Using physiologically and spatially structured consumer- resource population models to address current issues in plant pathology
Résumé
Epidemiologists and pathologists for addressing topical questions about, for example, the efficiency of agroecological solutions to mitigating crop diseases or their impact on pathogen evolution. We propose here to showcase two modeling approaches that our team is currently using in this context. Firstly, based on the framework of physiologically structured population models and its numerical implementation (referred to as the EBTtool) we represent a (multi-) seasonally growing crop canopy as a dynamic collection of small infectable patches of leaf tissue with intrinsic and dynamic properties (e.g. age, position in the canopy, nutrient content, infection status). Dynamics of predicted disease epidemics depend on the dynamic properties of all the patches over time. Secondly, the agent-based modeling environment NetLogo provides a conceptual framework to model spatially extended dynamics of disease progression in explicit landscapes with different spatial arrangements of crops that are not necessarily static over the cropping seasons. We are using these two modeling approaches to study resource dynamics at the canopy and landscape scales as a way to explore the potential of regulating crop pathogens by reducing or diversifying nitrogen fertilization practices in the pathosystems wheat/rusts and wheat/septoria tritici blotch. These modeling approaches offer the opportunity to (1) predict short and long term epidemiological dynamics based on assumptions on the consumer-resource interactions at the lesion scale, (2) to reveal pathogen trade-offs (transmission, virulence, aggressiveness) that emerge from the interactions between the pathogen and ecophysiological and morphological dynamics of the crop canopy, (3) to study the effect of spatial resource heterogeneity on pathogen dynamics, adaptation and maladaptation.
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