DYNAMO-A: A generic simulation model coupling crop growth and disease epidemic - Laetitia Willocquet; Simone Bregaglio; Roberto Ferrise; KH Kim; Serge Savary (PLoS ONE, 2025)
Very few dynamic simulation models truly involve explicit, quantitative, two-way couplings of epidemiological and agrophysiological processes. Our aim is to develop a generic, transparent and simple, coupled disease-crop model, DYNAMO-A, where a polycyclic epidemic develops within the canopy of an annual crop. DYNAMO-A builds upon existing models, RICEPEST and WHEATPEST, respectively designed as crop loss simulation platforms for rice and wheat, and the generic model GENEPEST, which was designed for further crop-specific development and educational purposes. Two intertwined components constitute DYNAMO-A: (1) an agrophysiological component simulates crop growth, which alters the carrying capacity of epidemics; and (2) an epidemiological component simulates epidemics, which affect crop growth through damage mechanisms. Analyses using DYNAMO-A consider different simulation scenarios according to the pathogen lifestyle (trophism) and production situations. First, scenarios consider a biotrophic ideotype which is a light stealer and assimilate diverter, and a necrotrophic ideotype which is a light stealer and an accelerator of leaf senescence. Second, scenarios consider two production situations (favourable or less favourable), i.e., two contexts leading to differing attainable (un-injured) crop yields (good or average). Epidemics caused by a biotrophic pathogen reduce the green leaf area and diverts plant assimilates to the pathogen tissues, resulting in a decrease in yield. In epidemics caused by a necrotrophic pathogen, both diseased and green leaf areas are reduced because of disease-induced senescence, resulting also in yield loss. Overall, at a given level of disease epidemic, absolute yield losses are higher with a biotrophic pathogen in a more favourable production situation, whereas yield losses to a necrotrophic pathogen tend to be similar irrespective of production situations. Our results concur with previous studies, both field-experiment and model-based, on several crop-disease systems. Future modelling with DYNAMO-based models should enable interdisciplinary research addressing plant disease impacts on current and future agricultural production.