pop_step: Surviving a non-selective process
In PROSPER: Simulation of Weed Population Dynamics

Description Usage Arguments Details Value See Also Examples

pop_step picks the individuals that will pass to the next development stage. This is a random process for every individual, which does not exert any selection pressure.

pop_step(
  start,
  start_comb = NA,
  result = NA,
  stepname = NA,
  surv_prob,
  max_vec_length = 1e+07
)

`start`	column names of parental cohorts. `character vector`.
`start_comb`	all named columns in `start` are joined and returned as a column with the name of `start_comb` (`character`). Only used when `start` longer than 1.
`result`	name of the results column. `character`.
`stepname`	name of the new column of dfgenotype added by this function. `character`.
`surv_prob`	probability to survive this step and reach the next growth stage. `numeric`.
`max_vec_length`	used internally, a technical term, defining the maximum length of vectors to be used.

Individuals that reach the next growth stage are picked by using rbinom. In contrast to sel_herb, pop_step does not exert any evolutionary selection pressure. When more than one column is selected with start, they are summed and the result is passed to the picking process. By setting start_comb the sum is added as a column to dfgenotype.

A new column is added to dfgenotype containing the surviving individuals of the different genotypes.

quanti pop_germc

struc_preparation2(Rmx=10, af=c(0.01,0.8), epis=0, dom=1)
gen_freq(af=c(0.01,0.8), n_seeds=10000)
#How many individuals of each genotype will reach the next growth stage?
pop_step(start="initialSB",  stepname="survivingthewinter",
                            surv_prob=0.4)