Vertical distribution of soil carbon, nitrogen, and phosphorus in typical Chinese terrestrial ecosystems

被引:42
|
作者
Chai Hua [1 ,2 ]
Yu Guirui [1 ]
He Nianpeng [1 ]
Wen Ding [1 ]
Li Jie [2 ]
Fang Jiangping [2 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
[2] Tibet Univ, Agr & Anim Husb Coll, Linzhi 860000, Peoples R China
基金
中国国家自然科学基金;
关键词
soil profile; storage; stoichiometry; vertical distribution; China; LAND-USE; MANAGEMENT; DECOMPOSITION; GRASSLAND; PLANT; NUTRIENTS; RESPONSES; CLIMATE; TREES;
D O I
10.1007/s11769-015-0756-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Characterization of the vertical distribution of soil organic carbon (C), nitrogen (N), and phosphorus (P) may improve our ability to accurately estimate soil C, N, and P storage. Based on a database of 21 354 records in 74 long-term monitoring plots from 2004 to 2013 in the Chinese Ecosystem Research Network (CERN), we built fitting functions to quantify the vertical distribution of soil C, N, and P (up to 100 cm depth) in the typical Chinese terrestrial ecosystems. The decrease of soil C, N, and P content with depth can be well fitted with various mathematical functions. The fitting functions differed greatly between artificial (agriculture) and natural (desert, forest, and grassland) ecosystems, and also differed with respect to soil C, N, and P content. In both the artificial and natural ecosystems, the best fitting functions were exponential functions for C, quadratic functions for N, and quadratic functions for P. Furthermore, the stoichiometric ratios of soil C, N, and P were ranked in descending order: grassland > forest > agriculture > desert, and were also associated with climate. This study is the first to build the fitting functions for the profile distribution of soil C, N, and P in China at a national scale. Our findings provide a scientific basis to accurately assess the storage of C, N, and P in soils at a large scale, especially for the integrative analysis of historical data.
引用
收藏
页码:549 / 560
页数:12
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