title: Thirteen challenges in modelling plant diseases.
abstract: The underlying structure of epidemiological models, and the questions that models can be used to address, do not necessarily depend on the host organism in question. This means that certain preoccupations of plant disease modellers are similar to those of modellers of diseases in human, livestock and wild animal populations. However, a number of aspects of plant epidemiology are very distinctive, and this leads to specific challenges in modelling plant diseases, which in turn sets a certain agenda for modellers. Here we outline a selection of 13 challenges, specific to plant disease epidemiology, that we feel are important targets for future work.
authors.affiliation: Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. Electronic address: njc1001@cam.ac.uk.
authors.forename: Nik J
authors.initials: NJ
authors.lastname: Cunniffe
authors.affiliation: BioSciences, University of Exeter, Penryn Campus, Tremough TR10 9EZ, UK.
authors.forename: Britt
authors.initials: B
authors.lastname: Koskella
authors.affiliation: Department of Zoology, Oxford University, Oxford OX1 3PS, UK.
authors.forename: C Jessica E
authors.initials: CJ
authors.lastname: Metcalf
authors.affiliation: Computational and Systems Biology, Rothamsted Research, Harpenden AL5 2JQ, UK.
authors.forename: Stephen
authors.initials: S
authors.lastname: Parnell
authors.affiliation: United States Department of Agriculture, Agricultural Research Service, 2001 South Rock Road, Fort Pierce, FL 34945, USA.
authors.forename: Tim R
authors.initials: TR
authors.lastname: Gottwald
authors.affiliation: Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK.
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Gilligan
mesh_terms: D018556:Crops, Agricultural; D017753:Ecosystem; D015233:Models, Statistical; D010935:Plant Diseases / Q000517:prevention & control / Q000706:statistics & numerical data*; D014887:Weather
keywords: Compartmental models; Landscape-scale models; Plant disease model; Plant epidemiology; Stochastic models