IPMpack (version 1.6)

trackPopStructManyCov: Tracks population structure in a stochastic environment.

Description

Provided a set of time-varying covariates, projects the population forward, and stores state of the population.

Usage

trackPopStructManyCov(covariate, nRunIn, tMax, growthObj, survObj, fecObj, 
nBigMatrix, minSize, maxSize, nMicrosites, integrateType, correction)

Arguments

covariate

matrix with tMax rows, and as many columns as there are relevant covariates.

nRunIn

numeric, number of initial samples to discard.

tMax

numeric, total number of time-steps to run (same as ncol(covariate)).

growthObj

a growth object, defined to correspond to covariate definition (indexing used to make the growth object must match up).

survObj

a survival object, defined to correspond to covariate definition in covariate.

fecObj

a fecundity object, defined to correspond to covariate definition in covariate.

nBigMatrix

numeric, number of size bins in the IPM.

minSize

numeric, minimum size in the IPM

maxSize

numeric, maximum size in the IPM.

nMicrosites

vector, if sum(nMicrosites) > 0 then density dependence is assumed to operate on seedling establishment, and if length(nMicrosites) > 1, then the number of microsites available for establishment at time t is nMicrosites[min(t,length(nMicrosites))].

integrateType

integration type, defaults to "midpoint" (which uses probability density function); other option is "cumul" (which uses the cumulative density function).

correction

correction type, defaults to "none"; option is "constant" which will multiply every column of the IPM by a constant sufficient to adjust values to those predicted for survival at that size.

Value

• rc
  matrix of the numbers of individuals in each size and seed class (row) over time (columns).
• IPM.here
  IPM constructed corresponding to pop structure and covariates at tMax.

See Also

stochGrowthRateManyCov

Examples

### NOT RUN ####

# Generate relevant data, build objects
#dff <- generateDataStoch()
#print(head(dff))
#gr1 <- makeGrowthObj(dff, Formula = sizeNext~size+size2+covariate1)
#sv1 <- makeSurvObj(dff, Formula = surv~size+size2+covariate2)
#fv1 <- makeFecObj(dff, Formula =fec~size+size2,Transform="log")

# Generate time series of covariates for which growth rate is required
# here set to be seasonal environment. NOTE that the order of covariates
# is the same as in dff
#tVals <- seq(1, 20, by = 1/12)
#covTest <- (1 + 0.5*sin(2*pi*tVals))
#covMatTest <- data.frame(covariate1 = rnorm(length(covTest), covTest, 0.5) - 1, 
#covariate2 = rnorm(length(covTest),covTest,0.5) - 1, 
#covariate3 = rnorm(length(covTest), covTest,0.5) - 1)

#st <- trackPopStructManyCov(covariate = covMatTest, nRunIn = 2*10, 
#tMax = length(tVals), growthObj = gr1, survObj = sv1, fecObj = fv1, 
#nBigMatrix = 100, minSize = 2*min(dff$size, na.rm = TRUE), 
#maxSize = 1.5*max(dff$size, na.rm = TRUE), nMicrosites = 0)

# Function to plot output
#plotResultsStochStruct(tVals = tVals, st = st, covTest = covTest)