SDG indicator framework for quantitative food system analysis on multiple scales

The food system, a complex system, is researched in many different ways. To assess this system, both qualitative methods and quantitative model analysis are performed to identify important processes in this complex system and identify synergies and trade-offs. To guide such analysis, this document describes an indicator framework to facilitate a food systems assessment that intends to cover relevant domains in the food system and which can be used in multi-model assessments. It is based on the Sustainable Development Goals (SDGs), to cover a broad set of themes and advances existing indicators to meet the following objectives: 1. To provide a comprehensive framework to show trade-offs and synergies between different domains. 2. To make visible what is assessed and what is not. 3. To work towards a common narrative on presenting model results, which makes clear how indicators are defined and how they relate to SDGs. This SDG indicator framework distinguishes between goal indicators and process indicators. Where goal indicators track progress towards achieving the SDGs, while process indicators provide more detailed insight in the system, nature of the progress or obstacles. To define which indicators are goal indicators and which are more related to the process, causal diagrams were designed per SDG. Indicators are selected for each relevant SDG, illustrating their use with causal diagrams. The set of official UN SDG indicators was used as an entry point. In addition, indicators aligned with model outputs of five models that were selected for this framework: MAGNET, MagnetGrid, BioSpacs, LPJmL and SSID. These are used for food system analysis within WUR, and collaborations are being developed between the models to assess food systems across multiple scales. The SDG indicator framework was tested in two case studies focusing on food systems at two spatial scales. One case focusses on the water and land system of districts in Pakistan, and the other one on healthy diets in Ethiopia. The SDG indicator framework demonstrated its effectiveness in both case studies by uncovering trade-offs across contrasting SDG indicators spanning environmental, social, and economic dimensions of sustainable development. To obtain such integrated insight, case studies used multiple models across biophysical and socio-economic domains. This multi-model approach revealed nuanced trade-offs, such as the environmental impacts of achieving Zero Hunger (SDG 2) in Ethiopia, offering valuable insights for policymakers navigating complex SDG interdependencies. However, challenges in reconciling divergent model assumptions, such as discrepancies in outputs for indicators such as GDP per capita, highlight the need for greater integration and alignment among models to improve reliability and accuracy. Visualization of trade-offs and trends among SDG indicators proved crucial for simplifying complex results and communicating them effectively to policymakers. Tools such as spider diagrams and maps enabled quick interpretation of key patterns, such as the environmental impacts of Ethiopia’s Zero Hunger scenario or the spatial distribution of Pakistan’s goal indicators. However, simplifications in visualizations risk losing nuances, such as the dual impacts of food prices on different populations or the significance of proportional changes at a global scale. Future research should address these limitations by refining visualizations and incorporating specific indicator targets, enhancing their comparability and relevance across countries and scales. By building on these findings, the framework can evolve into a more robust tool for supporting evidence-based policy decisions aligned with sustainable development goals.