GC13B-1144
The spatial patterns of soil respiration regulated by biological and environmental variables along a precipitation gradient
Monday, 14 December 2015
Poster Hall (Moscone South)
Wenfang Xu1, Xianglan Li2, Wei Liu3, Linghao Li3, Longyu Hou4, Huiqiu Shi3, Jiangzhou Xia5, Dan Liu5, Haicheng Zhang5, Yang Chen5, Wenwen Cai5, Yang Fu5 and Wenping Yuan5, (1)CAREERI/CAS Cold and Arid Regions Environmental and Engineering Research Institute, Lanzhou, China, (2)Beijing Normal University, Haidian, Beijing, China, (3)Institute of Botany, The Chinese Academy of Sciences, State Key Laboratory of Vegetation and Environmental Change, beijing, China, (4)CAU China Agricultural University, Department of Grassland Science, Beijing, China, (5)Beijing Normal University, Beijing, China
Abstract:
Precipitation is a key environmental factor in determining ecosystem structure and function. Knowledge of how soil respiration responds to climate change (precipitation etc.) and human activities (grazing, clipping etc.) is crucial for assessing the impacts of climate change on terrestrial ecosystems and for improving model simulations and predictions of future global C cycling in response to human activities. In this study, we examined the spatial patterns of soil respiration along a precipitation gradient from 176.7 mm to 398.1 mm. Our results showed that soil respiration increased linearly with increasing mean annual precipitation. The increasing trend was similar to the trends of shoot biomass, litter biomass and soil total C content along the precipitation gradient. Root biomass was described by quadratic curves along the increasing precipitation gradient and may result from the tradeoff of environmental regulation and carbon allocation. Our results indicated that precipitation was the primary controlling factor in determining the spatial pattern of soil respiration. The linear/nonlinear relationships in this study describing the variations of the ecosystem carbon process with precipitation could be useful for model development, parameterization and validation at the regional scale to improve predictions of how the carbon process in grasslands responds to climate change, land use and grassland management.