Modelling rice yield with temperature optima of rice productivity derived from satellite NIRv in tropical monsoon area

doi:10.1016/j.agrformet.2020.108135

	Modelling rice yield with temperature optima of rice productivity derived from satellite NIRv in tropical monsoon area
	Wang, Xiaobo 2,3; Wang, Shaoqiang 2,3; Li, Xia 4; Chen, Bin 2,3; Wang, Junbang 2,3; Huang, Mei 2,3; Rahman, Atiq 1
刊名	AGRICULTURAL AND FOREST METEOROLOGY
	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.
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关键词	CLIMATE-CHANGE ; CARBON-DIOXIDE ; HEAT-STRESS ; NITROGEN ; IMPACTS ; GROWTH
WOS研究方向	Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000566373700006
资助机构	National Natural Science Foundation of China ; National Key Research and Development Project
内容类型	期刊论文
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.Bangladesh Ctr Adv Studies, Dhaka 1212, Bangladesh 2.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Minist Ecol & Environm, Foreign Environm Cooperat Ctr, Beijing 100035, Peoples R China
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.