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fireSense Manual: v. 0.0.0.9000

9 fireSense_SpreadPredict Module

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9.0.0.1 Authors:

Jean Marchal [aut], Eliot McIntire [aut, cre], Tati Michelleti [aut], Ian Eddy [aut], Alex M. Chubaty [ctb]

9.1 Module Overview

9.1.1 Module summary

Predicts a surface (raster) of fire spread probabilities using a model previously fit with fireSense_SpreadFit. fireSense (Marchal et al. 2017b, a; 2019)

9.1.2 Module inputs and parameters

Describe input data required by the module and how to obtain it (e.g., directly from online sources or supplied by other modules) If sourceURL is specified, downloadData("fireSense_SpreadPredict", "..") may be sufficient.

Table 9.1 shows the full list of module inputs.

Table 9.1: Table 9.2: List of fireSense_SpreadPredict input objects and their description.
objectName objectClass desc sourceURL
covMinMax_spread data.table range used to rescale coefficients during spreadFit NA
fireSense_SpreadCovariates data.table data.table of covariates with pixelID column corresponding to flammableRTM index. NA
fireSense_SpreadFitted fireSense_SpreadFit An object of class ‘fireSense_SpreadFit’ created by the fireSense_SpreadFit module. NA
flammableRTM SpatRaster RTM with nonflammable pixels coded as 0 and flammable as 1. NA

Summary of user-visible parameters (Table 9.3)

Table 9.3: Table 9.4: List of fireSense_SpreadPredict parameters and their description.
paramName paramClass default min max paramDesc
climCol character MDC NA NA the name of the climate covariate in sim$fireSense_spreadCovariates
coefToUse character meanCoef NA NA Which coefficient to use to predict? The best coefficient (bestCoef) from DEOPtim or the average (meanCoef; default).
lowerSpreadProb numeric 0.13 NA NA Lower spread probability
mutuallyExclusiveCols list vegPC NA NA a named list, where the name of the list must be a covariate in the data.table. Covariates matching the values in each list element will be set to 0. List content should be a grep regex.
.runInitialTime numeric 0 NA NA when to start this module? By default, the start time of the simulation.
.runInterval numeric 1 NA NA optional. Interval between two runs of this module, expressed in units of simulation time.Defaults to 1 year.
.saveInitialTime numeric NA NA NA optional. When to start saving output to a file.
.saveInterval numeric NA NA NA optional. Interval between save events.
.useCache logical FALSE NA NA Should this entire module be run with caching activated? This is generally intended for data-type modules, where stochasticity and time are not relevant

9.1.3 Events

  • Module initiation;
  • Make predictions.

9.1.4 Plotting

Write what is plotted.

9.1.5 Saving

There is currently nothing saved, but this may change in the future.

9.1.6 Module outputs

Description of the module outputs (Table 9.5).

Table 9.5: Table 9.6: List of fireSense_SpreadPredict outputs and their description.
objectName objectClass desc
fireSense_SpreadPredicted SpatRaster A raster layer of spread probabilities

9.2 References

Marchal, J., Cumming, S.G. & McIntire, E.J.B. (2017a). Exploiting Poisson additivity to predict fire frequency from maps of fire weather and land cover in boreal forests of Québec, Canada. Ecography, 40, 200–209.
Marchal, J., Cumming, S.G. & McIntire, E.J.B. (2017b). Land cover, more than monthly fire weather, drives fire-size distribution in Southern Québec forests: Implications for fire risk management. PLoS ONE, 12, 1–17.
Marchal, J., Cumming, S.G. & McIntire, E.J.B. (2019). Turning Down the Heat: Vegetation Feedbacks Limit Fire Regime Responses to Global Warming. Ecosystems.