title: Landscape-scale disease risk quantification and prediction.
abstract: The study of plant disease epidemics at a landscape scale can be extended to allow for predictions about disease occurrence at this scale. Examined within the context of the disease triangle, systems developed to incorporate information primarily about the pathogen and conditions conducive to the infection process. Parametric methods can be used to relate environmental conditions to disease, and specifically relate environment to the inoculum production, the resulting infection process, or both. Aspects relating to the presence or absence of the host plant within the landscape, or patterns of the host within the landscape, are much rarer in disease prediction, although analyses incorporating these factors have been conducted. Predictive systems at the landscape scale may concentrate only on the conditions for infection or possible migratory paths of pathogen propagules. Incorporation of all components of the disease triangle may be one way to improve these systems.
authors.affiliation: Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Uppsala SE 750 07, Sweden; email: jonathan.yuen@mykopat.slu.se.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Yuen
authors.forename: Asimina
authors.initials: A
authors.lastname: Mila
mesh_terms: D018556:Crops, Agricultural / Q000382:microbiology*; D010935:Plant Diseases / Q000382:microbiology*; D018570:Risk Assessment
keywords: Bayesian decision theory; disease triangle; epidemiology; modeling