birthFunction {rSHAPE}

This function calculates the number of births for the vector of populations which are expected to be passed. The number of parameters which can be passed may be more than the number required to use one of the growth forms.

Description

This function calculates the number of births for the vector of populations which are expected to be passed. The number of parameters which can be passed may be more than the number required to use one of the growth forms.

Usage

birthFunction(func_inSize, func_inFitness, func_bProb, func_sizeStep,
  func_growthForm = c("logistic", "exponential", "constant", "poisson"),
  func_deaths = NULL, func_carryingCapacity = NULL,
  func_basalRate = NULL, func_deathScale = FALSE, func_drift = TRUE,
  func_roundValues = TRUE)

Arguments

func_inSize

This is the vector of population sizes within the community

func_inFitness

This is the vector of fitness value for the community

func_bProb

This is the general bith probability defined for this run of SHAPE

func_sizeStep

This is a proportional scalar that will control what proportion of a standard "generation" is simulated for each step within a SHAPE run. NOTE: This parameter is not perfectly validated to run as may be expected with all models. For now, it should be left as a value of "1", but exists for future implementation and testing.

func_growthForm

This is the implemeted growth model to be simulated in this run. Currently this can be one of "logistic","exponential","constant","poisson".

func_deaths

This is the vector of deaths for the genotypes within the community

func_carryingCapacity

This is the maximum community size supported by tge simulated environment.

func_basalRate

This is the basal growth rate, otherwise definable as the number of offspring an individual will produce from a single birth event.

func_deathScale

This is a logical toggle to define if the number of births should be scaled by the number of deaths. The exact interpretation of this varies by growth model, but in general it forces growth to follow rates expected by standard pure birth models while still simulating deaths within the community.

func_drift

This is a logical toggle as to whether or not stochasticity is introduced into the deterministic calculations that may be encountered within the growth function. Its exact implementation varies based on the growth model being simulated.

func_roundValues

This is a logical toggle to define if the number of births and deaths are forced to be tracked as integer values. If TRUE, then any fractional amounts will be stochastically rounded to the nearest integer with a probability of being rounded up equal to the decimal value – ie: 0.32 means 32% chance of being rounded up –

Value

A vector of births with the same length as the vector of population sizes passed.

# Imagine you've got an evolving community of three populations where in each time step individuals with # relateive fitness of 1 produce 2 offspring. birthFunction(func_inSize = c(100,100,100), func_inFitness = c(1,2,1.05), func_bProb = 1, func_sizeStep = 1, func_growthForm = "exponential", func_drift = FALSE) # Now with evolutionary drift birthFunction(func_inSize = c(100,100,100), func_inFitness = c(1,2,1.05), func_bProb = 1, func_sizeStep = 1, func_growthForm = "exponential", func_drift = TRUE)