Uran Chung, Socio-economic program, International Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico, Kindie Tesfaye, Socio-economic program, International Maize and Wheat Improvement Center (CIMMYT), Addis Ababa, Ethiopia, Thanda Dhliwayo, CIMMYT, El Batan, Mexico, Felix San Vicente, Global Maize Program, CIMMYT, Texcoco, Mexico, Jill Cairns, PO Box MP163, CIMMYT, Harare, ZIMBABWE, Zaidi P.H., Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), New Delhi, India, Sika Gbegbelegbe, Social Science, International Institute of Tropical Agriculture (IITA), Lilongwe, Malawi and Kai Sonder, CIMMYT, Mexico City, Mexico
Abstract:
Introduction: Maize is one of the most important staple food sources for human beings globally. However, the production of maize is affected by several factors. For example, extreme heat wave in combination with drought which hit the Corn Belt of the USA in 2012 had a strong impact on maize prices and affected the world market for this important commodity. Awareness related to climate change has been already heightened and IPCC (Intergovernmental Panel on Climate Change) announced that the goal now is to delay global warming by less two degree Celsius by 2050. Many crop models used to simulate maize grain yields and assessed production under climate change. However, crop model simulation results show differences and errors depending on the environmental data and crop cultivars used. In the early 2000s, CIMMYT developed the maize mega environment as a targeting tool for maize cultivars based on many studies. The current version of maize mega environments has 6 classes depending on climate (i.e. precipitation and temperature).
Method: We simulated maize grain yields at CIMMYT representative stations using process-based models, such as APSIM-Maize, CERES-Maize, MAIZIM, and a statistical model to evaluate and identify the potential of the different modeling approaches for identifying hot spots of climate change impact for the respective mega environments. For the increased scenarios, the historical daily maximum and minimum temperatures were increased by 1 – 4C, for example Baseline+1C, Baseline+2C, Baseline+3C, and Baseline+4C and each model simulated under two CO2 conditions, 380and 550 ppm, respectively. Yield changes were compared across sites and models.
Preliminary results: The simulation models agreed for most locations, but differed widely in actual yields. With increasing temperature, all models showed declining grain yields with an increase in relative variability. Especially, with temperature increase of +4C, the simulated grain yield decreased for all the models. All models used in this study agreed that warmer locations would have lower yields due to already higher growing season temperatures. Overall, there was a reduction in all the simulated yields and biomass as the growing season temperature increased.
![[ International Annual Meetings - Home Page ]](images/banner.jpg "[ International Annual Meetings - Home Page ]")