| Summary: | Regional and global economic models, combined with spatially distributed crop growth simulation models and hydrology models that simulate water supply and demand across sectors (among others), represent the most widely used quantitative approach for addressing questions related to food security under alternative future scenarios (e.g., for a recent reference, van Dijk et al., 2021). These integrated foresight modelling approaches, hereinafter referred to as “Agricultural Integrated Assessment Models” (AIAMs), provide a macro-level view of the global food system, encompassing, directly or indirectly, implicitly or explicitly, components outlined in contemporary definitions (HLPE, 2017). Due to the complex nature of modelling the effects of crop pests and pathogens (P&P) on crop performances, the use of AIAMs in P&P-related analyses has been scant and limited to hypothetical epidemics caused by specific P&Ps affecting a single crop (Godfray et al., 2016; Petsakos et al., 2023). This limitation, also identified in the ex-ante assessment of the pesticide reduction objective of the European Common Agricultural Policy (Barreiro-Hurle et al., 2021), suggests that AIAMs overlook a critical element – one that has historically contributed to, or even triggered, famine events (Padmanabhan, 1973; Woodham-Smith, 1992). Given the importance of AIAMs in informing policies and shaping agricultural decisions at national and global scales (e.g., Barreiro-Hurle et al., 2021; Fuglie et al., 2022), it is necessary to adress this gap.
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