AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (4.7 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Publishing Language: Chinese

Leaf phenotypic variation in natural populations of the Cunninghamia securinega at different altitudes

Gongliang XIE1, Gongxiu HE1, Jiaxiang LI1, Yamei GONG1, Sen LIU1, Ting CHANG1, Yongxiang TIAN2, Zhonghua ZHU3, Ninghua ZHU1( )
College of Forestry, Central South University of Forestry & Technology, Changsha 410004, Hunan, China
Xiaoxi National Nature Reserve Administration, Yongshun 416700, Hunan, China
Youxian Forestry Bureau, Youxian 412300, Hunan, China
Show Author Information

Abstract

Objective

To reveal the leaf phenotypic diversity and its variation pattern in the natural Cunninghamia securinega population at different altitude gradients, to study the correlation between leaf phenotypic traits and altitude climate, and to provide scientific basis for the collection, conservation and utilization of the C. securinega germplasm resources.

Method

Twelve leaf phenotypic traits from four natural C. securinega populations at different altitudes were investigated in Xiangxi National Nature Reserve, Hunan province by using nested ANOVA, correlation analysis, principal component analysis and cluster analysis.

Result

Except for leaf width, 11 leaf phenotypic traits were significantly (P < 0.05) or highly significantly (P < 0.01) different between and within populations, with rich variation; The overall variation in leaf phenotypes among natural populations showed a decreasing trend with increasing altitude, and the populations with the highest and lowest coefficients of variation were Pop1 (18.52%) and Pop4 (13.95%), respectively; The intra-population phenotypic differentiation coefficient (77.46%) was greater than the inter-population phenotypic differentiation coefficient (22.54%), indicating that intra-population variation was the main source of variation, and the degree of population differentiation was at a low to medium level. The correlation analysis showed that needle thickness, specific leaf area, and specific leaf mass showed highly significantly negative correlations with temperature (P < 0.001) and positive correlations with precipitation (P < 0.001) as elevation increased, which suggested that the needles of hemlock exhibit stress tolerance strategies in order to adapt to the environment. Using the Ward.D2 hierarchical clustering method to analyze the clustering of the C. securinega populations, the four natural populations of the C. securinega at different elevations could be divided into four taxa.

Conclusion

The overall leaf phenotypic diversity of the C. securinega population showed a decreasing trend with increasing altitude and was significantly correlated with the altitude-climate factors. The phenotypic variation between and within populations was rich, but intra-population variation was dominant.

CLC number: S722.5 Document code: A Article ID: 1673-923X(2024)05-0144-12

References

【1】
【1】
 
 
Journal of Central South University of Forestry & Technology
Pages 144-155

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
XIE G, HE G, LI J, et al. Leaf phenotypic variation in natural populations of the Cunninghamia securinega at different altitudes. Journal of Central South University of Forestry & Technology, 2024, 44(5): 144-155. https://doi.org/10.14067/j.cnki.1673-923x.2024.05.015

581

Views

3

Downloads

0

Crossref

4

CSCD

Received: 13 September 2023
Published: 25 May 2024
© 2024 Journal of Central South University of Forestry & Technology