Data on measuring splash dispersal of a major wheat pathogen in the field

Capacity for dispersal is a fundamental fitness component of plant
pathogens. Characterization of plant pathogen dispersal is important for
understanding how pathogen populations change in time and space. We
devised a systematic approach to measure and analyze rain splash-driven
dispersal of plant pathogens in field conditions, using the major fungal
wheat pathogen Zymoseptoria tritici as a case study.We inoculated field
plots of wheat (Triticum aestivum) with two distinct Z. tritici strains.
Next, we measured disease intensity as counts of fruiting bodies
(pycnidia) using automated image analysis. These measurements
characterized primary disease gradients, which we used to estimate
effective dispersal of the pathogen population. Genotyping of reisolated
pathogen strains with strain-specific PCR confirmed the conclusions drawn
from phenotypic data. Consistently with controlled environment studies,we
found that the characteristic scale of dispersal is tens of centimeters.We
analyzed the data using a spatially explicit mathematical model that
incorporates the spatial extent of the source, rather than assuming a
point source,which allows for a more accurate estimation of dispersal
kernels.We employed bootstrapping methods for statistical testing and
adopted a two-dimensional hypotheses test based on kernel density
estimation, enabling more robust inference compared with standard methods.
We report the first estimates of dispersal kernels of the pathogen in
field conditions. However, repeating the experiment in other environments
would lead to more robust conclusions.We put forward advanced methodology
that paves the way for further measurements of plant pathogen dispersal in
field conditions, which can inform spatially targeted plant disease
management.