pop_germc: Germination
In PROSPER: Simulation of Weed Population Dynamics

Description Usage Arguments Details Value See Also Examples

pop_germc describes germination as random event for individual seeds. The function considers different cohorts and dormancy.

1	pop_germc(init_sb, germ, max_vec_length = 1e+07)

`init_sb`	column name of the initial seed bank in the data.frame dfgenotype that is delivered by struc_preparation. `character`.
`germ`	germination probabilities for the different cohorts. See details.
`max_vec_length`	used internally, a technical term, defining the maximum length of vectors to be used.

Each individual has a chance to germinate or to stay dormant. In case of germination, it emerges in one of the cohorts. The distribution of individual seeds to cohorts or dormancy is random. The function uses the columns init_SB of the data.frame dfgenotype as input. The output values are the numbers of seedlings of each genotype and each cohort.

germ must be given as a numeric vector or - in case of multiple columns in init_sb - data.frame or matrix. In that case the row number must fit to the length of init_sb. If the columns in init_sb represent cohorts, the rows of germ give the germination probabilities for these specific cohorts. The sum of one row of germ shall be ≥ 0 and ≤ 1. The difference of 1 and the sum of on row germ is the probability of dormancy.

Columns are added to dfgenotype: "germ_dorm" contains the numbers of each genotype that remain dormant, "germ1" to "germX" contain the numbers for each of X cohorts.

pop_reprod pop_step quanti

struc_preparation2(Rmx=10, af=c(0.01,0.8), epis=0, dom=1)
ls()
gen_freq( af=c(0.01,0.8), n_seeds=10000)
#Distribute the individuals to three cohorts with the germination 
#probabilities 0.2, 0.4 and 0.4.
pop_germc( init_sb="initialSB", germ=c(0.2,0.4,0.4))
rm(mf, dfgenotype, xprobab)