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 F_s/F_eco (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