Impacts of heat stress on leaf area index and growth duration of winter wheat in the North China Plain
文献类型:期刊论文
作者 | Chen, Yi1,2; Zhang, Zhao1; Tao, Fulu2,3![]() |
刊名 | FIELD CROPS RESEARCH
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出版日期 | 2018-06-01 |
卷号 | 222页码:230-237 |
关键词 | Extreme climate event impacts Heat stress Growth duration LAI Winter wheat |
ISSN号 | 0378-4290 |
DOI | 10.1016/j.fcr.2017.06.007 |
通讯作者 | Zhang, Zhao(zhangzhao@bnu.edu.cn) |
英文摘要 | Impact of high temperature stress on crop growth and productivity is one key concern with respect to crop production and food security under climate change. Due to the complexity and diversity of crop characteristics and farmers' management practices, as well as the difficulties in quantifying those agronomic management practices at reasonable temporal and spatial scales, crop responses to heat stress at a regional scale have not been properly assessed yet. In this study, we used remote-sensing data to investigate the responses of growth duration and leaf area index (LAI) of winter wheat to extreme high temperature during reproductive growing stage in the North China Plain from 2001 to 2008. Growing degree days above 0 degrees C (GDD) from heading to maturity was used to represent average temperature of growing environment, and the extreme temperature ( > 34 degrees C) degree days (EDD) was used as an indicator for heat stress. We detected statistically significant shortening of reproductive growing duration due to increase in GDD and EDD at both site and regional scales. We also found acceleration of leaf senescence under warmer environment, as well as considerable damages to leaf area by extremely high temperatures according to LAI values from remote-sensing data. Our results present the explicit patterns of crop responses to heat stress at different spatial scales and periods, indicating the complexity of the impacts of extreme events. Moreover, we highlighted that exposure, vulnerability and adaptation all should be considered in evaluating the impacts of extreme events. In addition, our findings suggest great potential for improving regional crop growth monitoring and yield prediction through assimilating remote-sensing data into mechanistic crop simulation models. |
WOS关键词 | CROP YIELD ASSESSMENT ; CLIMATE-CHANGE ; HIGH-TEMPERATURE ; KALMAN FILTER ; EXTREME HEAT ; MODELS ; MODIS ; PHENOLOGY ; SERIES ; TIME |
资助项目 | National Science Foundation of China[41571493] ; National Science Foundation of China[41571088] ; National Science Foundation of China[31561143003] ; Academy of Finland ; PLUMES project[277403] ; PLUMES project[292836] ; NORFASYS project[268277] ; NORFASYS project[292944] ; State Key Laboratory of Earth Surface Processes and Resource Ecology |
WOS研究方向 | Agriculture |
语种 | 英语 |
WOS记录号 | WOS:000432234200022 |
出版者 | ELSEVIER SCIENCE BV |
资助机构 | National Science Foundation of China ; Academy of Finland ; PLUMES project ; NORFASYS project ; State Key Laboratory of Earth Surface Processes and Resource Ecology |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/54898] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Zhang, Zhao |
作者单位 | 1.Beijing Normal Univ, Fac Geog Sci, State Key Lab Earth Surface Proc & Resource Ecol, Key Lab Environm Change & Nat Hazards, Beijing 100875, Peoples R China 2.Nat Resources Inst Finland Luke, FI-00790 Helsinki, Finland 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 4.Georg August Univ Gottingen, Dept Crop Sci, Grisebachstr 6, D-37077 Gottingen, DE, Germany |
推荐引用方式 GB/T 7714 | Chen, Yi,Zhang, Zhao,Tao, Fulu,et al. Impacts of heat stress on leaf area index and growth duration of winter wheat in the North China Plain[J]. FIELD CROPS RESEARCH,2018,222:230-237. |
APA | Chen, Yi,Zhang, Zhao,Tao, Fulu,Palosuo, Tam,&Rotter, Reimund P..(2018).Impacts of heat stress on leaf area index and growth duration of winter wheat in the North China Plain.FIELD CROPS RESEARCH,222,230-237. |
MLA | Chen, Yi,et al."Impacts of heat stress on leaf area index and growth duration of winter wheat in the North China Plain".FIELD CROPS RESEARCH 222(2018):230-237. |
入库方式: OAI收割
来源:地理科学与资源研究所
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