globalchange  > 影响、适应和脆弱性
DOI: 10.1111/gcb.12758
论文题名:
Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions
作者: Li T.; Hasegawa T.; Yin X.; Zhu Y.; Boote K.; Adam M.; Bregaglio S.; Buis S.; Confalonieri R.; Fumoto T.; Gaydon D.; Marcaida M.; Nakagawa H.; Oriol P.; Ruane A.C.; Ruget F.; Singh B.; Singh U.; Tang L.; Tao F.; Wilkens P.; Yoshida H.; Zhang Z.; Bouman B.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2015
卷: 21, 期:3
起始页码: 1328
结束页码: 1341
语种: 英语
英文关键词: Oryza sativa ; AgMIP ; Climate change ; Crop-model ensembles ; Yield prediction uncertainty
Scopus关键词: climate change ; climate conditions ; climate effect ; crop production ; crop yield ; modeling ; prediction ; rice ; uncertainty analysis ; Oryza sativa ; agriculture ; Asia ; catering service ; climate ; growth, development and aging ; rice ; sensitivity and specificity ; theoretical model ; uncertainty ; Agriculture ; Asia ; Climate ; Food Supply ; Models, Theoretical ; Oryza sativa ; Sensitivity and Specificity ; Uncertainty
英文摘要: Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi-year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO2 concentration [CO2]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model-based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well-controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO2] and temperature. © 2014 John Wiley & Sons Ltd.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/61767
Appears in Collections:影响、适应和脆弱性

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作者单位: International Rice Research Institute, Los Baños, Philippines; National Institute for Agro-Environmental Sciences, Tsukuba, Japan; Centre for Crop Systems Analysis, Wageningen University, Wageningen, Netherlands; National Engineering and Technology Center for Information Agriculture, Nanjing Agricultural University, Nanjing, China; University of Florida, Gainesville, FL, United States; CIRAD, UMR AGAP, Montpellier, France; Cassandra Lab, DiSAA, University of Milan, Milan, Italy; UMR1114 EMMAH, INRA, Avignon, France; CSIRO Agriculture Flagship, Brisbane, Australia; National Agriculture and Food Research Organization, Tsukuba, Japan; NASA Goddard Institute for Space Studies, New York, NY, United States; NASC Complex, CIMMYT, New Delhi, India; International Fertilizer Development Center, Muscle Shoals, AL, United States; Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China; UMR1114 EMMAH, UAPV, Avignon, France

Recommended Citation:
Li T.,Hasegawa T.,Yin X.,et al. Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions[J]. Global Change Biology,2015-01-01,21(3)
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