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An Epidemiological Simulation Model with Three Scales of Spatial Hierarchy

August 2004 , Volume 94 , Number  8
Pages  883 - 891

Laetitia Willocquet and Serge Savary

First author: UMR INRA-ENSAR BiO3P (Biologie des Organismes et des Populations appliquée à la Protection des Plantes), BP 35327, 35653 Le Rheu Cedex, France; and second author: Ecole Nationale Supérieure Agronomique de Rennes, 65 rue de Saint-Brieuc, CS 84215, 35042 Rennes Cedex, France

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Accepted for publication 5 April 2004.

An epidemiological model integrating three organizational scales of host plant populations (e.g., sites, leaves, and plants) is presented. At the lowest (site) scale, the model simulates the dynamics of vacant, latent, infectious, and removed sites. Three types of vacant sites are distinguished, depending on presence of infections at higher scales (leaf or plant). The rate of infection of each type of vacant site is computed according to ratios of autodeposition, allo-leaf-deposition, and allo-plantdeposition. At the leaf and plant scales, the rate of victimization is a function of the rate of infection of vacant sites. Sensitivity analyses showed that deposition patterns (the relative proportions of auto-, allo-leaf-, and allo-plant-depositions) and host structure (leaf size and number of leaves per plant) affected the speed of epidemics at the different scales. Model outputs conformed with results from other approaches in the case of random distribution of the disease. The model hypotheses concerning infection from autodeposited propagules, and their implications for disease epidemics, are discussed. The model can be used to derive relationships between allo-deposition ratios and disease incidences at the three scales. These relationships become simple when disease intensity is low. These relationships may be useful, e.g., to assess the potential efficiency of cultivar mixture to control epidemics. Integration of different organization scales and allo-deposition parameters enables the model to capture important features of epidemics developing in space without using explicitly spatialized variables. Such an approach could be useful to analyze other ecological processes that involve a variety of scales.

Additional keywords: canopy structure, disease aggregation.

© 2004 The American Phytopathological Society