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Author Webber, H.; Martre, P.; Asseng, S.; Kimball, B.; White, J.; Ottman, M.; Wall, G.W.; De Sanctis, G.; Doltra, J.; Grant, R.; Kassie, B.; Maiorano, A.; Olesen, J.E.; Ripoche, D.; Rezaei, E.E.; Semenov, M.A.; Stratonovitch, P.; Ewert, F.
Title Canopy temperature for simulation of heat stress in irrigated wheat in a semi-arid environment: A multi-model comparison Type Journal Article
Year 2017 Publication Field Crops Research Abbreviated Journal Field Crops Research
Volume 202 Issue Pages 21-35
Keywords Crop model comparison; Canopy temperature; Heat stress; Wheat
Abstract Even brief periods of high temperatures occurring around flowering and during grain filling can severely reduce grain yield in cereals. Recently, ecophysiological and crop models have begun to represent such phenomena. Most models use air temperature (Tair) in their heat stress responses despite evidence that crop canopy temperature (Tc) better explains grain yield losses. Tc can deviate significantly from Tair based on climatic factors and the crop water status. The broad objective of this study was to evaluate whether simulation of Tc improves the ability of crop models to simulate heat stress impacts on wheat under irrigated conditions. Nine process-based models, each using one of three broad approaches (empirical, EMP; energy balance assuming neutral atmospheric stability, EBN; and energy balance correcting for the atmospheric stability conditions, EBSC) to simulate Tc, simulated grain yield under a range of temperature conditions. The models varied widely in their ability to reproduce the measured Tc with the commonly used EBN models performing much worse than either EMP or EBSC. Use of Tc to account for heat stress effects did improve simulations compared to using only Tair to a relatively minor extent, but the models that additionally use Tc on various other processes as well did not have better yield simulations. Models that simulated yield well under heat stress had varying skill in simulating Tc. For example, the EBN models had very poor simulations of Tc but performed very well in simulating grain yield. These results highlight the need to more systematically understand and model heat stress events in wheat.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor (down)
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 4824
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Author Maiorano, A.; Martre, P.; Asseng, S.; Ewert, F.; Müller, C.; Rötter, R.P.; Ruane, A.C.; Semenov, M.A.; Wallach, D.; Wang, E.; Alderman, P.D.; Kassie, B.T.; Biernath, C.; Basso, B.; Cammarano, D.; Challinor, A.J.; Doltra, J.; Dumont, B.; Rezaei, E.E.; Gayler, S.; Kersebaum, K.C.; Kimball, B.A.; Koehler, A.-K.; Liu, B.; O’Leary, G.J.; Olesen, J.E.; Ottman, M.J.; Priesack, E.; Reynolds, M.; Stratonovitch, P.; Streck, T.; Thorburn, P.J.; Waha, K.; Wall, G.W.; White, J.W.; Zhao, Z.; Zhu, Y.
Title Crop model improvement reduces the uncertainty of the response to temperature of multi-model ensembles Type Journal Article
Year 2016 Publication Field Crops Research Abbreviated Journal Field Crops Research
Volume 202 Issue Pages 5-20
Keywords Impact uncertainty; High temperature; Model improvement; Multi-model ensemble; Wheat crop model
Abstract To improve climate change impact estimates and to quantify their uncertainty, multi-model ensembles (MMEs) have been suggested. Model improvements can improve the accuracy of simulations and reduce the uncertainty of climate change impact assessments. Furthermore, they can reduce the number of models needed in a MME. Herein, 15 wheat growth models of a larger MME were improved through re-parameterization and/or incorporating or modifying heat stress effects on phenology, leaf growth and senescence, biomass growth, and grain number and size using detailed field experimental data from the USDA Hot Serial Cereal experiment (calibration data set). Simulation results from before and after model improvement were then evaluated with independent field experiments from a CIMMYT world-wide field trial network (evaluation data set). Model improvements decreased the variation (10th to 90th model ensemble percentile range) of grain yields simulated by the MME on average by 39% in the calibration data set and by 26% in the independent evaluation data set for crops grown in mean seasonal temperatures >24 °C. MME mean squared error in simulating grain yield decreased by 37%. A reduction in MME uncertainty range by 27% increased MME prediction skills by 47%. Results suggest that the mean level of variation observed in field experiments and used as a benchmark can be reached with half the number of models in the MME. Improving crop models is therefore important to increase the certainty of model-based impact assessments and allow more practical, i.e. smaller MMEs to be used effectively.
Address 2016-09-13
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language Language Summary Language Newsletter July 2016 Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0378-4290 ISBN Medium Article
Area CropM Expedition Conference
Notes CropMwp;wos; ft=macsur; wsnot_yet; Approved no
Call Number MA @ admin @ Serial 4776
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Author Sánchez, B.; Rasmussen, A.; Porter, J.R.
Title Temperatures and the growth and development of maize and rice: a review Type Journal Article
Year 2014 Publication Global Change Biology Abbreviated Journal Glob. Chang. Biol.
