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.