Use statistically estimated maxB, maxANPP and establishment probabilities to generate specieEcoregion table.

makeSpeciesEcoregion(
  cohortDataBiomass,
  cohortDataShort,
  cohortDataShortNoCover,
  species,
  modelCover,
  modelBiomass,
  successionTimestep,
  currentYear
)

Arguments

cohortDataBiomass

a subset of cohortData

cohortDataShort

a subset of cohortData

cohortDataShortNoCover

a subset of cohortData

species

a data.table of species traits, e.g., longevity, shade tolerance, etc.

modelCover

statistical model of species presence/absence

modelBiomass

statistical model of species biomass

successionTimestep

The time between successive seed dispersal events.

currentYear

time(sim)

Details

See Details.

establishprob

This section takes the cover as estimated from the mature tree cover and partitions it between resprouting and seeds Unfortunately, establishment by seed is not independent of resprouting, i.e., some pixels would have both Since we don't know the level of independence, we can't correctly assess how much to discount the two. If there is resprouting > 0, then this is the partitioning: establishprob = f(establishprob + resproutprob + jointEstablishProbResproutProb) If jointEstablishProbResproutProb is 0, then these are independent events and the total cover probability can be partitioned easily between seeds and resprout. This is unlikely ever to be the case. We are picking 50 a number that is better than 0 (totally independent probabilities, meaning no pixel has both seeds and resprout potential) and 100 dependent probabilities, i.e., every pixel where there is seeds will also be a pixel with resprouting) This is expressed with the "* 0.5" in the code.

#' @return A speciesEcoregion data.table with added columns for parameters maxB, maxANPP and establishprob