Carbon and nitrogen dynamics of native <i>Leymus chinensis</i> grasslands along a 1000 km longitudinal precipitation gradient in northeastern China

• Main Authors: L. Ma, S. Yuan, C. Guo, R. Wang
• Format: Article
• Language: English
• Published: Copernicus Publications 2014-12-01
• Series: Biogeosciences
• Online Access: http://www.biogeosciences.net/11/7097/2014/bg-11-7097-2014.pdf

Understanding how ecosystem carbon (C) and nitrogen (N) cycles respond to the variability of precipitation can help us assess the effects of global climate change on terrestrial ecosystem structure and function. We investigated the contributions of aboveground biomass, litter, root, soil and microbial communities to ecosystem C and N processes at 14 sites along a 1000 km precipitation gradient in native <i>Leymus chinensis</i> grasslands of northeastern China. The results show that aboveground biomass C and N increased gradually, while no significant regional trends in litter and root biomass were found with increasing mean annual precipitation (MAP) along the gradient. Soil respiration increased first and then decreased from the dry to mesic sites, which could be ascribed to the relative changes in temperature, soil fungal : bacterial biomass and N availability. Surprisingly, N mineralization varied only slightly along the gradient, likely due to the decreases of soil organic matter quality (i.e., C : N). Stepwise regression models indicated regional soil C and N content positively correlated with MAP and clay content. Overall, C and N sequestration increased 3.2- and 1.8-fold with increasing MAP in terms of C and N storage in aboveground biomass, roots, litter and soil. It was concluded from the current study that regional precipitation variability strongly influences ecosystem C and N dynamics. The ecosystem C and N sequestration are primarily modulated by annual precipitation and soil texture, while the C and N turnover are largely controlled by microbial community composition, temperature and soil quality in <i>L. chinensis</i> grasslands across the large-scale precipitation gradient.