中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Improvement of predicting ecosystem productivity by modifying carbon-water-nitrogen coupling processes in a temperate grassland

文献类型:期刊论文

作者Cheng, Kai li1,6; Hu, Zhong min2,3; Li, Sheng gong1,6; Guo, Qun1,6; Hao, Yan bin4; Yuan, Wen ping2,5
刊名JOURNAL OF PLANT ECOLOGY
出版日期2021-02-01
卷号14期号:1页码:10-21
关键词gross primary productivity ecosystem model soil water content nitrogen constraint sensitivity grassland ecosystem
ISSN号1752-9921
DOI10.1093/jpe/rtaa072
通讯作者Hu, Zhong min(huzm@m.scnu.edu.cn) ; Li, Sheng gong(lisg@igsnrr.ac.cn)
英文摘要Aims Prediction of changes in ecosystem gross primary productivity (GPP) in response to climatic variability is a core mission in the field of global change ecology. However, it remains a big challenge for the model community to reproduce the interannual variation (IAV) of GPP in arid ecosystems. Accurate estimates of soil water content (SWC) and GPP sensitivity to SWC are the two most critical aspects for predicting the IAV of GPP in arid ecosystems. Methods We took a widely used model Biome-BGC as an example, to improve the model performances in a temperate grassland ecosystem. Firstly, we updated the estimation of SWC by modifying modules of evapotranspiration, SWC vertical profile and field capacity. Secondly, we modified the function of controlling water-nitrogen relation, which regulates the GPP-SWC sensitivity. Important Findings The original Biome-BGC overestimated the SWC and underestimated the IAV of GPP sensitivity, resulting in lower IAV of GPP than the observations, e.g. it largely underestimated the reduction of GPP in drought years. In comparison, the modified model accurately reproduced the observed seasonal and IAVs in SWC, especially in the surface layer. Simulated GPP-SWC sensitivity was also enhanced and became closer to the observations by optimizing parameter controlling nitrogen mineralization. Consequently, the model's capability of reproducing IAV of GPP has been largely improved by the modifications. Our results demonstrate that SWC in the surface layer and the consequent effects on nitrogen availability should be among the first considerations for accurate modeling IAV of GPP in arid ecosystems.
WOS关键词INTERANNUAL VARIABILITY ; SEMIARID ECOSYSTEMS ; MODEL PREDICTIONS ; USE EFFICIENCY ; TERRESTRIAL ; CLIMATE ; MINERALIZATION ; DYNAMICS ; FORESTS ; ABILITY
资助项目National Natural Science Foundation of China[31922053] ; National Key Research and Development Program of China[2017YFA0604801]
WOS研究方向Plant Sciences ; Environmental Sciences & Ecology ; Forestry
语种英语
WOS记录号WOS:000606831600002
出版者OXFORD UNIV PRESS
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/136667]  
专题中国科学院地理科学与资源研究所
通讯作者Hu, Zhong min; Li, Sheng gong
作者单位1.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China
2.Southern Marine Sci & Engn Guangdong Lab, Zhuhai 519082, Peoples R China
3.South China Normal Univ, Sch Geog, Shipai Campus, Guangzhou 510631, Peoples R China
4.Univ Chinese Acad Sci, Coll Life Sci, Beijing 100049, Peoples R China
5.Sun Yat Sen Univ, Sch Atmospher Sci, Guangzhou 519082, Peoples R China
6.Chinese Acad Sci, Synth Res Ctr Chinese Ecosyst Res Network, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Cheng, Kai li,Hu, Zhong min,Li, Sheng gong,et al. Improvement of predicting ecosystem productivity by modifying carbon-water-nitrogen coupling processes in a temperate grassland[J]. JOURNAL OF PLANT ECOLOGY,2021,14(1):10-21.
APA Cheng, Kai li,Hu, Zhong min,Li, Sheng gong,Guo, Qun,Hao, Yan bin,&Yuan, Wen ping.(2021).Improvement of predicting ecosystem productivity by modifying carbon-water-nitrogen coupling processes in a temperate grassland.JOURNAL OF PLANT ECOLOGY,14(1),10-21.
MLA Cheng, Kai li,et al."Improvement of predicting ecosystem productivity by modifying carbon-water-nitrogen coupling processes in a temperate grassland".JOURNAL OF PLANT ECOLOGY 14.1(2021):10-21.

入库方式: OAI收割

来源:地理科学与资源研究所

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