Early warning signals in plant disease outbreaks

Correspondence Sirio Orozco-Fuentes Email: [email protected] Summary 1. Infectious disease outbreaks in plants threaten ecosystems, agricultural crops and food trade. Currently, several fungal diseases are affecting forests worldwide, posing a major risk to tree species, habitats and consequently ecosystem decay. Prediction and control of disease spread are difficult, mainly due to the complexity of the interaction between individual components involved. 2. In thiswork,we introduce a lattice-based epidemicmodel coupled with a stochastic process thatmimics, in a very simplifiedway, the interaction between the hosts and pathogen. We studied the disease spread by measuring the propagation velocity of the pathogen on the susceptible hosts. Quantitative results indicate the occurrence of a critical transition between two stable phases: local confinement and an extended epiphytotic outbreak that depends on the density of the susceptible individuals. 3. Quantitative predictions of epiphytotics are performed using the framework early-warning indicators for impending regime shifts, widely applied on dynamical systems. These signals forecast successfully the outcome of the critical shift between the two stable phases before the system enters the epiphytotic regime. 4. Synthesis: Our study demonstrates that early-warning indicators could be useful for the prediction of forest disease epidemics through mathematical andcomputationalmodels suited tomore specificpathogenhost-environmental interactions.