Articles | Volume 18, issue 18
https://doi.org/10.5194/gmd-18-5997-2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
An endogenous modelling framework of dietary behavioural change in the fully coupled human-climate FRIDA v2.1 model
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- Final revised paper (published on 16 Sep 2025)
- Preprint (discussion started on 02 Jun 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
- RC1: 'Comment on egusphere-2025-2260', Kaia Waxenberg, 09 Jun 2025
- RC2: 'Comment on egusphere-2025-2260', Anonymous Referee #2, 22 Jul 2025
- AC1: 'Response to reviewers', Jefferson K. Rajah, 06 Aug 2025
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Jefferson K. Rajah on behalf of the Authors (07 Aug 2025)
Author's response
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ED: Publish as is (11 Aug 2025) by Roslyn Henry
AR by Jefferson K. Rajah on behalf of the Authors (11 Aug 2025)
General comments
I found this to be a strong paper overall, which significantly furthers research on global integrated assessment modelling. The introduction of a more endogenous food demand model represents a significant improvement over common GDP-based models. The conclusion that current income-driven models may be overestimating future global food demand is a significant, if not expected, finding.
The majority of the text is dedicated to model description and presentation of results, with limited reflection or discussion. There could be more emphasis on the relevance of results presented, particularly in relation to the shortcomings of widely available models. Reasons why the endogenous behavioural model predicts lower future food demand when compared to the income-driven model could be discussed more fully.
Specific grammatical corrections and content suggestions
Abstract
1 Introduction
2 Existing models review
3 Model description
4 Model Calibration
5 Simulation results
6 Conclusions