Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration

Peng Zhu, Qianlai Zhuang, Sotirios V. Archontoulis, Carl Bernacchi, Christoph Müller

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)2470-2484
Number of pages15
JournalGlobal change biology
Volume25
Issue number7
DOIs
StatePublished - Jul 2019

Fingerprint

Data integration
maize
Crops
crop
Temperature
warming
water stress
growing season
agricultural management
yield response
Water conservation
climate
Water
Hot Temperature
Biomass
effect
Satellites
biomass

Keywords

  • crop model
  • crop phenological stages
  • harvest index
  • high temperature stress
  • satellite observations
  • water stress

ASJC Scopus subject areas

  • Global and Planetary Change
  • Environmental Chemistry
  • Ecology
  • Environmental Science(all)

Cite this

Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration. / Zhu, Peng; Zhuang, Qianlai; Archontoulis, Sotirios V.; Bernacchi, Carl; Müller, Christoph.

In: Global change biology, Vol. 25, No. 7, 07.2019, p. 2470-2484.

Research output: Contribution to journalArticle

Zhu, Peng ; Zhuang, Qianlai ; Archontoulis, Sotirios V. ; Bernacchi, Carl ; Müller, Christoph. / Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration. In: Global change biology. 2019 ; Vol. 25, No. 7. pp. 2470-2484.
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