|   | 
Details
   web
Records
Author Hoffmann, H.; Zhao, G.; Constantin, J.; Raynal, H.; Wallach, D.; Coucheney, E.; Sosa, C.; Lewan, E.; Eckersten, H.; Specka, X.; Kersebaum, K.-C.; Nendel, C.; Grosz, B.; Dechow, R.; Kuhnert, M.; Yeluripati, J.; Kiese, R.; Haas, E.; Klatt, S.; Teixeira, E.; Bindi, M.; Trombi, G.; Moriondo, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Vanuytrecht, E.; Tao, F.; Rötter, R.; Cammarano, D.; Asseng, S.; Weihermüller, L.; Siebert, S.; Gaiser, T.; Ewert, F.
Title Effects of soil and climate input data aggregation on modelling regional crop yields Type Conference Article
Year (up) 2015 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title MACSUR Science Conference
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MACSUR Science Conference, 2015-04-08 to 2015-04-10, Reading, United Kingdom
Notes Approved no
Call Number MA @ admin @ Serial 5037
Permanent link to this record
 

 
Author Grosz, B.; Dechow, R.; Hoffmann, H.; Zhao, G.; Constantin, J.; Raynal, H.; Wallach, D.; Coucheney, E.; Lewan, E.; Eckersten, H.; Specka, X.; Kersebaum, K.-C.; Nendel, C.; Kuhnert, M.; Yeluripati, J.; Kiese, R.; Haas, E.; Klatt, S.; Teixeira, E.; Bindi, M.; Trombi, G.; Moriondo, M.; Doro, L.; Roggero, P.P.; Zhao, Z.; Wang, E.; Vanuytrecht, E.; Tao, F.; Rötter, R.; Cammarano, D.; Asseng, S.; Weihermüller, L.; Siebert, S.; Gaiser, T.; Ewert, F
Title The implication of input data aggregation on upscaling of soil organic carbon changes Type Conference Article
Year (up) 2015 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title MACSUR Science Conference
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference MACSUR Science Conference, 2015-04-08 to 2015-04-10, Reading, United Kingdom
Notes Approved no
Call Number MA @ admin @ Serial 5038
Permanent link to this record
 

 
Author Tao, F.; Zhang, Z.; Zhang, S.; Rötter, R.P.; Shi, W.; Xiao, D.; Liu, Y.; Wang, M.; Liu, F.; Zhang, H.
Title Historical data provide new insights into response and adaptation of maize production systems to climate change/variability in China Type Journal Article
Year (up) 2016 Publication Field Crops Research Abbreviated Journal Field Crops Research
Volume 185 Issue Pages 1-11
Keywords china; climate variability; grain yield; impact; maize; northeast china; tropical maize; wheat yields; heat-stress; crop yields; temperature; impacts; sensitivities; hybrids; trends
Abstract Extensive studies had been conducted to investigate the impacts of climate change on maize growth and yield in recent decades; however, the dynamics of crop husbandry in response and adaptation to climate change were not taken into account. Based on field observations spanning from 1981 to 2009 at 167 agricultural meteorological stations across China, we found that solar radiation and temperature over the observed maize growth period had decreasing trends during 1981-2009, and maize yields were positively correlated with these climate variables in major production regions. The decreasing trends in solar radiation and temperature during maize growth period were mainly ascribed to the adoption of late maturity cultivars with longer reproductive growth period (RGP). The adoption of late maturing cultivars with longer RGP contributed substantially to grain yield increase during the last three decades. The climate trends during maize growth period varied among different production areas. During 1981-2009, decreases in mean temperature, precipitation and solar radiation over maize growth period jointly reduced yield most by 13.2-17.3% in southwestern China, by contrast in northwestern China increases in mean temperature, precipitation and solar radiation jointly increased yield most by 12.9-14.4%. Our findings highlight that the adaptations of maize production system to climate change through shifts of sowing date and genotypes are underway and should be taken into accounted when evaluating climate change impacts. (C) 2015 Elsevier B.V. All rights reserved.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0378-4290 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4816
Permanent link to this record
 

 
Author Cammarano, D.; Rötter, R.P.; Asseng, S.; Ewert, F.; Wallach, D.; Martre, P.; Hatfield, J.L.; Jones, J.W.; Rosenzweig, C.; Ruane, A.C.; Boote, K.J.; Thorburn, P.J.; Kersebaum, K.C.; Aggarwal, P.K.; Angulo, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Brisson, N.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Heng, L.; Hooker, J.E.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Müller, C.; Kumar, S.N.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Priesack, E.; Ripoche, D.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; White, J.W.; Wolf, J.
Title Uncertainty of wheat water use: Simulated patterns and sensitivity to temperature and CO2 Type Journal Article
Year (up) 2016 Publication Field Crops Research Abbreviated Journal Field Crops Research
Volume 198 Issue Pages 80-92
Keywords Multi-model simulation; Transpiration efficiency; Water use; Uncertainty; Sensitivity
Abstract Projected global warming and population growth will reduce future water availability for agriculture. Thus, it is essential to increase the efficiency in using water to ensure crop productivity. Quantifying crop water use (WU; i.e. actual evapotranspiration) is a critical step towards this goal. Here, sixteen wheat simulation models were used to quantify sources of model uncertainty and to estimate the relative changes and variability between models for simulated WU, water use efficiency (WUE, WU per unit of grain dry mass produced), transpiration efficiency (Teff, transpiration per kg of unit of grain yield dry mass produced), grain yield, crop transpiration and soil evaporation at increased temperatures and elevated atmospheric carbon dioxide concentrations ([CO2]). The greatest uncertainty in simulating water use, potential evapotranspiration, crop transpiration and soil evaporation was due to differences in how crop transpiration was modelled and accounted for 50% of the total variability among models. The simulation results for the sensitivity to temperature indicated that crop WU will decline with increasing temperature due to reduced growing seasons. The uncertainties in simulated crop WU, and in particularly due to uncertainties in simulating crop transpiration, were greater under conditions of increased temperatures and with high temperatures in combination with elevated atmospheric [CO2] concentrations. Hence the simulation of crop WU, and in particularly crop transpiration under higher temperature, needs to be improved and evaluated with field measurements before models can be used to simulate climate change impacts on future crop water demand.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0378-4290 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4786
Permanent link to this record
 

 
Author Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S.
Title Lessons from climate modeling on the design and use of ensembles for crop modeling Type Journal Article
Year (up) 2016 Publication Climatic Change Abbreviated Journal Clim. Change
Volume Issue Pages
Keywords Model ensembles; Crop models; Climate models; Model weighting; Super ensembles
Abstract Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0165-0009 1573-1480 ISBN Medium Review
Area CropM Expedition Conference
Notes CropM; wos; ft=macsur; wsnotyet; Approved no
Call Number MA @ admin @ Serial 4781
Permanent link to this record