大别山北麓壳斗科主要树种种子和叶片性状协同变化特征OA
The covariation characteristics of seed and leaf traits in major Fagaceae species on the northern slopes of the Dabie Mountains
[目的]通过分析壳斗科不同树种种子和叶片性状的差异,探究其协同变化特征,为种质资源的收集、保护和利用提供理论依据.[方法]以安徽省六安市大别山北麓 10 种壳斗科树种为研究对象,测定种子干质量、种型指数、蛋白质含量、淀粉含量、脂肪含量,以及叶片比叶面积、叶干物质含量、碳含量、氮含量和磷含量.采用聚类分析和主成分分析解析种子与叶片性状的协同变化特征,利用贝叶斯线性混合模型评估环境和物种对该协同变化的影响.[结果]10种壳斗科树种的种子和叶片性状存在显著种间差异,变异系数为 8.25%～69.55%.聚类分析和主成分分析表明种子与叶片性状具有协同变化特征.聚类分析将种子和叶片性状划分为两个类群.主成分分析结果显示,叶的磷含量、叶干物质含量、种子淀粉含量和叶的碳含量在第一主成分上载荷较高,方差贡献率为 32.5%;种子蛋白质含量、叶的氮含量和种子脂肪含量在第二主成分上载荷较高,方差贡献率为 21.8%;种子干质量、比叶面积和种型指数在第三主成分上载荷较高,方差贡献率为 17.7%.贝叶斯线性混合模型结果表明,环境对前 3个主成分的解释率分别为 25.6%、30.2%和 27.7%,物种的解释率分别为 43.7%、47.6%和 46.3%.[结论]壳斗科主要树种的种子与叶片性状存在显著的协同变化规律,物种和环境是驱动该协同特征的关键因子.
[Objective]By analyzing the differences in seed and leaf traits among different tree species of Fagaceae,this study explored the covariation characteristics of seed and leaf traits in Fagaceae,to provide a theo-retical basis for the collection,conservation and utilization of germplasm resources.[Method]Ten Fagaceae spe-cies distributed in the northern foot of the Dabie Mountains,Lu'an city,Anhui Province were selected as research materials.Seed traits including seed dry mass,seed aspect ratio,seed protein content,seed starch content and seed fat content,as well as leaf traits including specific leaf area,leaf dry matter content,leaf carbon content,leaf ni-trogen content,and leaf phosphorus content,were measured.Cluster analysis and principal component analysis(PCA)were used to reveal the coordinated variation characteristics of seed and leaf traits,and Bayesian linear mixed models were applied to quantify the effects of environment and species on their coordinated variation.[Result]There were significant interspecific differences in seed and leaf traits among the 10 Fagaceae species,with coefficients of variation ranging from 8.25%to 69.55%.Cluster analysis and PCA indicated coordinated variation between seed and leaf traits.Cluster analysis grouped these traits into two clusters.PCA results showed that leaf phosphorus content,leaf dry matter content,seed starch content,and leaf carbon content loaded on the first principal component,with a variance contribution rate of 32.5%;seed protein content,leaf nitrogen content,and seed fat content loaded on the second principal component,with a variance contribution rate of 21.8%;and seed dry weight,specific leaf area,and seed shape index loaded on the third principal component,with a variance contribution rate of 17.7%.Bayesian linear mixed models revealed that the explanatory power of environment for the three prin-cipal components was 25.6%,30.2%,and 27.7%,respectively,while that of species was 43.7%,47.6%,and 46.3%,respectively.[Conclusion]Significant covariation patterns exist between seed and leaf traits of the 10 Fagaceae spe-cies,and species and environment are the key factors driving this covariation.
黄兴召;王思睿;杨莲康;韩晴;万芳芳;欧强新
安徽农业大学林学与园林学院,安徽省林木资源培育重点实验室,安徽 合肥 230036安徽农业大学林学与园林学院,安徽省林木资源培育重点实验室,安徽 合肥 230036安徽农业大学林学与园林学院,安徽省林木资源培育重点实验室,安徽 合肥 230036安徽农业大学林学与园林学院,安徽省林木资源培育重点实验室,安徽 合肥 230036安徽农业大学林学与园林学院,安徽省林木资源培育重点实验室,安徽 合肥 230036安徽农业大学林学与园林学院,安徽省林木资源培育重点实验室,安徽 合肥 230036
农业科技
壳斗科叶片性状种子性状协同变化贝叶斯混合模型
Fagaceaeleaf traitsseed traitssynergistic variationBayesian mixture model
《安徽农业大学学报》 2026 (4)
565-572,8
中国工程院战略研究与咨询项目(2024-DFZD-64)安徽省大学生创新创业训练计划项目(S202510364123)国家重点研发项目(2023YFD2200900)安徽省林草种质资源设施保存库种质收集与保存(2025BFAFN00700-2)
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