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Tom Pugh

Thomas Pugh

Senior lecturer

Tom Pugh

Substantial Differences in Crop Yield Sensitivities Between Models Call for Functionality-Based Model Evaluation

Author

  • Christoph Müller
  • Jonas Jägermeyr
  • James A. Franke
  • Alex C. Ruane
  • Juraj Balkovic
  • Philippe Ciais
  • Marie Dury
  • Pete Falloon
  • Christian Folberth
  • Tobias Hank
  • Munir Hoffmann
  • R. Cesar Izaurralde
  • Ingrid Jacquemin
  • Nikolay Khabarov
  • Wenfeng Liu
  • Stefan Olin
  • Thomas A.M. Pugh
  • Xuhui Wang
  • Karina Williams
  • Florian Zabel
  • Joshua W. Elliott
Show all

Summary, in English

Crop models are often used to project future crop yield under climate and global change and typically show a broad range of outcomes. To understand differences in modeled responses, we analyzed modeled crop yield response types using impact response surfaces along four drivers of crop yield: carbon dioxide (C), temperature (T), water (W), and nitrogen (N). Crop yield response types help to understand differences in simulated responses per driver and their combinations rather than aggregated changes in yields as the result of simultaneous changes in various drivers. We find that models' sensitivities to the individual drivers are substantially different and often more different across models than across regions. There is some agreement across models with respect to the spatial patterns of response types but strong differences in the distribution of response types across models and their configurations suggests that models need to undergo further scrutiny. We suggest establishing standards in model evaluation based on emergent functionality not only against historical yield observations but also against dedicated experiments across different drivers to analyze emergent functional patterns of crop models.

Department/s

  • Dept of Physical Geography and Ecosystem Science
  • eSSENCE: The e-Science Collaboration
  • MERGE: ModElling the Regional and Global Earth system
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • LU Profile Area: Nature-based future solutions

Publishing year

2024

Language

English

Publication/Series

Earth's Future

Volume

12

Issue

3

Document type

Journal article

Publisher

John Wiley & Sons Inc.

Topic

  • Agricultural Science

Keywords

  • AgMIP
  • crop model
  • evaluation
  • global
  • sensitivity
  • uncertainty

Status

Published

ISBN/ISSN/Other

  • ISSN: 2328-4277