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干旱区地理 ›› 2019, Vol. 42 ›› Issue (3): 599-605.doi: 10.12118/j.issn.1000-6060.2019.03.16

• 生态与环境 • 上一篇    下一篇

雪岭云杉林叶片碳氮化学计量特征及其与土壤理化因子的关系

李晓菲1,2, 李 路1,2, 常亚鹏1,2, 许仲林1,2   

  1. 1 新疆大学资源与环境科学学院,新疆乌鲁木齐 8300462 新疆大学资源与环境科学学院绿洲生态教育部重点实验室,新疆 乌鲁木齐 830046

  • 收稿日期:2018-11-21 修回日期:2019-02-21 出版日期:2019-05-25 发布日期:2019-05-21
  • 通讯作者: 许仲林,男,博士,副教授,主要研究方向为GIS与环境建模. E-mail:galinwa@gmail.com
  • 作者简介:李晓菲(1992-),女,新疆博乐人,硕士研究生,主要方向为环境与气候建模. E-mail:lxf_0306@163.com
  • 基金资助:
    国家自然科学基金资助项目(4136109831500398);自治区研究生科研创新项目

Stoichiometric characteristics of leaf C and N and their correlation with soil physicochemical factors in Picea Schrenkiana forests

LI Xiaofei1,2, LI Lu1,2, CHANG Yapeng1,2, XU Zhonglin1,2   

  1. (1 College of Resource and Environmental Science,Xinjiang University,Urumqi  830046,Xinjiang,China;2 Key Laboratory of Oasis Ecology,College of Resource and Environmental Science,Xinjiang University,Urumqi  830046,Xinjiang,China)

  • Received:2018-11-21 Revised:2019-02-21 Online:2019-05-25 Published:2019-05-21

摘要:

碳(C)、氮(N)对于植物生长和生理调节机能意义重大。研究雪岭云杉林叶片CN化学计量特征随土壤理化因子的变化特征,对于认识森林生态系统的分布格局和未来变化趋势具有重要意义,为进一步探讨全球变化对植物的影响提供科学依据。以雪岭云杉林叶片为研究对象,利用统计分析探究叶片CN化学计量的变化特征,并利用冗余分析(Redundancy analysisRDA)技术对叶片CN化学计量特征与土壤理化因子的关系进行研究。研究结果表明,叶片C含量的平均值为465.28 g·kg-1,变异系数为14%;叶片N含量的平均值为6.54 g·kg-1,变异系数为42%;土壤C/N的平均值为90.63,变异系数为82%。冗余分析的结果表明,在0~30 cm层中,叶片CN化学计量特征主要受到土壤含水量和pH的驱动,土壤含水量与叶片C/N之间呈正相关关系,与叶片CN含量之间呈负相关关系;pH与叶片CN含量成正比,与C/N成反比;在30~80 cm层中,土壤含水量和土壤粘粒含量是影响叶片CN化学计量特征的主要因素,土壤含水量和叶片C/N之间呈正比,土壤粘粒含量与CN含量之间呈正比,与叶片C/N之间呈反比;pH、土壤CN含量对叶片CN化学计量特征的影响不显著。

关键词: 雪岭云杉林, 冗余分析, 化学计量特征, 理化因子

Abstract:

Carbon (C) and nitrogen (N) play important roles in plant growth and physiological functions.Study of the relationship between the C and N content in leaves of a plant and its environmental factors contributes to elucidating the supply of plant nutrients and plant growth in different environments which is of great significance to understand the distribution pattern of forest ecosystems and the trend of future changes,and even the response of plants to global change.This paper took the leaves of Picea schrenkianaSchrenks spruceforests and the corresponding soil of the trees as the study objects.With samples collected from the field,we retrieved the C and N contents in the leaves and analyzed different soil layers.Then we evaluated the variation of C and N stoichiometric characteristics through statistical analysis.Finallythe redundancy analysisRDAwas used to investigate the relationships between the stoichiometric characteristics of C and N from the leaves and the soil physicochemical factors.The results showed that the average concentrations of C and N in the leaf were 465.28 g·kg-1 and 6.54 g·kg-1 respectively,and the variation coefficient were 14% and 82% respectively.The RDA showed that in the soil layer from 0 to 30 cm the stoichiometric characteristics of C and N in the leaf were mainly affected by soil water content and its acidityalkalinity.For the soil water content,there was a positive correlation with the C/N ratio but a negative correlation with the C and N content in the leaf while for the acidityalkalinity of the soil,there was a positive correlation with C and N contents in the leaf but a negative correlation with the C/N ratio.In the soil layer from 30 to 80 cm,the stoichiometric characteristics of C and N in the leaf were mainly affected by soil water content and soil clay content.Specifically,for soil water content,there was a positive correlation with the C/N ratio.For soil clay content,there was a positive correlation with C and N contents but a negative correlation with the C/N ratio.Additionally,there were not significant relationships between pH and the C and N contents in the soil and the leafs C and N stoichiometric characteristics.The soil water content in different soil layers was related to the stoichiometric characteristics of C and N from the leaf,which indicated that the soil water content had certain effects on nutrient uptake by plants,and that was not related to the soil depth.

Key words: Picea schrenkiana forests, redundancy analysis, stoichiometric characteristics, physicochemical factor