English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

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

Zhu, P., Zhuang, Q., Archontoulis, S. V., Bernacchi, C., Müller, C. (2019): Dissecting the nonlinear response of maize yield to high temperature stress with model-data integration. - Global Change Biology, 25, 7, 2470-2484.
https://doi.org/10.1111/gcb.14632

Item is

Files

show Files
hide Files
:
8497.pdf (Any fulltext), 534KB
 
File Permalink:
-
Name:
8497.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-
:
8497.pdf (Any fulltext), 3MB
 
File Permalink:
-
Name:
8497.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Zhu, P.1, Author
Zhuang, Q.1, Author
Archontoulis, S. V.1, Author
Bernacchi, C.1, Author
Müller, Christoph2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 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 CO2 might 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.

Details

show
hide
Language(s):
 Dates: 2019
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1111/gcb.14632
PIKDOMAIN: RD2 - Climate Resilience
eDoc: 8497
Research topic keyword: Food & Agriculture
Research topic keyword: Climate impacts
Model / method: LPJmL
Organisational keyword: RD2 - Climate Resilience
Working Group: Land Use and Resilience
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Global Change Biology
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 25 (7) Sequence Number: - Start / End Page: 2470 - 2484 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals192