How to pertubate the fecundity rates of a deterministic matrix model using the popdemo package in R?

See the FAQ: How to do a minimal reproducible example reprex for beginners. To address the problem as stated, the objects delta and data need to be known, and it's not clear that the matrix

m <- structure(c(0, 0.369, 0, 0, 0, 0, 0, 0, 0.232, 0, 0, 0, 0, 0, 0, 0.207, 0, 0, 0, 0, 0, 0, 0.047, 0, 0, 0, 0, 0, 0, 0.042, 2082, 0, 0, 0, 0, 0.32),
  .Dim =
    c(6L, 6L), .Dimnames = list(NULL, NULL)
)
m
#>       [,1]  [,2]  [,3]  [,4]  [,5]    [,6]
#> [1,] 0.000 0.000 0.000 0.000 0.000 2082.00
#> [2,] 0.369 0.000 0.000 0.000 0.000    0.00
#> [3,] 0.000 0.232 0.000 0.000 0.000    0.00
#> [4,] 0.000 0.000 0.207 0.000 0.000    0.00
#> [5,] 0.000 0.000 0.000 0.047 0.000    0.00
#> [6,] 0.000 0.000 0.000 0.000 0.042    0.32

represents either or something else. And, without a model or algorithm, it is unclear how the matrix is populated from m[1,6], the fecundity.