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应用生态学报 ›› 2024, Vol. 35 ›› Issue (4): 877-885.doi: 10.13287/j.1001-9332.202404.013

• 稳定同位素生态学专栏 • 上一篇    下一篇

青藏高原东缘不同植被类型下草本植物叶片碳氮稳定同位素差异及其驱动因素

陈淼1,2, 刘顺1,2, 许格希1,2, 陈健1,2, 邢红爽1,2, 李非凡1,2, 张淼淼1,2, 曹向文1,2, 史作民1,2,3*   

  1. 1中国林业科学研究院森林生态环境与自然保护研究所, 国家林业和草原局森林生态环境重点实验室, 北京 100091;
    2四川米亚罗森林生态系统国家定位观测研究站, 四川理县 623100;
    3南京林业大学南方现代林业协同创新中心, 南京210037
  • 收稿日期:2023-07-03 接受日期:2024-02-22 出版日期:2024-04-18 发布日期:2024-10-18
  • 通讯作者: * E-mail: shizm@caf.ac.cn
  • 作者简介:陈淼, 男, 1991年生, 博士研究生。主要从事碳氮稳定同位素生态学研究。E-mail: chenmiaocc@163.com
  • 基金资助:
    中央级公益性科研院所基本科研业务费专项(CAFYBB2021ZA002-2,CAFYBB2022QC002,CAFYBB2022SY021)和国家重点研发计划项目(2021YFD2200405)

Differences and drivers of leaf stable carbon and nitrogen isotope in herbs under different vegetation types on the eastern Qinghai-Tibet Plateau

CHEN Miao1,2, LIU Shun1,2, XU Gexi1,2, CHEN Jian1,2, XING Hongshuang1,2, LI Feifan1,2, ZHANG Miaomiao1,2, CAO Xiangwen1,2, SHI Zuomin1,2,3*   

  1. 1Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China;
    2Sichuan Miyaluo Forest Ecosystem National Observation and Research Station, Lixian 623100, Sichuan, China;
    3Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
  • Received:2023-07-03 Accepted:2024-02-22 Online:2024-04-18 Published:2024-10-18

摘要: 植物叶片碳氮稳定同位素自然丰度(δ13C和δ15N)可以提供植物生理生态过程的综合信息,已广泛应用于生态学研究。然而,目前对叶片δ13C和δ15N的研究主要集中于木本植物,对不同植被类型下草本植物叶片δ13C和δ15N的研究相对较少,其碳氮稳定同位素差异和驱动因素尚不明确。本研究以青藏高原东缘亚高山针叶林、高山灌丛和高山草甸中草本植物叶片为对象,研究了不同植被类型下草本植物叶片δ13C和δ15N的差异及其驱动因素。结果表明: 不同植被类型下草本植物叶片δ13C和δ15N值存在显著差异,高山草甸中草本植物叶片δ13C和δ15N值最高,高山灌丛次之,亚高山针叶林最低。方差分解发现,不同植被类型下草本植物叶片δ13C和δ15N的差异是由叶片功能性状和气候因子共同驱动的,其中叶片功能性状的相对贡献超过了气候因子。层次分割法分解广义混合效应模型发现,年均温度(MAT)、叶绿素指数、单位面积叶片氮含量(Narea)和比叶重是不同植被类型下草本植物叶片δ13C差异的主要驱动因素,而Narea和MAT对不同植被类型下草本植物叶片δ15N变异的相对重要性远高于其他变量。此外,使用最小二乘回归分析发现,不同植被类型下草本植物叶片δ13C与δ15N之间存在强烈耦合关系。本研究结果为理解不同植被类型下草本植物叶片δ13C和δ15N差异的关键驱动因素提供了新的见解。

关键词: 草本植物, 碳稳定同位素, 氮稳定同位素, 叶片功能性状, 气候因子

Abstract: The natural abundance of stable carbon and nitrogen isotopes (δ13C and δ15N) in leaves can provide comprehensive information on the physiological and ecological processes of plants and has been widely used in ecological research. However, recent studies on leaf δ13C and δ15N have focused mainly on woody species, few studies have been conducted on herbs in different vegetation types, and their differences and driving factors are still unclear. In this study, we focused on the herbs in subalpine coniferous forests, alpine shrublands, and alpine mea-dows on the eastern Qinghai-Tibet Plateau, and investigated the differences in leaf δ13C and δ15N of herbs and the driving factors. The results showed that there were significant differences in leaf δ13C and δ15N values of herbs among different vegetation types, with the highest δ13C and δ15N values in alpine meadows, followed by alpine shrublands, and the lowest in subalpine coniferous forests. Using variation partitioning analysis, we revealed that differences in leaf δ13C and δ15N of herbs among various vegetation types were driven by both leaf functional traits and climate factors, with the contribution of leaf functional traits being relatively higher than that of climate factors. Hierarchical partitioning results indicated that mean annual temperature (MAT), chlorophyll content index, leaf nitrogen content per unit area (Narea), and leaf mass per area were the main drivers of leaf δ13C variations of herbs across different vegetation types, while the relative importance of Narea and MAT for variation in leaf δ15N of herbs was much higher than those other variables. There was a strong coupling relationship between leaf δ13C and δ15N as indicated by the result of the ordinary least squares regression. Our findings could provide new insights into understanding the key drivers of leaf δ13C and δ15N variations in herbs across different vegetation types.

Key words: herbs, carbon stable isotope, nitrogen stable isotope, leaf functional trait, climatic factor