Create a Leslie matrix population model

The function creates a Leslie matrix from inputs of number of stages, fecundity (the top row of the matrix), and survival probability (the value in the sub-diagonal).

Usage

make_leslie_mpm(
  survival = NULL,
  fecundity = NULL,
  n_stages = NULL,
  lifetable = NULL,
  split = FALSE
)

Arguments

survival

a numeric value representing the survival probability of each stage along the lower off-diagonal of the matrix, with the final value being in the lower-right corner of the matrix. If only one value is provided, this is applied to all survival elements.

fecundity

a numeric vector of length n_stages representing the reproductive output of each stage. If only one value is provided, this is applied to all fecundity elements.

n_stages

a numeric value representing the number of stages in the matrix

lifetable

a life table containing columns px (age-specific survival) and fecundity (age-specific fecundity).

split

a logical argument indicating whether the output matrix should be split into separate A, U and F matrices (where A = U + F).

Value

A matrix of size n_stages x n_stages representing the Leslie matrix

References

Caswell, H. (2001). Matrix Population Models: Construction, Analysis, and Interpretation. Sinauer.

Leslie, P. H. (1945). On the use of matrices in certain population mathematics. Biometrika, 33 (3), 183–212.

Leslie, P. H. (1948). Some Further Notes on the Use of Matrices in Population Mathematics. Biometrika, 35(3-4), 213–245.

See also

• model_survival() to model age-specific survival using mortality models.

• model_fecundity() to model age-specific reproductive output using various functions.

Other Leslie matrices: rand_leslie_set(), reorganise_matrices()

Author

Owen Jones jones@biology.sdu.dk

Examples

make_leslie_mpm(
  survival = 0.5, fecundity = c(0.1, 0.2, 0.3),
  n_stages = 3, split = FALSE
)
#>      [,1] [,2] [,3]
#> [1,]  0.1  0.2  0.3
#> [2,]  0.5  0.0  0.0
#> [3,]  0.0  0.5  0.5
make_leslie_mpm(
  survival = c(0.5, 0.6, 0.7), fecundity = c(0.1, 0.2, 0.3),
  n_stages = 3
)
#>      [,1] [,2] [,3]
#> [1,]  0.1  0.2  0.3
#> [2,]  0.5  0.0  0.0
#> [3,]  0.0  0.6  0.7
make_leslie_mpm(
  survival = seq(0.1, 0.7, length.out = 4), fecundity = 0.1,
  n_stages = 4
)
#>      [,1] [,2] [,3] [,4]
#> [1,]  0.1  0.1  0.1  0.1
#> [2,]  0.1  0.0  0.0  0.0
#> [3,]  0.0  0.3  0.0  0.0
#> [4,]  0.0  0.0  0.5  0.7
make_leslie_mpm(
  survival = c(0.8, 0.3, 0.2, 0.1, 0.05), fecundity = 0.2,
  n_stages = 5
)
#>      [,1] [,2] [,3] [,4] [,5]
#> [1,]  0.2  0.2  0.2  0.2 0.20
#> [2,]  0.8  0.0  0.0  0.0 0.00
#> [3,]  0.0  0.3  0.0  0.0 0.00
#> [4,]  0.0  0.0  0.2  0.0 0.00
#> [5,]  0.0  0.0  0.0  0.1 0.05