A Monte Carlo approach to estimate the uncertainty in soil CO2 emissions caused by spatial and sample size variability | |
Du, Sheng3; Ma, Ming-Guo1; Song, Yi4; Su, Li-Jun2; Shi, Wei-Yu3,4 | |
刊名 | ECOLOGY AND EVOLUTION |
2015-10-01 | |
卷号 | 5期号:19页码:4480-4491 |
关键词 | Maize Monte Carlo Approach Oasis Soil Respiration Uncertainty |
ISSN号 | 2045-7758 |
DOI | 10.1002/ece3.1729 |
文献子类 | Article |
英文摘要 | The soil CO2 emission is recognized as one of the largest fluxes in the global carbon cycle. Small errors in its estimation can result in large uncertainties and have important consequences for climate model predictions. Monte Carlo approach is efficient for estimating and reducing spatial scale sampling errors. However, that has not been used in soil CO2 emission studies. Here, soil respiration data from 51 PVC collars were measured within farmland cultivated by maize covering 25km(2) during the growing season. Based on Monte Carlo approach, optimal sample sizes of soil temperature, soil moisture, and soil CO2 emission were determined. And models of soil respiration can be effectively assessed: Soil temperature model is the most effective model to increasing accuracy among three models. The study demonstrated that Monte Carlo approach may improve soil respiration accuracy with limited sample size. That will be valuable for reducing uncertainties of global carbon cycle. |
WOS关键词 | Semiarid Loess Plateau ; Terrestrial Ecosystems ; Climate-change ; Respiration ; Temperature ; Efflux ; China ; Flux ; Transpiration ; Dependence |
WOS研究方向 | Environmental Sciences & Ecology |
语种 | 英语 |
出版者 | WILEY-BLACKWELL |
WOS记录号 | WOS:000362523300022 |
内容类型 | 期刊论文 |
源URL | [http://ir.ieecas.cn/handle/361006/9239] |
专题 | 地球环境研究所_生态环境研究室 |
通讯作者 | Shi, Wei-Yu |
作者单位 | 1.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Peoples R China 2.Xian Univ Technol, Sch Sci, Xian 710054, Shaanxi, Peoples R China 3.Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China 4.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Shaanxi, Peoples R China |
推荐引用方式 GB/T 7714 | Du, Sheng,Ma, Ming-Guo,Song, Yi,et al. A Monte Carlo approach to estimate the uncertainty in soil CO2 emissions caused by spatial and sample size variability[J]. ECOLOGY AND EVOLUTION,2015,5(19):4480-4491. |
APA | Du, Sheng,Ma, Ming-Guo,Song, Yi,Su, Li-Jun,&Shi, Wei-Yu.(2015).A Monte Carlo approach to estimate the uncertainty in soil CO2 emissions caused by spatial and sample size variability.ECOLOGY AND EVOLUTION,5(19),4480-4491. |
MLA | Du, Sheng,et al."A Monte Carlo approach to estimate the uncertainty in soil CO2 emissions caused by spatial and sample size variability".ECOLOGY AND EVOLUTION 5.19(2015):4480-4491. |
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