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Ewert, F.; Boote, K.J.; Rötter, R.P.; Thorburn, P.; Nendel, C. (eds) |
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Crop modelling for agriculture and food security under global change. Abstracts. International Crop Modelling Symposium iCROPM2016, 15-17 March 2016, Berlin, Germany |
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Book Whole |
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2016 |
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CropM; MACSUR_ACK |
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Berlin |
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Ewert, F.; Boote, K.J.; Rötter, R.P.; Thorburn, P.; Nendel, C. |
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MA @ admin @ |
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2428 |
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Ewert, F.; van Bussel, L.G.J.; Zhao, G.; Hoffmann, H.; Gaiser, T.; Specka, X.; Nendel, C.; Kersebaum, K.-C.; Sosa, C.; Lewan, E.; Yeluripati, J.; Kuhnert, M.; Tao, F.; Rötter, R.P.; Constantin, J.; Raynal, H.; Wallach, D.; Teixeira, E.; Grosz, B.; Bach, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Kiese, R.; Haas, E.; Eckersten, H.; Trombi, G.; Bindi, M.; Klein, C.; Biernath, C.; Heinlein, F.; Priesack, E.; Cammarano, D.; Asseng, S.; Elliott, J.; Glotter, M.; Basso, B.; Baigorria, G.A.; Romero, C.C.; Moriondo, M. |
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Title |
Uncertainties in Scaling up Crop Models for Large Area Climate-change Impact Assessments |
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Book Chapter |
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Year |
2015 |
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261-277 |
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CropM; |
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Imperial College Press |
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London |
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Rosenzweig, C.; Hillel, D. |
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Handbook of Climate Change and Agroecosystems: The Agricultural Model Intercomparison and Improvement Project (AgMIP) Integrated Crop and Economic Assessments — Joint Publication with American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America (In 2 Parts) |
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ICP Series on Climate Change Impacts, Adaptation, |
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MA @ admin @ |
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2427 |
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Author |
Ewert, F.; Rötter, R. |
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Title |
State of Affairs in CropM |
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Conference Article |
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2013 |
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CropM |
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MACSUR TradeM Workshop on Global Food Security Challenges – European Research approaches. Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany, 2013-11-18 to 2013-11-20 |
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MA @ admin @ |
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2424 |
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Author |
Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P. |
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Title |
Heat stress impacts on wheat growth and yield were reduced in the Huang-Huai-Hai Plain of China in the past three decades |
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Journal Article |
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Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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Volume |
71 |
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44-52 |
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Keywords |
adaptation; crop production; cultivars; extreme climate; impacts; phenology; high-temperature stress; climate-change; winter-wheat; spring wheat; crop yields; day length; trends; variability; senescence; phenology |
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Abstract |
Heat stress impacts on crop growth and yield have been investigated by controlled-environment experiments, however little is known about the impacts under field conditions at large spatial and temporal scales, particularly in a setting with farmers’ autonomous adaptations. Here, using detailed experiment Observations at 34 national agricultural meteorological stations spanning from 1981 to 2009 in the Huang-Huai-Hai Plain (HHHP) of China, we investigated the changes in climate and heat stress during wheat reproductive growing period (from heading to maturity) and the impacts of climate change and heat stress on reproductive growing duration (RGD) and yield in a setting with farmers’ autonomous adaptations. We found that RGD and growing degree days above 0 degrees C (GDD) from heading to maturity increased, which increased yield by similar to 14.85%, although heat stress had negative impacts on RGD and yield. During 1981-2009, high temperature (>34 degrees C) degree days (HDD) increased in the northern part, however decreased in the middle and southern parts of HHHP due to advances in heading and maturity dates. Change in HDD, together with increase in GDD and decrease in solar radiation (SRD), jointly increased wheat yield in the northern and middle parts but reduced it in the southern part of HHHP. During the study period, increase in GDD and decrease in SRD had larger impacts on yield than change in HDD. However, with climate warming of 2 degrees C, damage of heat stress on yield may offset a large portion of the benefits from increases in RGD and GDD, and eventually result in net negative impacts on yield in the northern part of HHHP. Our study showed that shifts in cultivars and wheat production system dynamics in the past three decades reduced heat stress impacts in the HHHP. The insights into crop response and adaptation to climate change and climate extremes provide excellent evidences and basis for improving climate change impact study and designing adaptation measures for the future. (C) 2015 Elsevier B.V. All rights reserved. |
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2016-06-01 |
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English |
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ISSN |
1161-0301 |
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Notes |
CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4743 |
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Author |
Zhao, G.; Hoffmann, H.; Yeluripati, J.; Xenia, S.; Nendel, C.; Coucheney, E.; Kuhnert, M.; Tao, F.; Constantin, J.; Raynal, H.; Teixeira, E.; Grosz, B.; Doro, L.; Kiese, R.; Eckersten, H.; Haas, E.; Cammarano, D.; Kassie, B.; Moriondo, M.; Trombi, G.; Bindi, M.; Biernath, C.; Heinlein, F.; Klein, C.; Priesack, E.; Lewan, E.; Kersebaum, K.-C.; Rötter, R.; Roggero, P.P.; Wallach, D.; Asseng, S.; Siebert, S.; Gaiser, T.; Ewert, F. |
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Title |
Evaluating the precision of eight spatial sampling schemes in estimating regional means of simulated yield for two crops |
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Journal Article |
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Year |
2016 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
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Volume |
80 |
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Pages |
100-112 |
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Keywords |
Crop model; Stratified random sampling; Simple random sampling; Clustering; Up-scaling; Model comparison; Precision gain; species distribution models; systems simulation; weather data; large-scale; design; soil; optimization; growth; apsim; autocorrelation |
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Abstract |
We compared the precision of simple random sampling (SimRS) and seven types of stratified random sampling (StrRS) schemes in estimating regional mean of water-limited yields for two crops (winter wheat and silage maize) that were simulated by fourteen crop models. We found that the precision gains of StrRS varied considerably across stratification methods and crop models. Precision gains for compact geographical stratification were positive, stable and consistent across crop models. Stratification with soil water holding capacity had very high precision gains for twelve models, but resulted in negative gains for two models. Increasing the sample size monotonously decreased the sampling errors for all the sampling schemes. We conclude that compact geographical stratification can modestly but consistently improve the precision in estimating regional mean yields. Using the most influential environmental variable for stratification can notably improve the sampling precision, especially when the sensitivity behavior of a crop model is known. |
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English |
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ISSN |
1364-8152 |
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Notes |
CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4724 |
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