Editorial: Food systems, spatial modelling, and planning

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This Research Topic on Food Systems, Spatial Modelling, and Planning, was conceived to address these challenges through an intersectional lens focusing on food system thinking, geospatial modeling, and land use and spatial planning. This triad is deeply interdependent: food systems require understanding of their multiple dimensions and scales in a holistic manner; modelling provides the analytical foundation for evidence-based decision-making; and planning translates these insights into place-based strategies for food systems' sustainable transformation. This research topic brings together seven interdisciplinary studies from diverse contexts, including China, Central Asia, South Africa, Italy, Ireland, and the United Kingdom. Collectively, these contributions explore the complex interplay between food systems, spatial modelling, and spatial planning through two complementary dimensions:(1) A systemic framework dimension, which discusses key concepts, integrative approaches, and participatory frameworks for planning and governance processes to enable food system transformation.(2) An analytical dimension, which applies spatial modelling to examine the multidimensional drivers that shape agri-food and land-use dynamics, thereby supporting evidence-based planning and informed decision-making.The first group of contributions situates food systems transformation within broader systemic and governance contexts. A conceptual paper outlines a system-thinking framework that integrates environmental, social, and economic drivers through a One Health perspective. It emphasizes that food system resilience cannot be achieved in isolation from human and ecosystem health, and that participatory processes, bringing together policymakers, scientists, and communities, are essential to co-designing sustainable pathways (Gilmor et al., 2025).Complementing this, another study examines climate-smart adaptation and mitigation strategies, highlighting how farmers' perceptions of climate change influence their willingness to adopt innovative practices, particularly when supported by adequate knowledge, financial resources, and institutional frameworks (Mudzielwana, 2025).Both papers converge on a critical insight: food system's resilience and sustainability depend as much on enabling conditions as on technological options. Knowledge dissemination, social organization, and inclusive governance emerge as decisive factors for adaptive capacity, echoing studies (Dawid & Boka, 2025).The second group of contributions deepens this discussion by examining the agri-food dynamics that underpin food security. These studies deploy geospatial models, statistical methods, and scenario analyses to map how environmental, socio-economic and political factors shape agricultural performance and land-use change.Four studies from China exemplify the analytical power of spatial modelling. In Xinjiang, an optimized MaxEnt ecological niche model reveals how climate change and human activity jointly influence cotton cultivation distribution, emphasizing that production systems respond to both natural and socio-economic gradients (Wang et al., 2025). Spatial statistical analysis uncovers the heterogeneity of grain production drivers, showing how inputs such as cultivated land, fertilizers, and rural electrification shape regional disparities In Sichuan Province (Dang et al., 2025) Valbuena et al., 2010), advances in computational power now allow these models to integrate multiple spatial and behavioral layers with greater efficiency, opening new possibilities for simulating the co-evolution of human decision-making and landscape dynamics within food systems.The studies gathered under the Food Systems-Spatial Modelling-Planning topic enhance our understanding of how complex societal challenges can be addressed through the combined use of spatial modelling and system's thinking. Spatial modelling of agri-food systems informs planning (e.g. from water-saving measures and land-use assessments for farmland protection to policies that account for farmers' motivations) while systems' thinking translates these analytical insights into territorially coherent strategies. Together, they show that planning for sustainable food systems demands interdisciplinary and collaborative frameworks that equip policymakers with a holistic, data-informed vision of change.An important takeaway from this synthesis is that advancing sustainable food system requires triangulation, bringing together systemic understanding, spatial and quantitative evidence, and planning and governance practice (Figure 1). This conceptual framework illustrates how systems thinking, spatial modelling, planning and governance can interact to build more sustainable food systems. Systems thinking provides a holistic understanding of the multiple dimensions within food systems; spatial modelling offers analytical, "what-if," and visual tools to assess spatial dynamics; and spatial planning and governance translate this knowledge into coordinated strategies and policies. Together, they advance a more comprehensive understanding of how systems thinking, spatial modelling, and (food) planning may interact to drive the transition toward a Sustainable Food System. This need for integration extends beyond food systems to other complex socio-ecological and spatial domains, as contemporary realities increasingly demonstrate.Of the seven studies, three lines of research emerge:1. Spatial diagnostics and monitoring, which should evolve toward dynamic and systems thinking capable of continuously assessing agri-food performance and supporting evidence-based decision-making;2. Social and behavioural integration in planning, embedding farmer and stakeholder behaviour through participatory methods, supported by emerging tools such as GeoAI, large-language-model analytics, and agent-based simulations for scenario design;3. Cross-scale integration, linking local food systems with regional, national, and global sustainability goals through multi-level governance and planning.To strengthen and operationalise these strands, policy frameworks play a pivotal role in enabling and sustaining food system transformation. Effective spatial and agrifood planning can incentivize sustainable practices, foster innovation, and align multi-level governance toward shared sustainability goals. Integrating systems thinking and spatial evidence into policy design ensures that interventions are adaptive, equitable, and grounded in local realities.Recent work underscores that participatory and polycentric governance processes are increasingly advocated to support food system integration and transformation, while linking modelling outputs with policy processes enhances coherence and responsiveness (Edwards et al., 2024;Allen, 2016). For instance, the integrated assessment modelling framework developed for China demonstrates that most social and environmental targets of the Chinese food system remain misaligned with the United Nations Agenda 2030 (Wang, 2025). Similarly, the indicator framework proposed by the Food Systems Countdown Initiative helps inform more coherent policy responses by elucidating interactions among indicators (Schneider et al., 2025). Other perspectives propose integrating agricultural and agronomic models with social and demographic modelling to strengthen understanding of productivity and resilience for food security (Brown, 2025). Such integration enables decision-makers to explore trade-offs, anticipate unintended consequences, and evaluate alternative pathways toward sustainability.As food systems face unprecedented pressures, spatially informed and evidence-based policies provide the analytical and institutional foundations needed to plan sustainable and resilient food systems, serving as effective pathways toward a healthy planet. More broadly, the studies in this collection engage with wider scientific debates on spatial justice, planetary health, resilience,

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