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Acta Prataculturae Sinica ›› 2020, Vol. 29 ›› Issue (6): 56-70.DOI: 10.11686/cyxb2019424

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Application of 13C stable isotope labeling in the partitioning of ecosystem respiration in a Leymus chinensis steppe in Inner Mongolia, China

LI Ru-xia1,2, GENG Yuan-bo1,*   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-09-29 Revised:2019-11-25 Online:2020-06-20 Published:2020-06-20

Abstract: Grassland ecosystem respiration, of which the main components are soil respiration and aboveground plant respiration, plays an important role in the global carbon cycle and climate change. Also, different ecosystem respiratory components have different response mechanisms to environmental changes. In order to explore the contribution of grassland respiration to greenhouse gas emissions, we used a 13C natural stable isotope labeling method and a 13C pulse labeling method, combined with the static chamber-Keeling plot method, to distinguish the components of grassland ecosystem respiration in Leymus chinensis steppe. The research was conducted in the Xilin River Basin of Inner Mongolia and we then evaluated the two stable isotope methods according to partitioning results. It was found that: 1) 13C natural labeling and 13C pulse labeling methods gave significantly similar results when samples were from the same habitat, as defined by soil temperature and soil water content. Thus, the partitioning results obtained by the two methods are comparable. 2) Compared with the 13C natural labeling method, the pulse labeling method significantly improved the δ13C value of ecosystem respiration, soil respiration and above-ground plant respiration (P<0.05). 3) The partitioning results of the 13C natural labeling method and the 13C pulse labeling method expressed by Fs/Feco (ratio of soil respiration flux to ecosystem respiratory flux), were (75.2±4.3)% and (73.8±2.9)%, respectively, in 2011, and (89.2±2.0)% and (89.1±1.4)% in 2012. The statistical analysis indicated that there was no significant difference between partitioning results of the 13C natural labeling method and the 13C pulse labeling method in different years (2011: P=0.567; 2012: P=0.674). These results imply that under natural conditions, the potential differences among δ13C in ecosystem respiration components were enough to differentiate ecosystem respiration. This discovery can improve the efficiency of ecosystem respiration partitioning research using the isotope labeling method. Further, this information will facilitate more insightful study of the ecosystem carbon cycle process.

Key words: 13C natural labeling method, 13C pulse labeling method, Keeling plot, partitioning of ecosystem respiration, Leymus chinensis steppe