Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1038/s41467-020-16692-w |
Quantifying the drivers and predictability of seasonal changes in African fire | |
Yu, Yan1; Mao, Jiafu2,3; Thornton, Peter E.2,3; Notaro, Michael4; Wullschleger, Stan D.2,3; Shi, Xiaoying2,3; Hoffman, Forrest M.3,5,6; Wang, Yaoping7 | |
2020-06-09 | |
发表期刊 | NATURE COMMUNICATIONS
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ISSN | 2041-1723 |
出版年 | 2020 |
卷号 | 11期号:1 |
文章类型 | Article |
语种 | 英语 |
国家 | USA |
英文摘要 | Africa contains some of the most vulnerable ecosystems to fires. Successful seasonal prediction of fire activity over these fire-prone regions remains a challenge and relies heavily on in-depth understanding of various driving mechanisms underlying fire evolution. Here, we assess the seasonal environmental drivers and predictability of African fire using the analytical framework of Stepwise Generalized Equilibrium Feedback Assessment (SGEFA) and machine learning techniques (MLTs). The impacts of sea-surface temperature, soil moisture, and leaf area index are quantified and found to dominate the fire seasonal variability by regulating regional burning condition and fuel supply. Compared with previously-identified atmospheric and socioeconomic predictors, these slowly evolving oceanic and terrestrial predictors are further identified to determine the seasonal predictability of fire activity in Africa. Our combined SGEFA-MLT approach achieves skillful prediction of African fire one month in advance and can be generalized to provide seasonal estimates of regional and global fire risk. Fire is an important component of many African ecosystems, but prediction of fire activity is challenging. Here, the authors use a statistical framework to assess the seasonal environmental drivers of African fire, which allow for a better prediction of fire activity. |
领域 | 地球科学 ; 气候变化 ; 资源环境 |
收录类别 | SCI-E |
WOS记录号 | WOS:000542773600001 |
WOS关键词 | SATELLITE-OBSERVATIONS ; BURNED AREA ; EMISSIONS ; CLIMATE ; VARIABILITY ; FEEDBACKS ; RAINFALL ; IMPACTS ; TRENDS ; FOCUS |
WOS类目 | Multidisciplinary Sciences |
WOS研究方向 | Science & Technology - Other Topics |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/274420 |
专题 | 资源环境科学 |
作者单位 | 1.Princeton Univ, Atmospher & Ocean Sci Program, Princeton, NJ 08544 USA; 2.Oak Ridge Natl Lab, Div Environm Sci, POB 2008, Oak Ridge, TN 37831 USA; 3.Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN 37830 USA; 4.Univ Wisconsin, Nelson Inst Ctr Climat Res, Madison, WI USA; 5.Oak Ridge Natl Lab, Computat Sci & Engn Div, Oak Ridge, TN USA; 6.Univ Tennessee, Dept Civil & Environm Engn, Knoxville, TN USA; 7.Univ Tennessee, Inst Secure & Sustainable Environm, Knoxville, TN USA |
推荐引用方式 GB/T 7714 | Yu, Yan,Mao, Jiafu,Thornton, Peter E.,et al. Quantifying the drivers and predictability of seasonal changes in African fire[J]. NATURE COMMUNICATIONS,2020,11(1). |
APA | Yu, Yan.,Mao, Jiafu.,Thornton, Peter E..,Notaro, Michael.,Wullschleger, Stan D..,...&Wang, Yaoping.(2020).Quantifying the drivers and predictability of seasonal changes in African fire.NATURE COMMUNICATIONS,11(1). |
MLA | Yu, Yan,et al."Quantifying the drivers and predictability of seasonal changes in African fire".NATURE COMMUNICATIONS 11.1(2020). |
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