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- Publisher Website: 10.1111/gcb.14632
- Scopus: eid_2-s2.0-85065420855
- PMID: 30929302
- WOS: WOS:000477087100023
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Article: Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration
Title | Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration |
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Authors | |
Keywords | crop model crop phenological stages harvest index high temperature stress satellite observations water stress |
Issue Date | 2019 |
Citation | Global Change Biology, 2019, v. 25, n. 7, p. 2470-2484 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/326414 |
ISSN | 2023 Impact Factor: 10.8 2023 SCImago Journal Rankings: 4.285 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhu, Peng | - |
dc.contributor.author | Zhuang, Qianlai | - |
dc.contributor.author | Archontoulis, Sotirios V. | - |
dc.contributor.author | Bernacchi, Carl | - |
dc.contributor.author | Müller, Christoph | - |
dc.date.accessioned | 2023-03-09T10:00:29Z | - |
dc.date.available | 2023-03-09T10:00:29Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Global Change Biology, 2019, v. 25, n. 7, p. 2470-2484 | - |
dc.identifier.issn | 1354-1013 | - |
dc.identifier.uri | http://hdl.handle.net/10722/326414 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.relation.ispartof | Global Change Biology | - |
dc.subject | crop model | - |
dc.subject | crop phenological stages | - |
dc.subject | harvest index | - |
dc.subject | high temperature stress | - |
dc.subject | satellite observations | - |
dc.subject | water stress | - |
dc.title | Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1111/gcb.14632 | - |
dc.identifier.pmid | 30929302 | - |
dc.identifier.scopus | eid_2-s2.0-85065420855 | - |
dc.identifier.volume | 25 | - |
dc.identifier.issue | 7 | - |
dc.identifier.spage | 2470 | - |
dc.identifier.epage | 2484 | - |
dc.identifier.eissn | 1365-2486 | - |
dc.identifier.isi | WOS:000477087100023 | - |