An individual-based model to simulate Coffee Leaf Rust epidemics
2021-07-28, 13:30–13:40 (UTC), Blue

Coffee Leaf Rust (CLR) is an aggressive plant disease of high economic importance that has caused major production collapses worldwide. To explore how the management and long-term planning of a coffee farm can influence CLR epidemic outcomes over several years, we took advantage of Julia’s multiple dispatch and distributed computing to develop and test an individual-based model of a coffee farm.

CLR is an active research topic in plant pathology and epidemiology. However, the overall effect of the use of shade trees on the development of the CLR disease has not yet been established. The introduction of shade trees in a farm produces local changes that can have positive or negative effects on the development of CLR epidemics, depending on the life cycle stage of present infections.
In an effort to integrate relevant pathology and ecology knowledge, we developed a spatially explicit individual-based model that allows us to simulate CLR epidemics at a farm scale and its effect on coffee productivity over several years. Using high-throughput computing, we explore different agricultural management strategies, including various patterns of shade-providing tree placement within the farm, and test their efficacy at controlling a potential CLR outbreak. This talk will show how Agents.jl and Distributed.jl facilitated our research.

Manuela Vanegas Ferro is a PhD candidate in Biological Design at Arizona State University. She earned a Bachelor of Science degree in Biology and Microbiology and a Master of Science degree in Computational Biology from Universidad de los Andes in Colombia. Manuela has experience in modeling complex biological systems at different scales. Currently, she is developing an individual-based model that integrates biological features of coffee rust disease and socio-economic aspects of coffee farmers' management practices to find optimal long-term farming strategies.