A stochastic, spatially-explicit, demo-genetic model simulating the spread and evolution of a plant pathogen in a heterogeneous landscape to assess resistance deployment strategies.
It is based on a spatial geometry for describing the landscape and allocation of different cultivars, a dispersal kernel for the dissemination of the pathogen, and a SEIR (‘Susceptible-Exposed-Infectious-Removed’) structure with a discrete time step.
It provides a useful tool to assess the performance of a wide range of deployment options with respect to their epidemiological, evolutionary and economic outcomes.


Configuration and dependencies

Read file “DESCRIPTION” for details on configuration requirements (with linux and R).
The package for compiling needs g++, gsl dev library and ffmpeg (for videos).

Under Linux OS:

sudo apt-get install g++ libgsl2 libgsl-dev ffmpeg

Under Windows use the zip.
> You can install Rtools and get g++, gsl and ffmpeg binaries under Windows (using pacman).

R packages dependencies :
* Rcpp * sp * Matrix * mvtnorm * maptools * fields * splancs * sf
* DBI * RSQLite * foreach * parallel * doParallel

To install :


Shiny interface

You can try the online Landsepi R Shiny App
or run it into R. To run the shiny interface into R you will need the following packages:

Install packages : install.packages(c("shiny","shinyBS", "DT", "shinyjs", "gridExtra", "png", "grid"
, "future", "promises", "tools", "shinyalert"))

The app can be launched with:



Run demonstrations (in 20-year simulations) for different deployment strategies:

demo_landsepi(strat = "MO") ## for a mosaic of cultivars
demo_landsepi(strat = "MI") ## for a mixture of cultivars
demo_landsepi(strat = "RO") ## for a rotation of cultivars
demo_landsepi(strat = "PY") ## for a pyramid of resistance genes

Get started

To get started see the first article