Climate Change, High-Temperature Stress, Rice Productivity, and Water Use in Eastern China: A New Superensemble-Based Probabilistic Projection

Journal of Applied Meteorology and Climatology - Tập 52 Số 3 - Trang 531-551 - 2013
Fulu Tao, Zhao Zhang

Tóm tắt

AbstractThe impact of climate change on rice productivity in China remains highly uncertain because of uncertainties from climate change scenarios, parameterizations of biophysical processes, and extreme temperature stress in crop models. Here, the Model to Capture the Crop–Weather Relationship over a Large Area (MCWLA)-Rice crop model was developed by parameterizing the process-based general crop model MCWLA for rice crop. Bayesian probability inversion and a Markov chain Monte Carlo technique were then applied to MCWLA-Rice to analyze uncertainties in parameter estimations and to optimize parameters. Ensemble hindcasts showed that MCWLA-Rice could capture the interannual variability of the detrended historical yield series fairly well, especially over a large area. A superensemble-based probabilistic projection system (SuperEPPS) coupled to MCWLA-Rice was developed and applied to project the probabilistic changes of rice productivity and water use in eastern China under scenarios of future climate change. Results showed that across most cells in the study region, relative to 1961–90 levels, the rice yield would change on average by 7.5%–17.5% (from −10.4% to 3.0%), 0.0%–25.0% (from −26.7% to 2.1%), and from −10.0% to 25.0% (from −39.2% to −6.4%) during the 2020s, 2050s, and 2080s, respectively, in response to climate change, with (without) consideration of CO2 fertilization effects. The rice photosynthesis rate, biomass, and yield would increase as a result of increases in mean temperature, solar radiation, and CO2 concentration, although the rice development rate could accelerate particularly after the heading stage. Meanwhile, the risk of high-temperature stress on rice productivity would also increase notably with climate change. The effects of extreme temperature stress on rice productivity were explicitly parameterized and addressed in the study.

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Tài liệu tham khảo

Aggarwal, 2002, Climate change and rice yields in diverse agroenvironments of India. II. Effect of uncertainties in scenarios and crop models on impact assessment, Climatic Change, 52, 331, 10.1023/A:1013714506779

Ainsworth, 2005, What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2, New Phytol., 165, 351, 10.1111/j.1469-8137.2004.01224.x

Challinor, 2005, Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles, Tellus, 57A, 498, 10.3402/tellusa.v57i3.14670

Challinor, 2009, Ensemble yield simulations: Crop and climate uncertainties, sensitivity to temperature and genotypic adaptation to climate change, Climate Res., 38, 117, 10.3354/cr00779

Chavas, 2009, Long-term climate change impacts on agricultural productivity in eastern China, Agric. For. Meteor., 149, 1118, 10.1016/j.agrformet.2009.02.001

Cheng, 2009, Interactions of elevated [CO2] and night temperature on rice growth and yield, Agric. For. Meteor., 149, 51, 10.1016/j.agrformet.2008.07.006

Easterling, 2007

Food Agriculture Organization of the United Nations (FAO), 1991

Gerten, 2004, Terrestrial vegetation and water balance—Hydrological evaluation of a dynamic global vegetation model, J. Hydrol., 286, 249, 10.1016/j.jhydrol.2003.09.029

Hastings, 1970, Monte Carlo sampling methods using Markov chain and their applications, Biometrika, 57, 97, 10.1093/biomet/57.1.97

Horie, 1995

Horie, 1997

Iizumi, 2009, Parameter estimation and uncertainty analysis of a large-scale crop model for paddy rice: Application of a Bayesian approach, Agric. For. Meteor., 149, 333, 10.1016/j.agrformet.2008.08.015

Iizumi, 2011, Probabilistic evaluation of climate change impacts on paddy rice productivity in Japan, Climatic Change, 107, 169, 10.1007/s10584-010-9990-7

Imin, 2004, Effect of early cold stress on the maturation of rice anthers, Proteomics, 4, 1873, 10.1002/pmic.200300738

Kim, 2003, Seasonal changes in the effects of elevated CO2 on rice at three levels of nitrogen supply: A free air CO2 enrichment (FACE) experiment, Global Change Biol., 9, 826, 10.1046/j.1365-2486.2003.00641.x

Kimball, 1983, Carbon dioxide and agricultural yield: An assemblage and analysis of 430 prior observation, Agron. J., 75, 779, 10.2134/agronj1983.00021962007500050014x

Kimball, 2002, Responses of agricultural crops to free-air CO2 enrichment, Adv. Agron., 77, 293, 10.1016/S0065-2113(02)77017-X

Kropff, 1993

Liu, 2012, Contrasting effects of warming and autonomous breeding on single-rice productivity in China, Agric. Ecosyst. Environ., 149, 20, 10.1016/j.agee.2011.12.008

Lobell, 2008, Prioritizing climate change adaptation needs for food security in 2030, Science, 319, 607, 10.1126/science.1152339

Lobell, 2012, Extreme heat effects on wheat senescence in India, Nature Climate Change, 2, 186, 10.1038/nclimate1356

