lambda_matrix: Lambda estimates using demographic data in a matrix approach

In NathanWhitmore/harvest: Visualising the Sustainability of a Wildlife Harvest

Lambda estimates using demographic data in a matrix approach

Description

A calculation of the finite rate of increase (lambda) using a simplied population projection matrix approach based on basic demographic data.

The model based on demographic data: age of first basic reproduction, number of female offspring per female, maximum age of reproduction, and two pieces of empirical survival data: 1) the juvenile survival rate through to adulthood, and 2) annual survival rate for adults.

Usage

lambda_matrix(r.stage, b, stages, terminal)

Arguments

r.stage	Stage in which first reproduction occurs
b	Number of female offspring per female
stages	Number of distinct survival/fecundity stages
S	Vector of stage specific survival rates
terminal	Logical - whether all adults die after reaching final stage

Details

If the stages of matrix are set to represent age and there is obligate death of adults (terminal = TRUE) then the finite rate of increase should be equivalent to that generated by the lambda_PM function ( equivalent to the "PM" equiation of Slade et al (1998)

Value

Returns an estimate of the finite rate of increase for a given population based on the juvenile survival rate through to adulthood, and the adult annual survival rate.

Author(s)

Nathan Whitmore

References

Slade, N. A., Gomulkiewicz, R., & Alexander, H. M. (1998). Alternatives to Robinson and Redford's method of assessing overharvest from incomplete demographic data. Conservation Biology, 12(1), 148-155.

Examples

# e.g. life history data from Ochotona princeps (Slade et al. 1998)
# in which each stage is equivalent to a year
# such that r.stage is equivalent to age of first reproduction
# and number of stages is the maximum age of reproduction

lambda_matrix(
  r.stage = 1,  # stage of first reproduction
  b = 3.25,  # number of female offspring per female
  stages = 6 , # number of stages
  S = c(0.11,rep(0.7,5)),  # survival rate vector
  terminal = TRUE
)

NathanWhitmore/harvest documentation built on Feb. 15, 2023, 2:28 p.m.