Spatial patterns and recent temporal trends in global transpiration modelled using eco-evolutionary optimality
文献类型：期刊论文
| 作者 | Li, Shijie1,2,3; Wang, Guojie1; Zhu, Chenxia1; Hannemann, Marco2,3; Poyatos, Rafael4,5; Lu, Jiao6; Li, Ji7; Ullah, Waheed8; Hagan, Daniel Fiifi Tawia9; Garcia-Garcia, Almudena2,3 |
| 刊名 | AGRICULTURAL AND FOREST METEOROLOGY
 |
| 出版日期 | 2023-11-15 |
| 卷号 | 342页码:11 |
| 关键词 | Transpiration Penman -Monteith Ball-Berry-Leuning model P model |
| ISSN号 | 0168-1923 |
| DOI | 10.1016/j.agrformet.2023.109702 |
| 通讯作者 | Peng, Jian(jian.peng@ufz.de) |
| 英文摘要 | Transpiration from vegetation accounts for about two thirds of land evapotranspiration (ET), and exerts important effects on of global water, energy, and carbon cycles. Resistance-based ET partitioning models using remote sensing data are one of the main methods to estimate global land transpiration, overcoming the limitation by the sparse distribution and short observation periods of site-level measurements. However, the uncertainties of estimated transpiration for these models mainly come from the resistance parameterization based on specific empirical parameters across different plant functional types (PFT). A model based on eco-evolutionary optimization (P model) has recently been proposed to simulate stomatal conductance without the need of calibrated parameters. Here, we calculated global long-term (1982-2018) monthly transpiration with the Penman-Monteith (PM) equation using canopy conductance estimated by the P model (PM-P) and Ball-Berry-Leuning model (PMBBL). Using the observations of SAPFLUXNET and FLUXNET sites as reference, the performance of PM-P was comparable with that of PM-BBL and Global Land Evaporation Amsterdam model (GLEAM). Multi-year mean and trends in growing season transpiration estimated by GLEAM and the PM-P model revealed a similar spatial distribution globally. Both GLEAM and the PM-P model showed a widespread increasing trend of growing season transpiration over 72.06%similar to 80.38% of global land, especially for some main greening hotspots with >3.0 mm/ year. The good performance of the P model indicated that it could avoid the uncertainties emerging from the resistance parameterization with too many empirical parameters and had the potential to accurately estimate global transpiration. |
| WOS关键词 | GROSS PRIMARY PRODUCTION ; SAP FLOW MEASUREMENTS ; SOIL-MOISTURE ; EVAPOTRANSPIRATION ; EVAPORATION ; TOWER ; TREES |
| 资助项目 | National Natural Science Foundation of China[42275028] ; Sino-German Cooperation Group Project[GZ1447] ; ESA Dragon 5 CLIMATE-Pan-TPE project ; China Scholarship Council ; MoDEV PhD college-Towards novel Model-Data fusion for understanding Environmental Variability in space and time from high-resolution remote sensing |
| WOS研究方向 | Agriculture ; Forestry ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:001145342000001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Sino-German Cooperation Group Project ; ESA Dragon 5 CLIMATE-Pan-TPE project ; China Scholarship Council ; MoDEV PhD college-Towards novel Model-Data fusion for understanding Environmental Variability in space and time from high-resolution remote sensing |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/202331]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Peng, Jian |
| 作者单位 | 1.Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Nanjing 210044, Peoples R China 2.UFZ Helmholtz Ctr Environm Res, Dept Remote Sensing, Permoserstr 15, D-04318 Leipzig, Germany 3.Univ Leipzig, Remote Sensing Ctr Earth Syst Res, Talstr 35, D-04103 Leipzig, Germany 4.CREAF, Catalonia 08193, Spain 5.Univ Autonoma Barcelona, Catalonia 08193, Spain 6.Wuxi Univ, Sch Atmospher Sci & Remote Sensing, Wuxi 214105, Peoples R China 7.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 8.Rabdan Acad, Def & Secur, Abu Dhabi 114646, U Arab Emirates 9.Univ Ghent, Hydroclimate Extremes Lab, B-9000 Ghent, Belgium 10.Univ New South Wales, Sch Civil & Environm Engn, Sydney, 2052, Australia |
| 推荐引用方式 GB/T 7714 | Li, Shijie,Wang, Guojie,Zhu, Chenxia,et al. Spatial patterns and recent temporal trends in global transpiration modelled using eco-evolutionary optimality[J]. AGRICULTURAL AND FOREST METEOROLOGY,2023,342:11. |
| APA | Li, Shijie.,Wang, Guojie.,Zhu, Chenxia.,Hannemann, Marco.,Poyatos, Rafael.,...&Peng, Jian.(2023).Spatial patterns and recent temporal trends in global transpiration modelled using eco-evolutionary optimality.AGRICULTURAL AND FOREST METEOROLOGY,342,11. |
| MLA | Li, Shijie,et al."Spatial patterns and recent temporal trends in global transpiration modelled using eco-evolutionary optimality".AGRICULTURAL AND FOREST METEOROLOGY 342(2023):11. |
入库方式： OAI收割
来源：地理科学与资源研究所
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