Bundling measures for food systems transformation: a global, multimodel assessment
- PMID: 41197651
- DOI: 10.1016/j.lanplh.2025.101339
Bundling measures for food systems transformation: a global, multimodel assessment
Abstract
Background: Current food systems leave one in ten individuals at risk of hunger while driving unsustainable environmental impacts. Inaction risks further exacerbating negative impacts on both human and planetary health. These challenges emerge from complex system interactions, requiring approaches that engage with this complexity and consider how transformation measures interact across food systems. We aimed to quantify the magnitude and uncertainty of the impacts of key food systems transformation measures both individually and in a bundle using an ensemble of global economic models.
Methods: In this global multimodel assessment, we applied an ensemble of ten state-of-the-art global economic models to evaluate the potential of four key measures in transforming food systems: increasing agricultural productivity, halving food loss and waste, shifting towards healthier diets, and economy-wide climate mitigation policies aligned with limiting warming to 1·5°C. The scenarios used a middle-of-the-road shared socioeconomic pathway for population and gross domestic product growth, climate impact data from Jägermeyr and colleagues, Thornton and colleagues, and Nelson and colleagues, and dietary targets based on the EAT-Lancet healthy reference diet, with model simulations conducted from 2020 to 2050. We then assessed the effect of these measures in isolation and in combination in a bundled scenario. To further understand the interactions between these measures, we conducted a decomposition analysis that distinguishes between the individual effects of a measure (effect when implemented alone), total effects (its contribution within the bundle), and interaction effects (the difference between total and individual effects). This approach aimed to show complementarities and trade-offs that emerge when multiple measures are implemented simultaneously.
Findings: Our analysis showed that individual measures in isolation are insufficient to achieve high-level environmental objectives and might generate unintended consequences. In contrast, bundling measures produces co-benefits: avoiding 50% of projected agricultural greenhouse gas emissions by 2050 and almost 20% of anticipated land conversion, while moderating food price increases associated with ambitious climate change mitigation policies. Our decomposition analysis further shows that measures can have varying effects across different dimensions. Although dietary shifts and climate mitigation policies are the largest drivers of environmental benefits (each contributing to a median decline of >10 percentage points in non-CO2 emissions and 5 percentage points in agricultural land use globally), productivity improvements and reducing food loss and waste play essential roles in moderating price increases (each contributing to a median decline of >5 percentage points in average prices).
Interpretation: This study highlights the importance of implementing coordinated approaches to food system transformation and climate change mitigation rather than relying on isolated interventions. Comprehensive transformation requires understanding how supply-side and demand-side changes can interact with climate mitigation policies, enabling policy makers to design intervention packages that maximise benefits while minimising trade-offs across environmental, economic, and social dimensions.
Funding: Bill & Melinda Gates Foundation; Cornell Atkinson Center for Sustainability; Environment Research and Technology Development Fund; the Asahi Glass Foundation; CGIAR Initiative on Foresight; the CGIAR Science Program on Policy Innovations; US Department of Agriculture, Economic Research Service; and the ClimateWorks Foundation, European Union.
Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Conflict of interest statement
Declaration of interests Funding for SD, AM, TS, and KW was provided to the International Food Policy Research Institute through the CGIAR Initiative on Foresight and the CGIAR Science Program on Policy Innovations. RS’ time for contributing to this manuscript was covered by the US Department of Agriculture Economic Research Service. AB, DVV, ES, HL, and JD were funded by PBL Netherlands Environmental Assessment Agency and the EAT Foundation. FT received funding from the German Climate Protection Programme 2022 from the Federal Ministry of Food and Agriculture, and German Federal Ministry of Education and Research (grant agreement number 031B0730C). GT received funding from The Joint Research Centre, Seville. MG, TDO, MSu, MH, and DM-CC were funded by the Bill & Melinda Gates Foundation. MG, TDO, MSu, and MH received funding from Cornell Atkinson Center for Sustainability. HvM’s funding was provided by the Horizon Europe 101060075 BRIGHTSPACE project and of the Dutch Ministry of Agriculture, Nature, and Food through the Knowledgebase Program 34: Circular and Climate Neutral. MKu, TDL, and W-JvZ were supported by Wageningen Social and Economic Research. XZ’s participation in this research was partially supported by the ClimateWorks Foundation. FB was financed by the IKEA Foundation, the Rockefeller Foundation, the Children's Investment Fund Foundation, the Wellcome Trust, and the Bill & Melinda Gates Foundation. IW received funding from the PyMiCCS project. MSp received funding from Wellcome Trust and the EU Horizon Programme. All other authors declare no competing interests.
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