Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis
文献类型：期刊论文
| 作者 | Xie Xinyao1,3 ; Li Ainong1; Tan Jianbo2; Lei Guangbin1; Jin Huaan1; Zhang Zhengjian1,3
|
| 刊名 | ECOLOGICAL INDICATORS
 |
| 出版日期 | 2020 |
| 卷号 | 113页码:106224 |
| 关键词 | Global GPP datasets Lagged effect of drought Photosynthesis LUE-based models ML-based models Process-based models |
| ISSN号 | 1470-160X |
| DOI | 10.1016/j.ecolind.2020.106224 |
| 产权排序 | 1 |
| 通讯作者 | Li, Ainong(ainongli@imde.ac.cn) |
| 文献子类 | Article |
| 英文摘要 | Understanding the lagged effect of drought on photosynthesis is essential in global climate change research. Various gross primary productivity (GPP) datasets have been used to assess the drought effect on photosynthesis. However, discrepancies have been found in these GPP datasets, and whether the GPP discrepancies can cause uncertainties in understanding the lagged effect of drought on photosynthesis remains unclear. Here, twenty-six global GPP datasets from light use efficiency (LUE)-, machine learning (ML)-, and process-based models during 2001-2010, were used to evaluate the role of GPP discrepancies in characterizing the lagged effect of drought on photosynthesis. Based on probability analysis, a relatively reliable pattern about the lagged effect of drought on global photosynthesis was derived from multiple GPP datasets. Results showed that these 26 GPP datasets existed obvious discrepancies across the globe, with a standard deviation (SD) value of 42 g C m(-2) month(-1). Moreover, the area presenting the lagged effect of drought on photosynthesis was found to range between 32% and 69% of the global vegetated lands, confirming the obvious differences in drought patterns derived from different GPP datasets. Our results also indicated that the tropical region (20 degrees N-20 degrees S) presented lower reliabilities of lagged effect than other regions, indicating that the assessment of drought effect on photosynthesis in the tropical region should be more cautious. Furthermore, the probability-based lagged effect of drought on global photosynthesis showed that the lagged effect of drought on photosynthesis existed in 50% of the vegetated lands, with dominant lagged months being less than 8 months, suggesting that the water deficiency in preceding months probably influences vegetation growth. Our study highlights the need to better constrain the carbon modelling under tropical climate and demonstrates that uncertainties caused by GPP datasets should be considered when assessing drought effect on photosynthesis. |
| 电子版国际标准刊号 | 1872-7034 |
| WOS关键词 | GROSS PRIMARY PRODUCTIVITY ; LIGHT-USE EFFICIENCY ; LEAF-AREA INDEX ; CARBON-CYCLE ; TERRESTRIAL ECOSYSTEMS ; CLIMATE EXTREMES ; VEGETATION GROWTH ; TIME-SCALES ; FOREST ; MODEL |
| 资助项目 | National Earth System Science Data Center, National Science AMP; Technology Infrastructure of China ; Department for Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma ; National Key Research and Development Program of China[2016YFA0600103] ; National Natural Science Foundation of China[41631180] ; National Natural Science Foundation of China[41571373] ; National Natural Science Foundation of China[41701430] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19030303] ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS[SDS-135-1708] |
| WOS研究方向 | Biodiversity & Conservation ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000523335900100 |
| 出版者 | ELSEVIER |
| 资助机构 | National Earth System Science Data Center, National Science AMP; Technology Infrastructure of China ; Department for Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS |
| 源URL | [http://ir.imde.ac.cn/handle/131551/34113]  |
| 专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
| 通讯作者 | Li Ainong |
| 作者单位 | 1.Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China; 2.School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410114, China 3.University of Chinese Academy of Sciences, Beijing 100049, China; |
| 推荐引用方式 GB/T 7714 | Xie Xinyao,Li Ainong,Tan Jianbo,et al. Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis[J]. ECOLOGICAL INDICATORS,2020,113:106224. |
| APA | Xie Xinyao,Li Ainong,Tan Jianbo,Lei Guangbin,Jin Huaan,&Zhang Zhengjian.(2020).Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis.ECOLOGICAL INDICATORS,113,106224. |
| MLA | Xie Xinyao,et al."Uncertainty analysis of multiple global GPP datasets in characterizing the lagged effect of drought on photosynthesis".ECOLOGICAL INDICATORS 113(2020):106224. |
入库方式： OAI收割
来源：成都山地灾害与环境研究所
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