文献类型：期刊文献

英文题名：Simulation of soil nitrogen storage of the typical steppe with the DNDC model: A case study in Inner Mongolia, China

作者：Li, R. H.[1,2,3] Li, X. B.[1,3] Li, G. Q.[4] Wen, W. Y.[5]

第一作者：Li, R. H.

通信作者：Li, XB[1]

机构：[1]Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China;[2]Henan Polytech Univ, Sch Surveying & Land Informat Engn, Jiaozuo 454000, Peoples R China;[3]Beijing Normal Univ, Coll Resources Sci & Technol, Beijing 100875, Peoples R China;[4]Ludong Univ, Inst Geog & Planning, Yantai 264025, Peoples R China;[5]Chinese Acad Forestry, Inst Wetland Res, Beijing 100090, Peoples R China

年份：2014

卷号：41

起止页码：155-164

外文期刊名：ECOLOGICAL INDICATORS

收录：;EI(收录号：20141217474705);Scopus(收录号：2-s2.0-84896745097);WOS:【SCI-EXPANDED(收录号:WOS:000334822200018)】；

基金：Our research is sponsored by the Major Basic Research Development Program of China (973 Program, Grant No. 2014CB138803), the Key Projects of National Natural Science Foundation of China (41030535), the Free Inquiry Project of State Key Laboratory of Earth Surface Processes and Resource Ecology (2011-TDZY-102), and National Natural Science Foundation of China (41371524). We thank Changsheng Li for his provision of DNDC model. We thank Jianjun Qiu, Liangxin Fan, Ligang Wang, Jia Deng, Hu Li and Zhao Zhang for their assistance in using the DNDC model. We are grateful for the proofreading of Roland Achtziger and the detailed comments of the two anonymous referees.

语种：英文

外文关键词：DNDC; Remote sensing; Soil N storage; Steppe; Inner Mongolia

摘要：Soil nutrient depletion is one of the characteristics of steppe degradation. Soil nitrogen (N) storage is an indicator of ecosystem productivity, and its simulation is necessary to monitor steppe degradation and for recovery measures. The study presents a simulation framework of soil N storage by integrating a denitrification-decomposition (DNDC) ecosystem model-based simulation and multi-source remote sensing data-based inversion. The DNDC model is a key player in the framework, whereas remote sensing prepares the input parameters and verification data. To run a DNDC model spatially, climate, soil, and vegetation databases were built, and land use, slop, grazing, and mowing parameters were formulated by remote sensing inversion. A soil N storage prediction model was established with the maximum of normalized difference vegetation index (NDVI) to provide comparable results with the simulation of soil N storage with the DNDC model. The results indicate that soil N storage declined from east to west throughout the study area. From 1990 to 2011. no change in the spatial distribution of soil N storage was determined, and the spatial heterogeneity of soil N storage decreased with its increase in the low-N area and decrease in the high-N area. A significant correlation (P < 0.01) was determined between soil N storage data detected by remote sensing inversion and that simulated with DNDC, and both estimation results of soil N storage matched well. Soil N storage simulated with the DNDC model was more sensitive to soil organic carbon (SOC), bulk density, pH and N fixation index than other parameters, and using the most sensitive factor (MSF) method, the range of annual mean soil N storage was determined to be between 2339.61 and 5484.61 kg ha(-1). The variation in regional soil N storage in a typical steppe in Inner Mongolia, China can therefore be simulated using the DNDC model with support from remote sensing. (C) 2014 Elsevier Ltd. All rights reserved.