Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China's Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model
文献类型：期刊论文
| 作者 | Chen, Tao4; Tang, Guoping4; Yuan, Ye3; Xu, Zhenwu1,2; Jiang, Nan4 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-05-06 |
| 卷号 | 15期号:9页码:25 |
| 关键词 | subtropical forests water use efficiency vapor pressure deficit elevated CO2 concentration a modified analytical WUE model |
| DOI | 10.3390/rs15092441 |
| 通讯作者 | Tang, Guoping(tanggp3@mail.sysu.edu.cn) |
| 英文摘要 | The subtropical forests in China play a pivotal part in the global and regional carbon-water cycle and in regulating the climate. Ecosystem water-use efficiency (WUE) is a crucial index for understanding the trade-off between ecosystem carbon gain and water consumption. However, the underlying mechanisms of the WUE in forest ecosystems, especially the different subtropical forests, have remained unclear. In this paper, we developed a simple framework for estimating forest WUE and revealing the underlying mechanisms of forest WUE changes via a series of numerical experiments. Validated by measured WUE, the simulated WUE from our developed WUE framework showed a good performance. In addition, we found that the subtropical forest WUE experienced a significant increasing trend during 2001-2018, especially in evergreen and deciduous broadleaf forests where the increasing rate was greatest (0.027 gC kg(-1) H2O year(-1), p < 0.001). Further analysis indicated that the atmospheric CO2 concentration and vapor pressure deficits (VPD), rather than leaf area index (LAI), were the dominant drivers leading to the subtropical forest WUE changes. When summed for the whole subtropical forests, CO2 and VPD had an almost equal spatial impact on annual WUE change trends and accounted for 45.3% and 49.1% of the whole study area, respectively. This suggests that future forest management aiming to increase forest carbon uptake and protect water resources needs to pay more attention to the long-term impacts of climate change on forest WUE. |
| WOS关键词 | NET PRIMARY PRODUCTIVITY ; TERRESTRIAL ECOSYSTEMS ; EDDY COVARIANCE ; CARBON-DIOXIDE ; CLIMATE-CHANGE ; RAINFALL INTERCEPTION ; VAPOR-PRESSURE ; EVAPOTRANSPIRATION ; SATELLITE ; CO2 |
| 资助项目 | National Natural Science Foundation of China[42171025] ; China Scholarships Council[202106380124] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000988051600001 |
| 资助机构 | National Natural Science Foundation of China ; China Scholarships Council |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/197155]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Tang, Guoping |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China 4.Sun Yat Sen Univ, Sch Geog & Planning, Dept Phys Geog Resources & Environm, Guangzhou 510275, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Tao,Tang, Guoping,Yuan, Ye,et al. Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China's Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model[J]. REMOTE SENSING,2023,15(9):25. |
| APA | Chen, Tao,Tang, Guoping,Yuan, Ye,Xu, Zhenwu,&Jiang, Nan.(2023).Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China's Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model.REMOTE SENSING,15(9),25. |
| MLA | Chen, Tao,et al."Disentangling the Key Drivers of Ecosystem Water-Use Efficiency in China's Subtropical Forests Using an Improved Remote-Sensing-Driven Analytical Model".REMOTE SENSING 15.9(2023):25. |
入库方式： OAI收割
来源：地理科学与资源研究所
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