Contributions of historical changes in sowing date and climate to U.S. maize yield trend: An evaluation using large-area crop modeling and data assimilation

Abstract

The consequences of changes observed in climate and management to yield trends in major cropproducing regions have implications for future food availability. We present an assessment of the impacts of historical changes in sowing date and climate to the maize yield trend in the U.S. Corn Belt from 1980 to 2006 by using large-area crop modeling and a data assimilation technique (i.e., the model optimization based on the Markov chain Monte Carlo method). Calibrated at a regional scale, the model captured the major characteristics of the changes reported in yield as well as the timing and length of maize growth periods across the Corn Belt. The simulation results using the calibrated model indicate that while the climate change observed for the period likely contributed to a decreasing yield trend, the positive contribution from the reported shift to an earlier sowing date offset the negative impacts. With the given spread in the assessment results across previous studies and in this study, the conclusion that the negative impacts of climate change on U.S. maize yield trend more likely derive from a decreasing trend in growing-season precipitation than to an increasing trend in temperature.