Masutomi, 2009, Impact assessment of climate change on rice production in Asia in comprehensive consideration of process/parameter uncertainty in general circulation models, Agric. Ecosyst. Environ., 131, 281, 10.1016/j.agee.2009.02.004

Matsui, 1992, Effect of elevated CO2 and high temperature on growth and yield of rice. Part 2. Sensitive period and pollen germination rate in high temperature sterility of rice spikelets at flowering, Japan. J. Crop. Sci., 61, 148

Matthews, 1997, Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation, Agric. Syst., 54, 399, 10.1016/S0308-521X(95)00060-I

Metropolis, 1953, Equation of state calculations by fast computing machines, J. Chem. Phys., 21, 1087, 10.1063/1.1699114

Mitchell, 2005, An improved method of constructing a database of monthly climate observations and associated high-resolution grids, Int. J. Climatol., 25, 693, 10.1002/joc.1181

Mitchell, T. D., T. R.Carter, P. D.Jones, M.Hulme, and M.New, 2004: A comprehensive set of high-resolution grids of monthly climate for Europe and the globe: The observed record (1901–2000) and 16 scenarios (2001–2100). Working Paper 55, Tyndall Centre for Climate Change Research, University of East Anglia, Norwich, UK, 30 pp. [Available online at http://www.tyndall.ac.uk/sites/default/files/wp55.pdf.]

Morison, 1999, Interactions between increasing CO2 concentration and temperature on plant growth, Plant Cell Environ., 22, 659, 10.1046/j.1365-3040.1999.00443.x

Nakagawa, 2003

Peng, 2004, Rice yields decline with higher night temperature from global warming, Proc. Natl. Acad. Sci. USA, 101, 9971, 10.1073/pnas.0403720101

Prentice, 2001

Press, 1992

Rötter, 2011, Crop-climate models need an overhaul, Nature Climate Change, 1, 175, 10.1038/nclimate1152

Shen, 2011, Simulating the rice yield change in the middle and lower reaches of the Yangtze River under SRES B2 scenario, Acta Ecol. Sin., 31, 40, 10.1016/j.chnaes.2010.11.007

Tao, 2010, Adaptation of maize production to climate change in North China Plain: Quantify the relative contributions of adaptation options, Eur. J. Agron., 33, 103, 10.1016/j.eja.2010.04.002

Tao, 2013, Climate change, wheat productivity and water use in the North China Plain: A new super-ensemble-based probabilistic projection, Agric. For. Meteor., 170, 146, 10.1016/j.agrformet.2011.10.003

Tao, 2003, Future climate change, the agricultural water cycle, and agricultural production in China, Agric. Ecosyst. Environ., 95, 203, 10.1016/S0167-8809(02)00093-2

Tao, 2006, Climate changes and trends in phenology and yields of field crops in China, 1981–2000, Agric. For. Meteor., 138, 82, 10.1016/j.agrformet.2006.03.014

Tao, 2008, Global warming, rice production and water use in China: Developing a probabilistic assessment, Agric. For. Meteor., 148, 94, 10.1016/j.agrformet.2007.09.012

Tao, 2009, Modelling the impacts of weather and climate variability on crop productivity over a large area: A new process-based model development, optimization, and uncertainties analysis, Agric. For. Meteor., 149, 831, 10.1016/j.agrformet.2008.11.004

Tao, 2009, Modelling the impacts of weather and climate variability on crop productivity over a large area: A new super-ensemble-based probabilistic projection, Agric. For. Meteor., 149, 1266, 10.1016/j.agrformet.2009.02.015

Tebaldi, 2008, Towards probabilistic projections of climate change impacts on global crop yields, Geophys. Res. Lett., 35, 10.1029/2008GL033423

Tubiello, 2002, Simulating the effects of elevated CO2 on crops: Approaches and applications for climate change, Eur. J. Agron., 18, 57, 10.1016/S1161-0301(02)00097-7

Tubiello, 2007, Crop response to elevated CO2 and world food supply: A comment on “Food for Thought” by Long et al., Science 312:1918–1921, 2006, Eur. J. Agron., 26, 215, 10.1016/j.eja.2006.10.002

Xiong, W., D.Conway, J.Jiang, Y.Li, E.Lin, Y.Xu, H.Ju, and S.Calsamiglia-Mendlewicz, 2008: The impacts of climate change on Chinese agriculture—Phase II. Future cereal production in China: Modelling the interaction of climate change, water availability and socioeconomic scenarios. AEA Group Final Rep., 41 pp. [Available online at https://ueaeprints.uea.ac.uk/33659/1/Future-cereal-production-Interaction.pdf.]

Yang, 2006, The impact of free-air CO2 enrichment (FACE) and N supply on yield formation of rice crops with large panicle, Field Crops Res., 98, 141, 10.1016/j.fcr.2005.12.014

Yao, 2007, Assessing the impacts of climate change on rice yields in the main rice areas of China, Climatic Change, 80, 395, 10.1007/s10584-006-9122-6

Zobler, 1986