Approach
PC is empirically known to affect genotypic and genetic descriptors
commonly used in population genetics studies (Halkett et al., 2005): 1)
the number of different genotypes per population, as characterised by
the genotypic richness indices R and Pareto \(\beta\)(Arnaud-Haond et al., 2007), and two genetic indices, namely, 2) the
inbreeding coefficient F IS and its moments
(Balloux et al., 2003; Stoeckel & Masson, 2014) and 3) the LD index
(Navascués et al., 2010). To date, no analytical formalisation has been
developed to predict the theoretical probability distributions of these
descriptors under varying rates of clonality. We thus used simulations
to i) synthesise the effects of varying rates of clonality on the ranges
and dynamics of these genotypic and genetic descriptors, ii) assess
whether these descriptors actually provide the ability to discriminate
and quantify rates of clonality using a classic supervised learning
method, and iii) determine which descriptors best account for specific
ranges of rates of clonality, with the aim of providing recommendations
for future analyses and interpretations.