Modelling rice yield with temperature optima of rice productivity derived from satellite NIRv in tropical monsoon area
文献类型：期刊论文
| 作者 | Wang, Xiaobo1,2; Wang, Shaoqiang1,2; Li, Xia3; Chen, Bin1,2; Wang, Junbang1,2; Huang, Mei1,2; Rahman, Atiq4 |
| 刊名 | AGRICULTURAL AND FOREST METEOROLOGY
 |
| 出版日期 | 2020-11-15 |
| 卷号 | 294页码:12 |
| 关键词 | Optimal temperature Near-infrared reflectance of vegetation Crop model Climate change Tropical rice |
| ISSN号 | 0168-1923 |
| DOI | 10.1016/j.agrformet.2020.108135 |
| 通讯作者 | Wang, Shaoqiang(sqwang@igsnrr.ac.cn) |
| 英文摘要 | Tropical rice production is at risk from rising temperature. Understanding regional and seasonal heterogeneity of optimum temperatures for rice production is important for model simulation to predict rice yield change under climate change. However, studies or tools for widely observation of crop responses to temperature over broad spatial scales with long time spans are limited. In this study, we detected optimum temperature range for rice gross primary production (T-opt(GPP)) in the lower Gangetic plains and delta region using the near-infrared reflectance of vegetation (NIRv), which is a new photosynthetic proxy, to improve ORYZA model performance in high-temperature season and assessed how tropical rice would respond to temperature increase in the study area. According to satellite observations of NIRv from 2001 to 2015, current ambient air temperature has exceeded the mean T-opt(GPP) of Boro rice (24.8 +/- 1.8 degrees C) and Aman rice (26.7 +/- 1.2 degrees C) in the lower Gangetic plains and delta region, suggesting a downtrend of rice production under future warming. The detection results show that rice has lower T-opt(GPP) in the regions with more drought stress and lower background temperature under water-limited conditions. Furthermore, the model modified by NIRv-T-opt(GPP) shows better performance in potential yields, especially in high-temperature seasons on the region scale. Without CO2 fertilization effect, each degree-Celsius increase is expected to reduce rice potential yields by 4.9 +/- 1.6% based on the default T-opt(GPP) range in ORYZA model and by 7.0 +/- 1.2% based on the detected NIRv-T-opt(GPP) range in the study area. This study implies that global grid-based model simulation may underestimate sensitivity of tropical rice yield to temperature rise due to the neglect of regional and seasonal heterogeneity of T-opt(GPP). NIRv makes it possible to determine local optimal temperatures for crop production, and to improve grid-based modelling across various agricultural systems in different growing seasons at the regional scale. |
| WOS关键词 | CLIMATE-CHANGE ; CARBON-DIOXIDE ; HEAT-STRESS ; NITROGEN ; IMPACTS ; GROWTH |
| 资助项目 | National Natural Science Foundation of China[31,861,143,015] ; National Natural Science Foundation of China[41,871,342] ; National Key Research and Development Project[2017YFC0503803] |
| WOS研究方向 | Agriculture ; Forestry ; Meteorology & Atmospheric Sciences |
| 语种 | 英语 |
| WOS记录号 | WOS:000566373700006 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Project |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/157942]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Wang, Shaoqiang |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Minist Ecol & Environm, Foreign Environm Cooperat Ctr, Beijing 100035, Peoples R China 4.Bangladesh Ctr Adv Studies, Dhaka 1212, Bangladesh |
| 推荐引用方式 GB/T 7714 | Wang, Xiaobo,Wang, Shaoqiang,Li, Xia,et al. Modelling rice yield with temperature optima of rice productivity derived from satellite NIRv in tropical monsoon area[J]. AGRICULTURAL AND FOREST METEOROLOGY,2020,294:12. |
| APA | Wang, Xiaobo.,Wang, Shaoqiang.,Li, Xia.,Chen, Bin.,Wang, Junbang.,...&Rahman, Atiq.(2020).Modelling rice yield with temperature optima of rice productivity derived from satellite NIRv in tropical monsoon area.AGRICULTURAL AND FOREST METEOROLOGY,294,12. |
| MLA | Wang, Xiaobo,et al."Modelling rice yield with temperature optima of rice productivity derived from satellite NIRv in tropical monsoon area".AGRICULTURAL AND FOREST METEOROLOGY 294(2020):12. |
入库方式： OAI收割
来源：地理科学与资源研究所
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