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Jaromir, K.; Piotr, B.; Cezary, S. |
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Field experiment in Lubelskie region to validate crop growth models in temperate climate |
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2014 |
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CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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MA @ admin @ |
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2506 |
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Valin, H.; Sands, R.D.; van der Mensbrugghe, D. and; Nelson, G.C.; Ahammad, H.; Blanc, E.; Bodirsky; Benjamin; Fujimori, S.; Hasegawa, T.; Havlik, P.; and Heyhoe, E.; Kyle, P.; Mason-D’Croz, D.; Paltsev; Sergey; Rolinski, S.; Tabeau, A.; van Meijl, H. and; von Lampe, M.; Willenbockel, D. |
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Title |
The future of food demand: Understanding differences in global economic models |
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Journal Article |
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Year |
2014 |
Publication |
Agricultural Economics |
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Agric. Econ. |
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45 |
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1 |
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51-67 |
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Keywords |
world food demand; socioeconomic pathways; climate change; computable general equilibrium; partial equilibrium; systems |
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Abstract |
Understanding the capacity of agricultural systems to feed the world population under climate change requires projecting future food demand. This article reviews demand modeling approaches from 10 global economic models participating in the Agricultural Model Intercomparison and Improvement Project (AgMIP). We compare food demand projections in 2050 for various regions and agricultural products under harmonized scenarios of socioeconomic development, climate change, and bioenergy expansion. In the reference scenario (SSP2), food demand increases by 59-98% between 2005 and 2050, slightly higher than the most recent FAO projection of 54% from 2005/2007. The range of results is large, in particular for animal calories (between 61% and 144%), caused by differences in demand systems specifications, and in income and price elasticities. The results are more sensitive to socioeconomic assumptions than to climate change or bioenergy scenarios. When considering a world with higher population and lower economic growth (SSP3), consumption per capita drops on average by 9\% for crops and 18% for livestock. The maximum effect of climate change on calorie availability is -6% at the global level, and the effect of biofuel production on calorie availability is even smaller. |
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0169-5150 |
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TradeM, ft_macsur |
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MA @ admin @ |
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4752 |
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Ipcc |
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Summary for Policymakers |
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Book Chapter |
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Year |
2014 |
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Climate Change 2014: Impacts, Adaptation, and Vuln |
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1-32 |
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Cambridge University Press |
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Cambridge, United Kingdom and New York, NY, USA |
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Field, C.B.; Barros, V.R.; Dokken, D.J.; Mach, K.J.; Mastrandrea, M.D.; Bilir, T.E.; Chatterjee, M.; Ebi, K.L.; Estrada, Y.O.; Genova, R.C.; Girma, B.; Kissel, E.S.; Levy, A.N.; MacCracken, S.; Mastrandrea, P.R.; White, L.L. |
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MA @ admin @ |
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2500 |
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Jabloun, M.; Li, X.; Olesen, E.; Schelde, K.; Tao, F. |
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Title |
RDAISY: a comprehensive modelling framework for automated calibration, sensitivity and uncertainty analysis of the DAISY model |
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2014 |
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CropM |
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MACSUR CropM International Symposium and Workshop: Modelling climate change impacts on crop production for food security, Oslo, Norway, 2014-02-10 to 2014-02-12 |
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MA @ admin @ |
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2502 |
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Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P. |
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Variability in crop yields associated with climate anomalies in China over the past three decades |
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Journal Article |
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2016 |
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Regional Environmental Change |
Abbreviated Journal |
Reg Environ Change |
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16 |
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6 |
Pages |
1715-1723 |
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Keywords |
Adaptation; Climate change; Climate extremes; Drought; Impacts and vulnerability |
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Abstract |
We used simple and explicit methods, as well as improved datasets for climate, crop phenology and yields, to address the association between variability in crop yields and climate anomalies in China from 1980 to 2008. We identified the most favourable and unfavourable climate conditions and the optimum temperatures for crop productivity in different regions of China. We found that the simultaneous occurrence of high temperatures, low precipitation and high solar radiation was unfavourable for wheat, maize and soybean productivity in large portions of northern, northwestern and northeastern China; this was because of droughts induced by warming or an increase in solar radiation. These climate anomalies could cause yield losses of up to 50 % for wheat, maize and soybeans in the arid and semi-arid regions of China. High precipitation and low solar radiation were unfavourable for crop productivity throughout southeastern China and could cause yield losses of approximately 20 % for rice and 50 % for wheat and maize. High temperatures were unfavourable for rice productivity in southwestern China because they induced heat stress, which could cause rice yield losses of approximately 20 %. In contrast, high temperatures and low precipitation were favourable for rice productivity in northeastern and eastern China. We found that the optimum temperatures for high yields were crop specific and had an explicit spatial pattern. These findings improve our understanding of the impacts of extreme climate events on agricultural production in different regions of China. |
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2016-06-20 |
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1436-3798 1436-378x |
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CropM, ft_macsur |
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MA @ admin @ |
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4757 |
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