Switching from a mechanistic model to a continuous model to study at different scales the effect of vine growth on the dynamic of a powdery mildew epidemic.
OBJECTIVE
Epidemiological simulation models coupling plant growth with the dispersal and disease dynamics of an airborne plant pathogen were devised for a better understanding of host-pathogen dynamic interactions and of the capacity of grapevine development to modify the progress of powdery mildew epidemics.


METHODS
The first model is a complex discrete mechanistic model (M-model) that explicitly incorporates the dynamics of host growth and the development and dispersion of the pathogen at the vine stock scale. The second model is a simpler ordinary differential equations (ODEs) compartmental SEIRT model (C-model) handling host growth (foliar surface) and the ontogenic resistance of the leaves. With the M-model various levels of vine development are simulated under three contrasting climatic scenarios and the relationship between host and disease variables are examined at key periods in the epidemic process. The ability of the C-model to retrieve the main dynamics of the disease for a range of vine growth given by the M-model is investigated.


RESULTS
The M-model strengthens experimental results observed regarding the effect of the rate of leaf emergence and of the number of leaves at flowering on the severity of the disease. However, it also underlines strong variations of the dynamics of disease depending on the vigour and indirectly on the climatic scenarios. The C-model could be calibrated by using the M-model provided that different parameters before and after shoot topping and for various vigour levels and inoculation time are used. Biologically relevant estimations of the parameters that could be used for its extension to the vineyard scale are obtained.


CONCLUSIONS
The M-model is able to generate a wide range of growth scenarios with a strong impact on disease evolution. The C-model is a promising tool to be used at a larger scale.
UMR CNRS IMB & INRIA EPI Anubis, Université Victor Segalen Bordeaux, France.
Jean-Baptiste
JB
Burie
Michel
M
Langlais
Agnès
A
Calonnec
D000465:Algorithms; D001203:Ascomycota / Q000472:pathogenicity*; D002980:Climate; D003198:Computer Simulation; D018556:Crops, Agricultural / Q000254:growth & development* / Q000382:microbiology*; D058872:Epidemics; D004812:Epidemiologic Methods; D005602:France / Q000453:epidemiology; D054884:Host-Pathogen Interactions; D021621:Imaging, Three-Dimensional; D007113:Immunity, Innate; D008954:Models, Biological; D010935:Plant Diseases / Q000382:microbiology*; D018515:Plant Leaves / Q000254:growth & development / Q000382:microbiology; D018547:Plant Stems / Q000254:growth & development / Q000382:microbiology; D027843:Vitis / Q000254:growth & development* / Q000382:microbiology*