A polyetic modelling framework for plant disease emergence

Abstract

Plant disease emergences have dramatically increased recently as a result of global changes, especially with respect to trade, host genetic uniformity, and climate change. A better understanding of the conditions and processes determining epidemic outbreaks caused by the emergence of a new pathogen, or pathogen strain, is needed to develop strategies and inform decisions to manage emerging diseases. A polyetic process‐based model is developed to analyse conditions of disease emergence. This model simulates polycyclic epidemics during successive growing seasons, the yield losses they cause, and the pathogen survival between growing seasons. This framework considers one immigrant strain coming in a single event into a system where a resident strain is already established. Outcomes are formulated as probability of emergence, time to emergence, and yield loss, resulting from deterministic and stochastic simulations. An analytical solution to determine a threshold for emergence is also derived. Analyses focus on the effects of two fitness parameters on emergence: the relative rate of reproduction (epidemic speed), and the relative rate of mortality (decay of population between seasons). Analyses revealed that stochasticity is a critical feature of disease emergence. The simulations suggest that: (a) emergence may require a series of independent immigration events before a successful invasion takes place; (b) an explosion in the population size of the new pathogen (or strain) may be preceded by many successive growing seasons of cryptic presence following an immigration event; and (c) survival between growing seasons is as important as reproduction during the growing season in determining disease emergence.

Analysis of the Similarity between in Silico Ideotypes and Phenotypic Profiles to Support Cultivar Recommendation—A Case Study on Phaseolus vulgaris L.

“…In particular, the methodology proposed can be easily extended to traits involved with resistance/tolerance to biotic and abiotic stressors. Indeed, examples of ideotyping studies targeting resistance/tolerance traits are already available (e.g., [14,58,59]), and constant efforts are being made by the modelling community to enhance the capability of crop models to reproduce the impact of environmental stressors on crop growth and development (e.g., [60,61]).…”

Economic analysis of disease and control of multi-field epidemics in agriculture

“…the periodic absence of host plants. Environmental stochasticity associated with such multi-seasonal dynamics may play a role in the emergence of novel, better-adapted pathogens (Willocquet et al, 2020). We also assumed that the yield loss in diseased fields remains constant.…”

Modelling quantitative fungicide resistance and breakdown of resistant cultivars: Designing integrated disease management strategies for Septoria of winter wheat

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