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Author Martre, P.
Title Reducing uncertainty in prediction of wheat performance under climate change Type
Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 5 Issue (up) Pages Sp5-38
Keywords
Abstract Projections of climate change impacts on crop performances are inherently uncertain. However, multimodel uncertainty analysis of crop responses is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we report on the Agricultural Model Intercomparison and Improvement Project ensemble of 30 wheat models tested using both crop and climate observed data in diverse environments, including infra-red heating field experiments, for their accuracy in simulating multiple crop growth, N economy and yield variables. The relative error averaged over models in reproducing observations was 24-38% for the different end-of-season variables. Clusters of wheat models organized by their correlations with temperature, precipitation, and solar radiation revealed common characteristics of climatic responses; however, models are rarely in the same cluster when comparing across sites. We also found that the amount of information used for calibration has only a minor effect on model ensemble climatic responses, but can be large for any single model. When simulating impacts assuming a mid-century A2 emissions scenario for climate projections from 16 downscaled general circulation models and 26 wheat models, a greater proportion of the uncertainty in climate change impact projections was due to variations among wheat models rather than to variations among climate models. Uncertainties in simulated impacts increased with atmospheric [CO2] and associated warming. Extrapolating the model ensemble temperature response (at current atmospheric [CO2]) indicated that warming is already reducing yields at a majority of wheat-growing locations. Finally, only a very weak relationship was found between the models’ sensitivities to interannual temperature variability and their response to long-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs. In conclusion, uncertainties in prediction of climate change impacts on crop performance can be reduced by improving temperature and CO2 relationships in models and are better quantified through use of impact ensembles. No Label
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Area Expedition Conference MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK
Notes Approved no
Call Number MA @ admin @ Serial 2153
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Author Makowski, D.; Asseng, S.; Ewert, F.; Bassu, S.; Durand, J.L.; Li, T.; Martre, P.; Adam, M.; Aggarwal, P.K.; Angulo, C.; Baron, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Bouman, B.; Bregaglio, S.; Brisson, N.; Buis, S.; Cammarano, D.; Challinor, A.J.; Confalonieri, R.; Conijn, J.G.; Corbeels, M.; Deryng, D.; De Sanctis, G.; Doltra, J.; Fumoto, T.; Gaydon, D.; Gayler, S.; Goldberg, R.; Grant, R.F.; Grassini, P.; Hatfield, J.L.; Hasegawa, T.; Heng, L.; Hoek, S.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Jongschaap, R.E.E.; Jones, J.W.; Kemanian, R.A.; Kersebaum, K.C.; Kim, S.-H.; Lizaso, J.; Marcaida, M.; Müller, C.; Nakagawa, H.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.J.; Olesen, J.E.; Oriol, P.; Osborne, T.M.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.; Rosenzweig, C.; Ruane, A.C.; Ruget, F.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Singh, B.; Singh, U.; Soo, H.K.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tang, L.; Tao, F.; Teixeira, E.I.; Thorburn, P.; Timlin, D.; Travasso, M.; Rötter, R.P.; Waha, K.; Wallach, D.; White, J.W.; Wilkens, P.; Williams, J.R.; Wolf, J.; Yin, X.; Yoshida, H.; Zhang, Z.; Zhu, Y.
Title A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration Type Journal Article
Year 2015 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 214-215 Issue (up) Pages 483-493
Keywords climate change; crop model; emulator; meta-model; statistical model; yield; climate-change; wheat yields; metaanalysis; uncertainty; simulation; impacts
Abstract Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without rerunning the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 degrees C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2].
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Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0168-1923 ISBN Medium Article
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 4714
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Author Kersebaum, K.C.; Kollas, C.; Bindi, M.; Palosuo, T.; Wu, L.; Sharif, B.; Öztürk, I.; Trnka, M.; Hlavinka, P.; Nendel, C.; Müller, C.; Waha, K.; Armas-Herrera, C.; Olesen, J.E.; Eitzinger, J.; Roggero, P.P.; Conradt, T.; Martre, P.; Ferrise, R.; Moriondo, M.; Ruiz-Ramos, M.; Ventrella, D.; Rötter, R.P.; Wegehenkel, M.; Eckersten, H.; Lorite Torres, I.J.; Hernandez, C.G.; Launay, M.; De Wit, A.; Hoffmann, H.; Weigel, H.-J.; Manderscheid, R.; Beaudoin, N.; Constantin, J.; Garcia de Cortazar-Atauri, I.; Mary, B.; Ripoche, D.; Ruget, F.
