Apply Markov chain approaches to compute age-specific
trajectory of reproduction for individuals in a matrix population model.
Includes functions to calculate the probability of achieving reproductive
maturity (mature_prob), mean age at first reproduction
(mature_age), and distribution of individuals first achieving
reproductive maturity among stage class (mature_distrib).
mature_prob(matU, matR = NULL, matF = NULL, matC = NULL, start = 1L)
mature_age(matU, matR = NULL, matF = NULL, matC = NULL, start = 1L)
mature_distrib(matU, start = 1L, repro_stages)The survival component of a matrix population model (i.e., a square projection matrix reflecting survival-related transitions; e.g., progression, stasis, and retrogression).
The reproductive component of a matrix population model (i.e., a
square projection matrix only reflecting transitions due to reproduction;
either sexual, clonal, or both). If matR is not provided, it will be
constructed by summing matF and matC.
(Optional) The matrix reflecting sexual reproduction. If provided
without matC, matC is assumed to be a zero matrix. If
matR is provided, this argument is ignored.
(Optional) The matrix reflecting clonal (asexual) reproduction.
If provided without matF, matF is assumed to be a zero
matrix. If matR is provided, this argument is ignored.
The index (or stage name) of the first stage at which the author
considers the beginning of life. Defaults to 1.
A vector of stage names or indices indicating which
stages are reproductive. Alternatively, a logical vector of length
ncol(matU) indicating whether each stage is reproductive
(TRUE) or not (FALSE).
For mature_distrib, a vector giving the proportion of
individuals that first reproduce within each stage class. For all others, a
scalar trait value.
Note that the units of time in returned values are the same as the
ProjectionInterval of the MPM.
Caswell, H. 2001. Matrix Population Models: Construction, Analysis, and Interpretation. Sinauer Associates; 2nd edition. ISBN: 978-0878930968
Other life history traits:
entropy_d(),
entropy_k(),
entropy_k_age(),
entropy_k_stage(),
gen_time(),
life_elas(),
life_expect_mean(),
longevity(),
net_repro_rate(),
shape_rep(),
shape_surv()
data(mpm1)
mature_prob(matU = mpm1$matU, matR = mpm1$matF, start = 2)
#> [1] 0.4318182
mature_prob(mpm1$matU, mpm1$matF, start = 2)
#> [1] 0.4318182
mature_age(matU = mpm1$matU, matR = mpm1$matF, start = 2)
#> small
#> 2.136364
mature_age(matU = mpm1$matU, matF = mpm1$matF, start = 2)
#> small
#> 2.136364
### distribution of first reproductive maturity among stage classes
repstage <- repro_stages(mpm1$matF)
mature_distrib(mpm1$matU, start = 2, repro_stages = repstage)
#> seed small medium large dormant
#> 0.00000000 0.00000000 0.92105263 0.07894737 0.00000000