Research challenges and opportunities for using big data in global change biology
文献类型：期刊论文
| 作者 | Xia, Jianyang3; Wang, Jing1,3 ; Niu, Shuli2,4
|
| 刊名 | GLOBAL CHANGE BIOLOGY
 |
| 出版日期 | 2020-09-13 |
| 页码 | 22 |
| ISSN号 | 1354-1013 |
| 关键词 | big data Earth system model global change biology machine learning model uncertainty |
| DOI | 10.1111/gcb.15317 |
| 通讯作者 | Xia, Jianyang(jyxia@des.ecnu.edu.cn) |
| 英文摘要 | Global change biology has been entering a big data era due to the vast increase in availability of both environmental and biological data. Big data refers to large data volume, complex data sets, and multiple data sources. The recent use of such big data is improving our understanding of interactions between biological systems and global environmental changes. In this review, we first explore how big data has been analyzed to identify the general patterns of biological responses to global changes at scales from gene to ecosystem. After that, we investigate how observational networks and space-based big data have facilitated the discovery of emergent mechanisms and phenomena on the regional and global scales. Then, we evaluate the predictions of terrestrial biosphere under global changes by big modeling data. Finally, we introduce some methods to extract knowledge from big data, such as meta-analysis, machine learning, traceability analysis, and data assimilation. The big data has opened new research opportunities, especially for developing new data-driven theories for improving biological predictions in Earth system models, tracing global change impacts across different organismic levels, and constructing cyberinfrastructure tools to accelerate the pace of model-data integrations. These efforts will uncork the bottleneck of using big data to understand biological responses and adaptations to future global changes. |
| WOS关键词 | PROGRESSIVE NITROGEN LIMITATION ; PLANT TRAIT DATABASE ; LAND CARBON STORAGE ; MODEL-DATA FUSION ; LONG-TERM CARBON ; DATA ASSIMILATION ; SOIL RESPIRATION ; INTERANNUAL VARIABILITY ; SPECIES RICHNESS ; ELEVATED CO2 |
| 资助项目 | National Natural Science Foundation of China[31722009] ; National Key R&D Program of China[2017YFA0604600] |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| 出版者 | WILEY |
| WOS记录号 | WOS:000568545700001 |
| 资助机构 | National Natural Science Foundation of China ; National Key R&D Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/156855]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Xia, Jianyang |
| 作者单位 | 1.Shanghai Inst Pollut Control & Ecol Secur, Shanghai, Peoples R China 2.Chinese Acad Sci, Nat Resources Res, Beijing, Peoples R China 3.East China Normal Univ, Sch Ecol & Environm Sci, Res Ctr Global Change & Ecol Forecasting, Zhejiang Tiantong Forest Ecosyst Natl Observat &, Shanghai, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xia, Jianyang,Wang, Jing,Niu, Shuli. Research challenges and opportunities for using big data in global change biology[J]. GLOBAL CHANGE BIOLOGY,2020:22. |
| APA | Xia, Jianyang,Wang, Jing,&Niu, Shuli.(2020).Research challenges and opportunities for using big data in global change biology.GLOBAL CHANGE BIOLOGY,22. |
| MLA | Xia, Jianyang,et al."Research challenges and opportunities for using big data in global change biology".GLOBAL CHANGE BIOLOGY (2020):22. |
入库方式： OAI收割
来源：地理科学与资源研究所
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