Description Usage Arguments Details Value Author(s) Examples
View source: R/IPMpack-Analyses.r
Function to project a population forwards using an IPM and a starting environment. The IPM may be structured by continuous (e.g. size) stage alone, or by continuous stage and environment.
1 | predictFutureDistribution(startingSizes, IPM, n.time.steps, startingEnv = 1)
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startingSizes |
vector containing the sizes of the desired starting population. |
IPM |
an IPMmatrix object (P matrix if only interested in survival projections, P matrix+ F matrix otherwise). |
n.time.steps |
a numeric defining the number of time steps for which projection is required. |
startingEnv |
vector defining the desired starting environment, of length one or length startingSizes; ignored if no environmental states are provided; otherwise if the length is less than startingSizes assumes all individuals start in the same environment, given by startingEnv[1]. |
Currently this does not accept IPMs with discrete stages (e.g. seedbank).
n.new.dist0 |
starting frequency distribution along meshpoints in IPMmatrix. |
n.new.dist |
final frequency distribution. |
C. Jessica E. Metcalf, Sean M. McMahon, Roberto Salguero-Gomez, Eelke Jongejans & Cory Merow.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | # Define starting population of interest
startPop <- rnorm(1000,2,1)
# Build T and F matrix
dff <- generateData()
Pmatrix <- makeIPMPmatrix(minSize = 1.1*min(dff$size, na.rm = TRUE),
maxSize = 1.1*max(dff$size, na.rm = TRUE), growObj = makeGrowthObj(dff),
survObj = makeSurvObj(dff), correction = "constant")
Fmatrix <- makeIPMFmatrix(minSize = 1.1*min(dff$size, na.rm = TRUE),
maxSize = 1.1*max(dff$size, na.rm = TRUE),
fecObj = makeFecObj(dff, fecConstants = data.frame(est=0.7), Transform="log"),
correction="constant")
# Make an IPMmatrix object containing P matrix + F matrix
# by replacing the P matrix
IPM <- Pmatrix
IPM@.Data <- Pmatrix + Fmatrix
# Project population five steps
a5 <- predictFutureDistribution(startingSizes = startPop, IPM = IPM,
n.time.steps = 5, startingEnv = 1)
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