simulateCarlina: Generates random data in the form used by IPMpack based on...

In IPMpack: Builds and analyses Integral Projection Models (IPMs).

Description

Simulates growth, survival and fecundity and density dependent seedling establishment to create a dataframe of the form required by the functions and methods used in IPMpack. Demographic stage data is only continuous. Note that the number or rows corresponding to each year of the data-frame does not inform about population size, since rows exist that correspond to offspring appearing in the subsequent year.

Usage

simulateCarlina(nSamp=200,nYrs=1000,nSampleYrs=15,
		m0=-1.37,ms=0.59,
		b0=-12.05,bs=3.64,
		A=-1,B=2,
		ag=1.14,bg=0.74,sig=0.29,
		mean.kids=3.16,sd.kids=0.5,
		meanYear=c(0,0,0),
		matVarYear=matrix(c(1.03,0,0,0,0.037,0.041,0,0.041,0.075),3,3),
		varA=0,varB=0,densDep=TRUE,
		maxPerYr=1000,maxStoreSeedlingsPerYr=200,
		sizes = c())

Arguments

nSamp	number of samples desired in the base population, defaults to 2000
nYrs	number of years in the simulation, defaults to 1000
nSampleYrs	number of years sampled, defaults to 15
m0	intercept survival
ms	slope survival
b0	intercept flowering
bs	slope flowering
A	intercept reproductive allometry seed production
B	slope reproductive allometry seed production
ag	intercept growth
bg	slope growth
sig	variance growth
mean.kids	mean kid size
sd.kids	variance kid size
meanYear	mean year effects
matVarYear	var-covariance in year effects for survival, growth and offspring size
varA	variance in seed intercept year effects - defaults to zero
varB	variance in seed slope year effects - defaults to zero
densDep	density dependence in seedling establishment or not?
maxPerYr	total number of individuals for which measurements will be transferred to the subsequent year (population will be resampled with replacement to obtain a population of this size)
maxStoreSeedlingsPerYr	max number of seedling recruits for which data will be stored in every year
sizes	starting sizes in the population (optional)

Value

A list including: dataf: A dataframe with headings: - "size": continuous variable, indicating current size. - "sizeNext" continuous variable, indicating size in the next time step. - "surv": boolean, indicating whether individual survived or not to the next time step. - "covariate": discrete covariate. - "covariateNext": discrete covariate in the next time step. - "fec": continuous variable, indicating fecundity. - nSeedlings: number seedlings corresponding to that year - m.year: intercept of mortality for that year - cg.year: intercept of growth for that year - b.year: intercept of offspring size for that year - offspringNext: where the row corresponds to offspring, this takes the value offspringNexxt - year: year of the sample

list.par: - a list of all the other parameters matVarYear - variance covariance matrix for demographic functions trueGrow - stochastic growth rate, log lambda s meantrueGrow - mean of lambda t vartrueGrow - variance of log lambda t

Author(s)

C. Jessica E. Metcalf, Sean M. McMahon, Roberto Salguero-Gomez, Eelke Jongejans & Cory Merow.

See Also

generateData

Examples

#Uncomment to run
#dff <- simulateCarlina(nSamp=1000)
#head(dff$dataf)

IPMpack documentation built on May 2, 2019, 2:36 a.m.