Landscape Epidemiology and Evolution
Landscape allocation
Allocate cultivars to one croptype
Allocate genes to a cultivar
Allocate croptypes to the landscape
Antiderivative of the Verhulst logistic function
Check croptypes
Check cultivars
Check cultivars genes
Check host dispersal
Check pathogen dispersal
Check genes
Check inoculum
Check the landscape
Check outputs
Check pathogen
Check the array PI0_mat when entered manually in loadInoculum().
Check simulation parameters
Check time
Check treatment
Compute AUDPC in a single 100% susceptible field
Create a LandsepiParams object.
Cultivars Type list
Package demonstration
Dispersal matrices for rust fungi of cereal crops.
Generation of epidemiological and economic model outputs
Generation of evolutionary model outputs
Get the "croptype/pathogen genotype" compatibility matrix.
Get the "cultivar/pathogen genotype" compatibility matrix.
Get the "resistance gene/pathogen genotype" compatibility matrix.
Get the "polygon/pathogen genotype" compatibility matrix.
LandsepiParams
Inoculum To Matrix
Inverse logit function
is.in.01
is.positive
is.strict.positive
is.wholenumber
Landscapes
Landscape Epidemiology and Evolution
Class LandsepiParams
Load Croptypes
Load a cultivar
Load a host dispersal matrix
Load pathogen dispersal matrices
Load a gene
Load Inoculum
Load a landscape
Load outputs
Load pathogen parameters
Load simulation parameters
Load treatment parameters
Logit function
Model for Landscape Epidemiology & Evolution
Allocation of cultivars
Periodic covariance function
Plotting allocation of croptypes in a landscape
Plotting pathotype frequencies
Plotting the landscape
Price reduction function
Reset cultivars genes
runShinyApp
Run a simulation
Save landscape and deployment strategy
Set croptypes
Set cultivars
Set host dispersal
Set pathogen dispersal
Set genes
Set inoculum
Set the landscape
Set outputs
Set the pathogen
Set the seed
setSeedValue
Set time parameters
Set chemical treatments
show
Simulation with input parameters as data.frames.
summary
Survival probability To Matrix
Switch from index of genotype to indices of agressiveness on different...
Update the probability of sexual reproduction
Update pathogen survival probability during the off-season
Generation of a video
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. Loup Rimbaud, Julien Papaïx, Jean-François Rey, Luke G Barrett, Peter H Thrall (2018) <doi:10.1371/journal.pcbi.1006067>.
Useful links