Using simple data experiments to explore the influence of non-temperature controls on maize yields in the mid-West and Great Plains

Abstract

Several recent papers have suggested that high temperatures are associated with reduced maize yields. To better understand the conditions under which this association may occur, we conduct two analyses on maize yields from 1981 to 2011 for 100 U.S. counties with large areas planted to maize in the mid-West and Great Plains. First, we compare statistical yield models in non-irrigated and extensively irrigated counties, after carefully evaluating the degree of crop irrigation in a county and selecting only counties with no irrigation or extensive irrigation. We find that yields in extensively irrigated counties have minimal dependency on temperature factors in the regression model. Second, we compare statistical yield models across non-irrigated counties using data sets with and without years with known extreme moisture anomalies. We find that for Minnesota, Central Iowa, and Northern Illinois, the sufficiency of yield models based only on temperature factors are highly leveraged by the few years with extreme moisture anomalies. In western Iowa and much of Illinois, temperature factors consistently explain a moderate amount of yield variability, even when extreme moisture anomalies are removed. In general, these findings suggest that in many regions maize yields are not solely dependent on temperature and that other factors (e.g. humidity, soil moisture, flooding) likely need to be accounted for to improve statistical yield models and to make accurate projections of maize yield in a changing climate.