Nitrogen storage in China's terrestrial ecosystems

被引:37
|
作者
Xu, Li [1 ]
He, Nianpeng [1 ,2 ]
Yu, Guirui [1 ,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] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
Nitrogen storage; Vegetation; Soil; Nitrogen cycle; China; SOIL ORGANIC-CARBON; GLOBAL PATTERNS; REACTIVE NITROGEN; SPATIAL-PATTERNS; LEAF; LIMITATION; ROOT; PRODUCTIVITY; RESPIRATION; TEMPERATURE;
D O I
10.1016/j.scitotenv.2019.136201
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Nitrogen (N) is an essential element for plant growth and ecosystem productivity. Accurate estimation of N storage in terrestrial ecosystems is crucial because it is one of the most important N pools in the earth system; however, the spatial patterns of N storage and the main influencing factors remain unclear due to the limited data available, particularly on the N content in plant organs. Here we systematically estimated the N storage in China for the first time using 44,337 field-measured data. The total N storage was 10.43 Pg N, with 0.29 Pg N in vegetation and 10.14 Pg N in soil (0-100 cm); of these, approximately 62.07% (0.18 Pg N) of the vegetation N was stored in active plant organs (leaf and root). Furthermore, N storage in the forest, grassland, wetland, and cropland ecosystems (excluding vegetation) was 3.74, 3.15, 0.24, and 1.93 Pg N, respectively. The spatial patterns of N density were different in vegetation and soil. Redundancy analysis showed that the main factor influencing the spatial patterns in vegetation was climate, whereas the main factors influencing the spatial patterns in soil were climate and soil nutrient. Our study clarified the N pools of each subsystem (particularly for plant organs) and revealed the main influencing factors. In addition, we compiled N density datasets for different plant organs and soil depths across various climatic regions in China, which could provide parameters for regional N cycle models or serve as a reference for regional N management. (C) 2019 Elsevier B.V. All rights reserved.
引用
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页数:11
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