Similar estimates of temperature impacts on global wheat yield by three independent methods

Research output: Contribution to journalArticlepeer-review

Authors

  • Bing Liu
  • Senthold Asseng
  • Christoph Müller
  • Frank Ewert
  • Joshua Elliot
  • David Lobell
  • Pierre Martre
  • Alex Ruane
  • Daniel Wallach
  • James Jones
  • Cynthia Rosenzweig
  • Pramod Aggarwal
  • Phillip Alderman
  • Jakarat Anothai
  • Bruno Basso
  • Christian Biernath
  • Davide Cammarano
  • Andy Challinor
  • Delphine Deryng
  • Giacomo De Sanctis
  • Jordi Doltra
  • Elias Fereres
  • Christian Folberth
  • Margarita Garcia-Vila
  • Sebastian Gayler
  • Gerrit Hoogenboom
  • Leslie Hunt
  • Roberto Izaurralde
  • Mohamed Jabloun
  • Curtis Jones
  • Kurt Kersebaum
  • Bruce Kimball
  • Ann-Kristin Koehler
  • Soora Naresh Kumar
  • Claas Nendel
  • Garry O'Leary
  • Jørgen Olesen
  • Michael Ottman
  • Taru Palosuo
  • P. V. Vara Prasad
  • Eckart Priesack
  • Matthew Reynolds
  • Ehsan Rezaei
  • Reimund Rötter
  • Erwin Schmid
  • Mikhail Semenov
  • Iurii Shcherbak
  • Elke Stehfest
  • Claudio Stöckle
  • Pierre Stratonovitch
  • Thilo Streck
  • Iwan Supit
  • Fulu Tao
  • Peter Thorburn
  • Katherina Waha
  • Gerard Wall
  • Enli Wang
  • Jeffrey White
  • Joost Wolf
  • Zhigan Zhao
  • Yan Zhu

Colleges, School and Institutes

Abstract

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify ‘method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Details

Original languageEnglish
Pages (from-to)1130–1136
Number of pages9
JournalNature Climate Change
Volume6
Early online date12 Sep 2016
Publication statusPublished - Dec 2016

Keywords

  • Agriculture , Climate-change impacts