The Effects of Warming on Winter Wheat Yields in Semi-Arid China
Xiao, G., Zhang, Q., Li, Y., Wang, R., Yao, Y., Zhao, H. and Bai, H. 2010. Impact of temperature increase on the yield of winter wheat at low and high altitudes in semiarid northwestern China. Agricultural Water Management 97: 1360-1364.
Xiao et al. conducted two sets of field experiments to evaluate the effects of different degrees of warming on the productivity of winter wheat (Triticum aestivum L.) from 2006 to 2008 in the semiarid northwestern part of China: one set at the Tongwei County experiment station located at the foot of Lulu Mountain (35°13'N, 105°14'E) at an altitude of 1798 meters above sea level, and another set at the mountain's summit at an altitude of 2351 meters. At each of these locations, the seven scientists established four different air temperature treatments (ambient and ambient plus 0.6, 1.4 and 2.2°C), which they created by placing electric heating wires on the surface of the soil between the rows of wheat, which induced the 0.6-2.2°C air temperature increases they measured continuously at a height of 20 cm above the tops of the wheat canopies.
Citing Gao et al. (2002), the Chinese researchers say it has been predicted that "the average temperature in the semiarid northwest portion of China in 2050 will be 2.2°C higher than it was in 2002," and they report that based on the observed results of their study, this increase in temperature "will lead to a significant change in the growth stages and water use of winter wheat," such that "crop yields at both high and low altitudes will likely increase," by 2.6% at low altitudes and 6.0% at high altitudes.
Even without the benefits of the aerial fertilization effect and the anti-transpiration effect of the ongoing rise in the air's CO2 content, the increase in temperature that is predicted by climate models for the year 2050, if it ever comes to pass, will likely lead to increases in winter wheat production in the northwestern part of China, not the decreases that climate alarmists routinely predict.
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