epid_output | R Documentation |
Generates epidemiological and economic outputs from model simulations.
epid_output(
types = "all",
time_param,
Npatho,
area,
rotation,
croptypes,
cultivars_param,
eco_param,
treatment_param,
pathogen_param,
audpc100S = 0.76,
writeTXT = TRUE,
graphic = TRUE,
path = getwd()
)
types |
a character string (or a vector of character strings if several outputs are to be computed) specifying the type of outputs to generate (see details):
|
time_param |
list of simulation parameters:
|
Npatho |
number of pathogen genotypes. |
area |
a vector containing polygon areas (must be in square meters). |
rotation |
a dataframe containing for each field (rows) and year (columns, named "year_1", "year_2", etc.), the index of the cultivated croptype. Importantly, the matrix must contain 1 more column than the real number of simulated years. |
croptypes |
a dataframe with three columns named 'croptypeID' for croptype index, 'cultivarID' for cultivar index and 'proportion' for the proportion of the cultivar within the croptype. |
cultivars_param |
list of parameters associated with each host genotype (i.e. cultivars):
|
eco_param |
a list of economic parameters for each host genotype as if cultivated in pure crop:
|
treatment_param |
list of parameters related to pesticide treatments:
|
pathogen_param |
a list of i. pathogen aggressiveness parameters on a susceptible host for a pathogen genotype not adapted to resistance and ii. sexual reproduction parameters:
|
audpc100S |
the audpc in a fully susceptible landscape (used as reference value for graphics). |
writeTXT |
a logical indicating if the output is written in a text file (TRUE) or not (FALSE). |
graphic |
a logical indicating if a tiff graphic of the output is generated (only if more than one year is simulated). |
path |
path of text file (if writeTXT = TRUE) and tiff graphic (if graphic = TRUE) to be generated. |
Outputs are computed every year for every cultivar as well as for the whole landscape.
The epidemiological impact of pathogen spread can be evaluated by different measures:
Area Under Disease Progress Curve (AUDPC): average number of diseased host individuals (status I + R) per time step and square meter.
Relative Area Under Disease Progress Curve (AUDPCr): average proportion of diseased host individuals (status I + R) relative to the total number of existing hosts (H+L+I+R).
Green Leaf Area (GLA): average number of healthy host individuals (status H) per time step and per square meter.
Relative Green Leaf Area (GLAr): average proportion of healthy host individuals (status H) relative to the total number of existing hosts (H+L+I+R).
Contribution of pathogen genotypes: for every year and every host (as well as for the whole landscape and the whole simulation duration), fraction of cumulative LIR infections attributed to each pathogen genotype.
The economic outcome of a simulation can be evaluated using:
Crop yield: yearly crop yield (e.g. grains, fruits, wine) in weight (or volume) units per hectare (depends on the number of productive hosts and associated theoretical yield).
Crop products: yearly product generated from sales, in monetary units per hectare (depends on crop yield and market value). Note that when disease = "mildew" a price reduction between 0% and 5% is applied to the market value depending on disease severity.
Operational crop costs: yearly costs associated with crop planting (depends on initial host density and planting cost) and pesticide treatments (depends on the number of applications and the cost of a single application) in monetary units per hectare.
Crop margin, i.e. products - operational costs, in monetary units per hectare.
A list containing, for each required type of output, a matrix summarising the output for each year and cultivar (as well as the whole landscape). Each matrix can be written in a txt file (if writeTXT=TRUE), and illustrated in a graphic (if graphic=TRUE).
Rimbaud L., Papaïx J., Rey J.-F., Barrett L. G. and Thrall P. H. (2018). Assessing the durability and efficiency of landscape-based strategies to deploy plant resistance to pathogens. PLoS Computational Biology 14(4):e1006067.
evol_output
## Not run:
demo_landsepi()
## End(Not run)
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