IFNsubmodels: Dynamic model components
In miquelcaceres/IFNdyn: IFN forest dynamics and scenario analysis

Description Usage Arguments Details Value References See Also Examples

Set of basic model functions to simulate forest dynamics in IFN plots:

IFNgrowth estimates growth as tree diameter increment or basal area increment.
IFNsurvival estimates survival probabilities.
IFNsurvivalPG estimates survival probabilities including previous diameter growth as predictor.
IFNingrowth estimates tree ingrowth densities and average diameters.
IFNingrowthdisp estimates tree ingrowth densities and average diameters taking into account spatial context.
IFNheight estimates height of trees (in m).
IFNheightgrowth estimates tree height increment (in m).
IFNfire estimates burning probability at the stand level and probability of death at the tree level.

IFNgrowth(
  treeData,
  plotData,
  numYears = 10,
  params = "defaultGrowthParams",
  response = "DI",
  prepared = FALSE,
  useProvince = TRUE,
  useRP = TRUE,
  stochastic = FALSE,
  verbose = FALSE
)

IFNsurvival(
  treeData,
  plotData,
  numYears = 10,
  params = "defaultSurvivalParams",
  prepared = FALSE,
  killVeryLargeTrees = TRUE,
  verbose = FALSE
)

IFNsurvivalPG(
  treeData,
  plotData,
  numYears = 10,
  params = "defaultSurvivalPGParams",
  prepared = FALSE,
  killVeryLargeTrees = TRUE,
  verbose = FALSE
)

IFNingrowth(
  treeData,
  plotData,
  numYears = 10,
  paramsB = "defaultIngrowthBParams",
  paramsN = "defaultIngrowthNParams",
  paramsDBH = "defaultIngrowthDBHParams",
  prepared = FALSE,
  stochastic = FALSE,
  thresholdIngrowth = FALSE,
  speciesNames = TRUE,
  verbose = FALSE
)

IFNingrowthdisp(
  treeData,
  plotData,
  nb,
  NspNmatrix,
  numYears = 10,
  paramsB = "defaultIngrowthBParams_disp",
  paramsN = "defaultIngrowthNParams_disp",
  paramsDBH = "defaultIngrowthDBHParams_disp",
  prepared = FALSE,
  stochastic = FALSE,
  thresholdIngrowth = FALSE,
  speciesNames = TRUE,
  verbose = FALSE
)

IFNheight(
  treeData,
  plotData,
  params = "defaultHeightParams",
  useProvince = TRUE,
  useRP = TRUE,
  verbose = FALSE
)

IFNheightgrowth(
  treeData,
  plotData,
  numYears = 10,
  params = "defaultHeightGrowthParams",
  prepared = FALSE,
  useProvince = TRUE,
  useRP = TRUE,
  stochastic = FALSE,
  verbose = FALSE
)

IFNfire(treeData, plotData)

`treeData`	A data frame with tree records in rows and columns 'ID', 'Species', 'DBH' (in cm) and 'N' (ha-1). Additionally, column 'OIFFIN' may be defined to indicate trees that are signaled to be cut during the following step.
`plotData`	A data frame with plot 'ID' in rows and columns 'SWHC' (mm), 'Rad' (MJ), 'Temp' (degrees C) and 'slope' (degrees).
`numYears`	An integer or integer vector with the number of years corresponding to one time step (by default 10-yr time steps are assumed)
`params`	Name of parameter data set or data frame with parameter values per species
`response`	Type of output: "BAI" (basal area increment, cm2), "DI" (diameter increment, cm) or "DBH" (new diameter at breast height, cm)
`prepared`	A flag to indicate that `treeData` is the result of calling function `prepareTreeCompetitionTable` (for `IFNgrowth` and `IFNsurvival`), `prepareSpeciesCompetitionTable` (for `IFNingrowth`) or `prepareSpatialSpeciesCompetitionTable` (for `IFNingrowthdisp`). Otherwise these functions are called internally.
`useProvince`	A flag to indicate that province information should be used in growth/height estimation.
`useRP`	A flag to indicate that "region de procedencia" should be used in growth/height estimation
`stochastic`	A flag to indicate that simulation of growth, mortality and ingrowth should be stochastic (i.e. non-deterministic)
`verbose`	A flag to indicate console output of the process
`killVeryLargeTrees`	Flag to indicate that trees with diameters larger than species-specific thresholds should be forced to die.
`paramsB`	Name of binomial model parameter data set or data frame with parameter values per species
`paramsN`	Name of Gamma model parameter data set or data frame with parameter values per species
`paramsDBH`	Name of Gamma model parameter data set or data frame with parameter values per species
`thresholdIngrowth`	Boolean flag to indicate that ingrowth should occur only when a given probability threshold is surpassed.
`speciesNames`	A flag to include species names in the output
`nb`	An object of class `listw` (see functions `IFNknn` and `nb2listw`).
`NspNmatrix`	A numeric matrix with the density proportion of each species (columns) in each plot (rows).

