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Author Asseng, S.; Ewert, F.; Martre, P.; Rötter, R.P.; Lobell, D.B.; Cammarano, D.; Kimball, B.A.; Ottman, M.J.; Wall, G.W.; White, J.W.; Reynolds, M.P.; Alderman, P.D.; Prasad, P.V.V.; Aggarwal, P.K.; Anothai, J.; Basso, B.; Biernath, C.; Challinor, A.J.; De Sanctis, G.; Doltra, J.; Fereres, E.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L.A.; Izaurralde, R.C.; Jabloun, M.; Jones, C.D.; Kersebaum, K.C.; Koehler, A.-K.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Palosuo, T.; Priesack, E.; Eyshi Rezaei, E.; Ruane, A.C.; Semenov, M.A.; Shcherbak, I.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.J.; Waha, K.; Wang, E.; Wallach, D.; Wolf, J.; Zhao, Z.; Zhu, Y. url  doi
openurl 
  Title (down) Rising temperatures reduce global wheat production Type Journal Article
  Year 2014 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change  
  Volume 5 Issue 2 Pages 143-147  
  Keywords climate-change; spring wheat; dryland wheat; yield; growth; drought; heat; CO2; agriculture; adaptation  
  Abstract Crop models are essential tools for assessing the threat of climate change to local and global food production1. Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature2. Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 °C to 32 °C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each °C of further temperature increase and become more variable over space and time.  
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  Language English Summary Language Original Title  
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  ISSN 1758-678x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4550  
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Author Rötter, R.P.; Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Basso, B.; Ruane, A.; Boote, K.J.; Thorburn, P.; Brisson, N.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Pertuzzi; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.-C.; Müller, C.; Kumar, S.N.; Nendel, C.; O’Leary, G.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J. url  openurl
  Title (down) Quantifying Uncertainties in Modeling Crop Water Use under Climate Change Type Conference Article
  Year 2013 Publication Abbreviated Journal  
  Volume Issue Pages  
  Keywords CropM  
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  Area Expedition Conference Impacts World 2013, International Conference on Climate Change Effects, Potsdam, Germany, 2013-05-27 to 2013-05-30  
  Notes Approved no  
  Call Number MA @ admin @ Serial 2767  
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Author Webber, H.; White, J.W.; Kimball, B.A.; Ewert, F.; Asseng, S.; Rezaei, E.E.; Pinter, P.J., Jr.; Hatfield, J.L.; Reynolds, M.P.; Ababaei, B.; Bindi, M.; Doltra, J.; Ferrise, R.; Kage, H.; Kassie, B.T.; Kersebaum, K.-C.; Luig, A.; Olesen, J.E.; Semenov, M.A.; Stratonovitch, P.; Ratjen, A.M.; LaMorte, R.L.; Leavitt, S.W.; Hunsaker, D.J.; Wall, G.W.; Martre, P. doi  openurl
  Title (down) Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions Type Journal Article
  Year 2018 Publication Field Crops Research Abbreviated Journal Field Crops Research  
  Volume 216 Issue Pages 75-88  
  Keywords Heat stress; Crop model improvement; Heat and drought interactions; Climate change impact assessments; Canopy temperature; Wheat; Air CO2 Enrichment; Elevated Carbon-Dioxide; Water-Use Efficiency; Climate-Change; Wheat Evapotranspiration; Stomatal Conductance; Multimodel Ensembles; Farming Systems; Drought-Stress; Spring Wheat  
  Abstract Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulate Tc. Model performance in predicting Tc was evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions.  
  Address 2018-02-19  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
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  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 5189  
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Author Raymundo, R.; Asseng, S.; Prassad, R.; Kleinwechter, U.; Concha, J.; Condori, B.; Bowen, W.; Wolf, J.; Olesen, J.E.; Dong, Q.; Zotarelli, L.; Gastelo, M.; Alva, A.; Travasso, M.; Quiroz, R.; Arora, V.; Graham, W.; Porter, C. url  doi
openurl 
  Title (down) Performance of the SUBSTOR-potato model across contrasting growing conditions Type Journal Article
  Year 2017 Publication Field Crops Research Abbreviated Journal Field Crops Research  
  Volume 202 Issue Pages 57-76  
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  Series Volume Series Issue Edition  
  ISSN 0378-4290 ISBN Medium article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4967  
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Author Wallach, D.; Thorburn, P.; Asseng, S.; Challinor, A.J.; Ewert, F.; Jones, J.W.; Rötter, R.; Ruane, A. url  openurl
  Title (down) Overview paper on comprehensive framework for assessment of error and uncertainty in crop model predictions Type Report
  Year 2016 Publication FACCE MACSUR Reports Abbreviated Journal  
  Volume 8 Issue Pages C4.1-D  
  Keywords MACSUR_ACK; CropM  
  Abstract Crop models are important tools for impact assessment of climate change, as well as for  exploring management options under current climate. It is essential to evaluate the  uncertainty associated with predictions of these models. Several ways of quantifying  prediction uncertainty have been explored in the literature, but there have been no  studies of how the different approaches are related to one another, and how they are  related to some overall measure of prediction uncertainty. Here we show that all the  different approaches can be related to two different viewpoints about the model; either  the model is treated as a fixed predictor with some average error, or the model can be  treated as a random variable with uncertainty in one or more of model structure, model  inputs and model parameters. We discuss the differences, and show how mean squared  error of prediction can be estimated in both cases. The results can be used to put  uncertainty estimates into a more general framework and to relate different uncertainty  estimates to one another and to overall prediction uncertainty. This should lead to a  better understanding of crop model prediction uncertainty and the underlying causes of  that uncertainty. This study was published as (Wallach et al. 2016)  
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  Notes Approved no  
  Call Number MA @ office @ Serial 2954  
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