环境的关系,为百里香资源保护与利用提供科学依据与参考。结果表明:百里香功能性状的整体变异程度较高,变异系数介于19.02%~63.67%。其中,茎节长的变异系数最大,叶长的变异系数最小。功能性状与环境因子具有显著相关性,茎长和海拔高度呈显著正相关,叶宽和纬度呈显著负相关。多个功能性状之间具有显著相关性,茎节数和叶数呈显著正相关,和茎节长呈显著负相关。8个功能性状可归为3个主成分因子,累计贡献率达82.01%。依据8个功能性状及经度、纬度进行聚类分析,59份百里香可划分为3个类群。This study examined 59 wild samples of Thymus mongolicus collected from Inner Mongolia Autonomous Region and Shanxi Province in China.By assessing eight functional traits of the stems and leaves,and employing descriptive statistics,correlation analysis,principal component analysis(PCA),and cluster analysis,we investigated the variations in functional traits among different regions and their relationship with environmental factors.The aim was to provide scientific basis and reference for the protection and utilization of T.mongolicus.The results revealed a high degree of overall variation in the functional traits of T.mongolicus,with coefficient of variation ranging from 19.02%to 63.67%.Notably,stem node length exhibited the highest coefficient of variation,whereas leaf length showed the lowest.Significant correlations observed between functional traits and environmental factors,specifically,stem length was positively correlated with altitude,and leaf width was negatively correlated with latitude.Furthermore,multiple functional traits were significantly correlated with each other,with stem node number positively correlated with leaf number and negatively correlated with stem node length.The eight functional traits could be grouped into three principal components,accounting for 82.01%of the total variance.Based on these functional traits,latitude,and longitude,cluster analysis classified the 59 samples into three distinct groups.
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