All functions check whether plot IDs in treeData exist as row names of plotData and whether species codes in treeData have models defined. If plotData contains field 'Province', this will be used to overwrite any province especification in treeData. Option stochastic = TRUE causes the models to be run in stochastic mode, which means that: (a) binomial draws are made for each tree to determine survival; (b) predicted growth (e.g. diameter increment) is stochastic (Gamma distribution); (c) Ingrowth density is stochastic (Gamma distribution coupled to a binomial draw); (d) Ingrowth diameter is stochastic (Gamma distribution). Stochasticity is not available for IFNsurvival and IFNsurvivalPG because these function return survival probabilities. Function IFNheight is only deterministic, because it is a static model. Function IFNfire implements the fire probability model of González et al. (2006) and the fire damage model of González et al. (2007), both calibrated for Catalonia. Height growht estimates of function IFNheightgrowth return NA values whenever the province is not included in the set of provinces with enough data to define height growth models for the target species.

Depends on the function:

IFNgrowth returns a vector with basal area increment (in cm2), diameter increments (in cm) or new diameter values (in cm).
IFNsurvival and IFNsurvivalPG return a vector with survival probabilities (0-1).
IFNingrowth and IFNingrowthdisp return a data frame with new tree records in rows and columns 'ID', 'Species', ('Name'), 'N' and 'DBH'.
IFNheight return a vector with height values (in m).
IFNheightgrowth return a vector with height increment values (in m).
IFNfire returns a list with two elements: (1) 'stand' is a data frame with as many rows as plots and columns 'Pfire10' (probability of burning in 10 year interval), 'fire' stochastic trial of fire occurrence and 'Pdead' proportion of trees dead; (2) 'tree' is a data frame with columns 'Psurv' (the probability of survival for each tree in each stand, following the order of 'treeData') and 'Psurv' (the probability of survival for each tree in each stand that burned in the stochastic trial, otherwise NA).

González, J.R., Trasobares, A., Palahí, M., Pukkala, T., 2007. Predicting stand damage and tree survival in burned forests in Catalonia (North-East Spain). Ann. For. Sci. 64, 733–742. https://doi.org/10.1051/forest

González, J.R., Palahí, M., Trasobares, A., Pukkala, T., 2006. A fire probability model for forest stands in Catalonia (north-east Spain). Ann. For. Sci. 63, 169–176. https://doi.org/10.1051/forest:2005109

IFNdynamics, prepareTreeCompetitionTable

# Load example tree data (two forest plots)
data(exampleTreeData)
head(exampleTreeData)

# Load IFN environmental data
data(plotDataIFN)
head(plotDataIFN)

# Load Regiones de Procedencia for IFN plots
data(plotRPIFN)

# Add Regiones de Procedencia to plot data
plotDataIFN = cbind(plotDataIFN, plotRPIFN)

# (1) Growth
IFNgrowth(exampleTreeData, plotDataIFN)

# (2) Survival probabilities
IFNsurvival(exampleTreeData, plotDataIFN)

# (3) Ingrowth model (local recruiment)
IFNingrowth(exampleTreeData, plotDataIFN)

# (4) Ingrowth model (colonization)
data(examplePlotCoords)
nb = IFNknn(examplePlotCoords, k = 1)
Nmatrix = tapply(exampleTreeData$N, list(exampleTreeData$ID, exampleTreeData$Species),
                 sum, na.rm=T)
NspNmatrix = sweep(Nmatrix, 1, rowSums(Nmatrix, na.rm=T), "/")
NspNmatrix = rbind(NspNmatrix,c(0.5, NA, NA, NA))
rownames(NspNmatrix)[4] = "80003"
NspNmatrix = cbind(NspNmatrix, c(NA,NA,NA,0.5))
colnames(NspNmatrix)[5] = "25"
IFNingrowthdisp(exampleTreeData, plotDataIFN, nb, NspNmatrix)

# (5) Static height model
IFNheight(exampleTreeData, plotDataIFN)

# (6) Height increment model
IFNheightgrowth(exampleTreeData, plotDataIFN)

# (7) Stochastic fire model
IFNfire(exampleTreeData, plotDataIFN)