Title Model inter-comparison on crop rotation effects – an intermediate report Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue (up) Pages
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Abstract Data of diverse crop rotations from five locations across Europe were distributed to modelers to investigate the capability of models to handle complex crop rotations and management interactions. Crop rotations comprise various main crops (winter/spring wheat, winter/spring barley, rye, oat, maize, sugar beet, oil seed rape and potatoes) plus several catch crops. The experimental setup of the datasets included treatments such as modified soils, crops exchanged within the rotations, irrigation/rainfed, nitrogen fertilization, residue management, tillage and atmospheric CO2 concentration. 19 modeling teams registered to model either the whole rotation or single crops. Models which are capable to run the whole rotation should provide transient as well as single year simulations with a reset of initial conditions. In the first step only initial soil conditions (water and soil mineral N) of the first year and key phenological stages were provided to the modelers. For calibration, crop yields and biomass were provided for selected years but not for all seasons. In total the combination of treatments and seasons results in 301 years of simulation. Results were analyzed to evaluate the effect of transient simulation versus single-year simulation regarding crop yield, biomass, water and nitrogen balance components. Model results will be evaluated crop-specifically to identify crops with highest uncertainty and potential for model improvement. Full data will be provided to modelers for model-improvement and results will provide insights into model capabilities to reproduce treatments and crops. Further, the question of error propagation along the transient simulation of crop rotations will be addressed.
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Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference
Series Volume 3(S) Sassari, Italy Series Issue Edition
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Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy
Notes Approved no
Call Number MA @ admin @ Serial 5104
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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.
Title 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 (up) 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
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 5189
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Author Tao, F.; Palosuo, T.; Roetter, R.P.; Hernandez Diaz-Ambrona, C.G.; Ines Minguez, M.; Semenov, M.A.; Kersebaum, K.C.; Cammarano, D.; Specka, X.; Nendel, C.; Srivastava, A.K.; Ewert, F.; Padovan, G.; Ferrise, R.; Martre, P.; Rodriguez, L.; Ruiz-Ramos, M.; Gaiser, T.; Hohn, J.G.; Salo, T.; Dibari, C.; Schulman, A.H.
Title Why do crop models diverge substantially in climate impact projections? A comprehensive analysis based on eight barley crop models Type Journal Article
Year 2020 Publication Agricultural and Forest Meteorology Abbreviated Journal Agricultural and Forest Meteorology
Volume 281 Issue (up) Pages 107851
Keywords agriculture; climate change; crop growth simulation; impact; model; improvement; uncertainty; air CO2 enrichment; elevated CO2; wheat growth; nitrogen dynamics; simulation-models; field experiment; atmospheric CO2; rice phenology; temperature; uncertainty
Abstract Robust projections of climate impact on crop growth and productivity by crop models are key to designing effective adaptations to cope with future climate risk. However, current crop models diverge strongly in their climate impact projections. Previous studies tried to compare or improve crop models regarding the impact of one single climate variable. However, this approach is insufficient, considering that crop growth and yield are affected by the interactive impacts of multiple climate change factors and multiple interrelated biophysical processes. Here, a new comprehensive analysis was conducted to look holistically at the reasons why crop models diverge substantially in climate impact projections and to investigate which biophysical processes and knowledge gaps are key factors affecting this uncertainty and should be given the highest priorities for improvement. First, eight barley models and eight climate projections for the 2050s were applied to investigate the uncertainty from crop model structure in climate impact projections for barley growth and yield at two sites: Jokioinen, Finland (Boreal) and Lleida, Spain (Mediterranean). Sensitivity analyses were then conducted on the responses of major crop processes to major climatic variables including temperature, precipitation, irradiation, and CO2, as well as their interactions, for each of the eight crop models. The results showed that the temperature and CO2 relationships in the models were the major sources of the large discrepancies among the models in climate impact projections. In particular, the impacts of increases in temperature and CO2 on leaf area development were identified as the major causes for the large uncertainty in simulating changes in evapotranspiration, above-ground biomass, and grain yield. Our findings highlight that advancements in understanding the basic processes and thresholds by which climate warming and CO2 increases will affect leaf area development, crop evapotranspiration, photosynthesis, and grain formation in contrasting environments are needed for modeling their impacts.
Address 2020-06-08
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Language Summary Language Original Title
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Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5232
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