TY - JOUR
T1 - Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration
AU - Zhu, Peng
AU - Zhuang, Qianlai
AU - Archontoulis, Sotirios V.
AU - Bernacchi, Carl
AU - Müller, Christoph
N1 - We thank three anonymous reviewers whose comments significantly improved this study. This research was supported by an NSF project (IIS-1027955) and a NASA LCLUC project (NNX09AI26G) to Q. Z. We acknowledge the Rosen High Performance Computing Center at Purdue for computing support.
We thank three anonymous reviewers whose comments signifi‐ cantly improved this study. This research was supported by an NSF project (IIS‐1027955) and a NASA LCLUC project (NNX09AI26G) to Q. Z. We acknowledge the Rosen High Performance Computing Center at Purdue for computing support.
National Science Foundation, Grant/Award Number: IIS ‐ 1027955; NASA, Grant/Award Number: NNX09AI26G
PY - 2019/7
Y1 - 2019/7
N2 - Evidence suggests that global maize yield declines with a warming climate, particularly with extreme heat events. However, the degree to which important maize processes such as biomass growth rate, growing season length (GSL) and grain formation are impacted by an increase in temperature is uncertain. Such knowledge is necessary to understand yield responses and develop crop adaptation strategies under warmer climate. Here crop models, satellite observations, survey, and field data were integrated to investigate how high temperature stress influences maize yield in the U.S. Midwest. We showed that both observational evidence and crop model ensemble mean (MEM) suggests the nonlinear sensitivity in yield was driven by the intensified sensitivity of harvest index (HI), but MEM underestimated the warming effects through HI and overstated the effects through GSL. Further analysis showed that the intensified sensitivity in HI mainly results from a greater sensitivity of yield to high temperature stress during the grain filling period, which explained more than half of the yield reduction. When warming effects were decomposed into direct heat stress and indirect water stress (WS), observational data suggest that yield is more reduced by direct heat stress (−4.6 ± 1.0%/°C) than by WS (−1.7 ± 0.65%/°C), whereas MEM gives opposite results. This discrepancy implies that yield reduction by heat stress is underestimated, whereas the yield benefit of increasing atmospheric CO2might be overestimated in crop models, because elevated CO2 brings yield benefit through water conservation effect but produces limited benefit over heat stress. Our analysis through integrating data and crop models suggests that future adaptation strategies should be targeted at the heat stress during grain formation and changes in agricultural management need to be better accounted for to adequately estimate the effects of heat stress.
AB - Evidence suggests that global maize yield declines with a warming climate, particularly with extreme heat events. However, the degree to which important maize processes such as biomass growth rate, growing season length (GSL) and grain formation are impacted by an increase in temperature is uncertain. Such knowledge is necessary to understand yield responses and develop crop adaptation strategies under warmer climate. Here crop models, satellite observations, survey, and field data were integrated to investigate how high temperature stress influences maize yield in the U.S. Midwest. We showed that both observational evidence and crop model ensemble mean (MEM) suggests the nonlinear sensitivity in yield was driven by the intensified sensitivity of harvest index (HI), but MEM underestimated the warming effects through HI and overstated the effects through GSL. Further analysis showed that the intensified sensitivity in HI mainly results from a greater sensitivity of yield to high temperature stress during the grain filling period, which explained more than half of the yield reduction. When warming effects were decomposed into direct heat stress and indirect water stress (WS), observational data suggest that yield is more reduced by direct heat stress (−4.6 ± 1.0%/°C) than by WS (−1.7 ± 0.65%/°C), whereas MEM gives opposite results. This discrepancy implies that yield reduction by heat stress is underestimated, whereas the yield benefit of increasing atmospheric CO2might be overestimated in crop models, because elevated CO2 brings yield benefit through water conservation effect but produces limited benefit over heat stress. Our analysis through integrating data and crop models suggests that future adaptation strategies should be targeted at the heat stress during grain formation and changes in agricultural management need to be better accounted for to adequately estimate the effects of heat stress.
KW - crop model
KW - crop phenological stages
KW - harvest index
KW - high temperature stress
KW - satellite observations
KW - water stress
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U2 - 10.1111/gcb.14632
DO - 10.1111/gcb.14632
M3 - Article
C2 - 30929302
AN - SCOPUS:85065420855
SN - 1354-1013
VL - 25
SP - 2470
EP - 2484
JO - Global change biology
JF - Global change biology
IS - 7
ER -