Subsampling
The inference method described above assumes that all individuals from the in silico population have been sampled and genotyped. When subsampling is applied in a realistic manner (i.e. , mimicking the subsampling level of most studies in molecular ecology), however, real issues emerge in terms of parameter accuracy and consequent estimates ofc .
Genetic parameters (which proved to be less informative for assessing the clonal rate) were nearly unaffected by realistic sample sizes, whereas genotypic parameters (which were most informative) were considerably overestimated when using realistic sample sizes, leading to a gross underestimate of c from real datasets collected from natural populations. This situation remained nearly unchanged when subsampling was performed before the population reached equilibrium (see Figure S2). The R parameter is so susceptible to sampling bias that a sampling effort of 50 units, consistent with many works studied thus far, including ours, cannot reliably estimate an R value lower than 0.9, with the exception of highly clonal populations (c >0.8). A correct and unbiased estimate of R can be achieved only by genotyping the entire population (Figures 4 and S2). Interestingly, the variance in F IS computed from samples provided more identifiable signals of rates of clonality at all populations sizes than genotyping all individuals. However, away from equilibrium, the variance in F IS became less informative than that obtained at equilibrium (Figure S2).