lefko3 (version 3.3.2)

slambda3: Estimate Stochastic Population Growth Rate

Description

Function slambda3() estimates the stochastic population growth rate, \(a\), defined as the long-term arithmetic mean of the log population growth rate estimated per simulated time (as given in equation 2 in Tuljapurkar, Horvitz, and Pascarella 2003). This term is estimated via projection of randomly sampled matrices, similarly to the procedure outlined in Box 7.4 of Morris and Doak (2002). Can handle both lefkoMat objects and lists of full A matrices.

Usage

slambda3(mpm, times = 10000L, tweights = NULL)

Arguments

mpm

A matrix projection model of class lefkoMat, or a list of full matrix projection matrices.

times

Number of iterations to random samples. Defaults to 10,000.

tweights

Numeric vector denoting the probabilistic weightings of annual matrices. Defaults to equal weighting among times.

Value

A data frame with the following variables:

pop

The identity of the population.

patch

The identity of the patch.

a

Estimate of stochastic growth rate, estimated as the arithmetic mean of the log population growth rate across simulated times.

var

The estimated variance of a.

sd

The standard deviation of a.

se

The standard error of a.

Stochastic growth rate is estimated both at the patch level and at the population level. Population level estimates will be noted at the end of the data frame with 0 entries for patch designation.

Notes

Weightings given in tweights do not need to sum to 1. Final weightings used will be based on the proportion per element of the sum of elements in the user-supplied vector.

Examples

# NOT RUN {
data(cypdata)
 
sizevector <- c(0, 0, 0, 0, 0, 0, 1, 2.5, 4.5, 8, 17.5)
stagevector <- c("SD", "P1", "P2", "P3", "SL", "D", "XSm", "Sm", "Md", "Lg",
  "XLg")
repvector <- c(0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1)
obsvector <- c(0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1)
matvector <- c(0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1)
immvector <- c(0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0)
propvector <- c(1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
indataset <- c(0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1)
binvec <- c(0, 0, 0, 0, 0, 0.5, 0.5, 1, 1, 2.5, 7)

cypframe_raw <- sf_create(sizes = sizevector, stagenames = stagevector,
  repstatus = repvector, obsstatus = obsvector, matstatus = matvector, 
  propstatus = propvector, immstatus = immvector, indataset = indataset,
  binhalfwidth = binvec)

cypraw_v1 <- verticalize3(data = cypdata, noyears = 6, firstyear = 2004,
  patchidcol = "patch", individcol = "plantid", blocksize = 4, 
  sizeacol = "Inf2.04", sizebcol = "Inf.04", sizeccol = "Veg.04", 
  repstracol = "Inf.04", repstrbcol = "Inf2.04", fecacol = "Pod.04",
  stageassign = cypframe_raw, stagesize = "sizeadded", NAas0 = TRUE, 
  NRasRep = TRUE)

rep_cyp_raw <- matrix(0, 11, 11)
rep_cyp_raw[1:2,7:11] <- 0.5

cypover3r <- overwrite(stage3 = c("SD", "SD", "P1", "P1", "P2", "P3", "SL", 
    "SL", "SL", "D", "XSm", "Sm", "D", "XSm", "Sm"), 
  stage2 = c("SD", "SD", "SD", "SD", "P1", "P2", "P3", "SL", "SL", "SL", 
    "SL", "SL", "SL", "SL", "SL"),
  stage1 = c("SD", "rep", "SD", "rep", "SD", "P1", "P2", "P3", "SL", "P3", 
    "P3", "P3", "SL", "SL", "SL"),
  eststage3 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, "D", "XSm", "Sm", "D", 
    "XSm", "Sm"), 
  eststage2 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, "XSm", "XSm", "XSm", 
    "XSm", "XSm", "XSm"), 
  eststage1 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, "XSm", "XSm", "XSm", 
    "XSm", "XSm", "XSm"), 
  givenrate = c(0.1, 0.1, 0.2, 0.2, 0.2, 0.2, 0.25, 0.4, 0.4, NA, NA, NA, 
    NA, NA, NA), 
  type = c("S", "S", "S", "S", "S", "S", "S", "S", "S", "S", "S", "S", "S", 
    "S", "S"))

cypmatrix3r <- rlefko3(data = cypraw_v1, stageframe = cypframe_raw, 
  year = "all", patch = "all", stages = c("stage3", "stage2", "stage1"),
  size = c("size3added", "size2added", "size1added"), 
  repmatrix = rep_cyp_raw, overwrite = cypover3r, yearcol = "year2", 
  patchcol = "patchid", indivcol = "individ")

cypstoch <- slambda3(cypmatrix3r)
cypstoch

# }