drawSubmodelEffects: Draw submodel effects

In miquelcaceres/IFNdyn: IFN forest dynamics and scenario analysis

Description

Draws the effect of individual variables on the predictions of a specific submodel of forest dynamics

Usage

drawSubmodelEffects(
  species,
  submodel = "growth",
  predictor = "DBH",
  rem.flat = TRUE
)

Arguments

species	Character vector of species codes to be studied.
submodel	Submodel to be studied. Either "growth", "survival", "survivalPG", "ingrowth", "ingrowthdisp", "ingrowthB", "ingrowthBdisp", "ingrowthN", "ingrowthNdisp", "height" or "heightgrowth".
predictor	String with the predictor whose effect is to be studied: DBH: Tree diameter. H: Tree height. H/D: Tree height to diameter ratio. N: Stand density. Nsp.N: Proportion of the target species. G: Stand's basal area. DBHincprev: DBH increment of the previous 10-yr timestep. BAL: Basal area of larger trees. SWHC: Soil water holding capacity. Rad: Annual radiation (daily mean). Temp: Mean annual temperature. Prec: Mean annual precipitation (mm). PET: Mean annual potential evapotranspiration (mm). P/PET: Moisture index (P/PET). slope: Slope (degrees). elevation: Elevation (m).
rem.flat	A flag to indicate that species with no response to the chosen predictor should be excluded from the plot

Details

The function uses species mean values for the non-target predictors. Ingrowth is modelled in two stages. Hence, the effect of particular predictors can be drawn for: (a) the binomial model to predict presence of ingrowth ('ingrowthB' or 'ingrowthBdisp'); (b) the density of ingrowth conditional to presence ('ingrowthN' or 'ingrowthNdisp'); (c) the density of ingrowth resulting from multiplying the two previous predictions ('ingrowth' or 'ingrowthdist'). In addition, two sets of ingrowth models are provided, either without or including dispersal effects.

Examples

pines = c("21", "22", "23", "24", "25", "26", "27","28","31","17")
oaks = c("45", "46", "44", "41", "43", "71","72")
other = c("51", "55","60", "73", "3","37", "38", "36", "83", "80")
drawSubmodelEffects(species = pines, predictor = "DBH", submodel = "growth")
drawSubmodelEffects(species = oaks, predictor = "DBH", submodel = "growth")
drawSubmodelEffects(species = other, predictor = "DBH", submodel = "growth")

miquelcaceres/IFNdyn documentation built on Feb. 1, 2021, 10:55 a.m.