Volume 20 Issue 2 Pages 408-417
Keywords Climate Change; Oryza/*growth & development; Temperature; Zea mays/*growth & development; cardinal temperatures; climatic change impacts; development; growth; lethal temperatures; maize; rice
Abstract Because of global land surface warming, extreme temperature events are expected to occur more often and more intensely, affecting the growth and development of the major cereal crops in several ways, thus affecting the production component of food security. In this study, we have identified rice and maize crop responses to temperature in different, but consistent, phenological phases and development stages. A literature review and data compilation of around 140 scientific articles have determined the key temperature thresholds and response to extreme temperature effects for rice and maize, complementing an earlier study on wheat. Lethal temperatures and cardinal temperatures, together with error estimates, have been identified for phenological phases and development stages. Following the methodology of previous work, we have collected and statistically analysed temperature thresholds of the three crops for the key physiological processes such as leaf initiation, shoot growth and root growth and for the most susceptible phenological phases such as sowing to emergence, anthesis and grain filling. Our summary shows that cardinal temperatures are conservative between studies and are seemingly well defined in all three crops. Anthesis and ripening are the most sensitive temperature stages in rice as well as in wheat and maize. We call for further experimental studies of the effects of transgressing threshold temperatures so such responses can be included into crop impact and adaptation models.
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1354-1013 ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur, IPCC-AR5 Approved no
Call Number MA @ admin @ Serial 4693
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Author Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J.W.; Hatfield, J.L.; Ruane, A.C.; Boote, K.J.; Thorburn, P.J.; Rötter, R.P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P.K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A.J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Kersebaum, K.C.; Müller, C.; Naresh Kumar, S.; 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.
Title Uncertainty in simulating wheat yields under climate change Type Journal Article
Year 2013 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change
Volume 3 Issue 9 Pages 827-832
Keywords crop production; models; food; co2; temperature; projections; adaptation; scenarios; ensemble; impacts
Abstract Projections of climate change impacts on crop yields are inherently uncertain(1). Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate(2). However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models(1,3) are difficult(4). Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development and policymaking.
Address
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1758-678x ISBN Medium Article
Area Expedition Conference
Notes CropM, ftnotmacsur, IPCC-AR5 Approved no
Call Number MA @ admin @ Serial 4599
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Author Gabaldón-Leal, C.; Webber, H.; Otegui, M.E.; Slafer, G.A.; Ordonez, R.A.; Gaiser, T.; Lorite, I.J.; Ruiz-Ramos, M.; Ewert, F.
Title Modelling the impact of heat stress on maize yield formation Type Journal Article
Year 2016 Publication Field Crops Research Abbreviated Journal Field Crops Research
Volume 198 Issue Pages 226-237
Keywords Heat stress; Maize; Zea mays (L); Crop models; HIGH-TEMPERATURE STRESS; KERNEL NUMBER; CROP GROWTH; GRAIN-YIELD; SIMULATION; CLIMATE; HYBRIDS; SET; VALIDATION; COMPONENTS
Abstract The frequency and intensity of extreme high temperature events are expected to increase with climate change. Higher temperatures near anthesis have a large negative effect on maize (Zea mays, L.) grain yield. While crop growth models are commonly used to assess climate change impacts on maize and other crops, it is only recently that they have accounted for such heat stress effects, despite limited field data availability for model evaluation. There is also increasing awareness but limited testing of the importance of canopy temperature as compared to air temperature for heat stress impact simulations. In this study, four independent irrigated field trials with controlled heating imposed using polyethylene shelters were used to develop and evaluate a heat stress response function in the crop modeling framework SIMPLACE, in which the Lintul5 crop model was combined with a canopy temperature model. A dataset from Argentina with the temperate hybrid Nidera AX 842 MG (RM 119) was used to develop a yield reduction function based on accumulated hourly stress thermal time above a critical temperature of 34 degrees C. A second dataset from Spain with a FAO 700 cultivar was used to evaluate the model with daily weather inputs in two sets of simulations. The first was used to calibrate SIMPLACE for conditions with no heat stress, and the second was used to evaluate SIMPLACE under conditions of heat stress using the reduction factor obtained with the Argentine dataset. Both sets of simulations were conducted twice; with the heat stress function alternatively driven with air and simulated canopy temperature. Grain yield simulated under heat stress conditions improved when canopy temperature was used instead of air temperature (RMSE equal to 175 and 309 g m(-2), respectively). For the irrigated and high radiative conditions, raising the critical threshold temperature for heat stress to 39 degrees C improved yield simulation using air temperature (RMSE: 221 gm(-2)) without the need to simulate canopy temperature (RMSE: 175 gm(-2)). However, this approach of adjusting thresholds is only likely to work in environments where climatic variables and the level of soil water deficit are constant, such as irrigated conditions and are not appropriate for rainfed production conditions. (C) 2016 Elsevier B.V. All rights reserved.
Address 2016-11-17
Corporate Author Thesis
Publisher Place of Publication Editor (down)
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0378-4290, 1872-6852 ISBN Medium Article
Area Expedition Conference
Notes ft_macsur, CropM Approved no
Call Number MA @ admin @ Serial 4880
Permanent link to this record