Quantifying clonality or merely evaluating its extent: how wrong can we be?
In many studies, R may reflect the orders of magnitude separating sample size and population size (sometimes together with the clonal size and/or clumping of clonal replicates) rather than the prevalence of sexual reproduction. As illustrated in this work, even moderate values of R under our usually very small sampling densities (several tens of sampling units in populations bearing one hundred thousand to millions of them) may thus suggest a high prevalence of clonal reproduction. Some examples exist in the literature in which only a good knowledge of species biology prevents misleading conclusions based on values of genotypic diversity. These examples indicate the need to be very careful in interpreting genotypic parameters alone in the numerous cases where no such extensive knowledge of the species studied exists. An enlightening case is the study by Orantes et al. (2012) on aphids reproducing through cyclical parthenogenesis. Eight populations ofAphis glycines were sampled at two time steps corresponding to the early season, when sexual reproduction arises at rather small population sizes, and the late season, after a demographic explosion of populations under full clonality. Against all expectations based on a presumed relationship between R and c and ignoring the effect of sampling density, Orantes et al. (2012) found lower genotypic diversity during the season of sexual reproduction (average R of 0.85, average Pareto \(\beta\) of 2.9) than during the later season of pure clonality (average R of 0.97, average Pareto \(\beta\) of 4.2), i.e. , \(R_{\text{sexual}}<R_{\text{clonal}}\) and\(\beta_{\text{sexual}}<\beta_{\text{clonal}}\). Without knowledge of the cycle and a good understanding of the effect of populationversus sample size, a higher rate of sexual reproduction in the late season could have been inferred. However, using the guidelines we aimed to develop here, R would mostly signal the significance of clonality and call for careful screening of genetic parameters. In fact, departure from HWE in this study confirms the complementarity of genotypic and genetic parameters by supporting the prevalence of clonal reproduction across the cycle, with mean F ISvalues of -0.21 and -0.24 in the earlier and later season, respectively, suggesting a more important influence of clonality in the later season, with a lower mean and larger variance. Similar patterns have been found in multiple studies on cyclical parthenogenetic species (e.g., Gilabert, Dedryver, Stoeckel, Plantegenest, & Simon, 2015; Loxdale et al., 2011). Another example is a highly clonal root-sucking nematode,Xiphinema index , which shows mid-range R values (0.16 to 0.39); however, negative mean F IS values with large variance in agreement with LD values suggest a rates of clonality exceeding 0.95 in all these populations, which had better agree with a naturalistic knowledge (Villate et al., 2010).
In fact, revising the numerous data acquired on clonal plants, including seagrasses, in light of the present results reveals very frequent negative F IS values, suggesting a much higher contribution of clonality than previously thought (Evans et al., 2014; Sinclair, Krauss, Anthony, Hovey, & Kendrick, 2014; Stoeckel et al., 2006) on the basis of their average R values (see Arnaud-Haond, Stoeckel, & Bailleul, 2019 for a meta-analysis). Unfortunately,F IS is often neglected in ecological studies, possibly due to difficulties in disentangling the influence of technical shortcomings such as null alleles from non-random mating such as selfing in some studies. In the seagrass literature, for example, moderate levels of R have led some authors to propose that sexual reproduction has a high incidence and may thus contribute greatly to recombination and dispersal through seed production (McMahon et al., 2017). The joint re-analysis of R and F ISvalues and their correlation can illuminate likely extreme but overlooked clonal rates (also see Arnaud-Haond et al., 2019). Although we seldom found this type of interpretation combining genotypic and genetic parameters in the literature (but see the examples above), this approach has been used by some authors, such as Ali et al. (2014) (also see the references above), to infer the importance of long-term clonality.
Interestingly, it has been shown that CloNcaSe, a method based on repeated genotypes alone (Ali et al., 2016), can deliver incorrect inferences, likely due to this subsampling effect on R. For a red alga (Gracilaria chilensis ) maintained through strict clonality for generations, R values of 0.2 to 0.23 lead CloNcaSe to infer a ĉ=0.82, while ClonEstiMate, a second method based on transition probabilities of genotype frequencies (Becheler et al., 2017), correctly infers a ĉ=1. Similarly, an aphid population sampled when mostly clonal lineages can be found (Rhopalosiphum padi, Halkett, Kindlmann, Plantegenest, Sunnucks, & Simon, 2006) has an R of 0.89, leading CloNcaSe to infer a ĉ=0.68, while ClonEstiMate better inferred a ĉ=0.9.
Revising estimates of clonality in natural populations is particularly important because present-day interpretations, often mostly focusing onR, are likely to grossly underestimate its extent. A vast body of literature exists on the relationship between genotypic diversity and the resistance or resilience of populations, as demonstrated in experimental studies (Hughes & Stachowicz, 2004; Hughes, Inouye, Johnson, Underwood, & Vellend, 2008; Reusch & Lampert, 2004; but see Massa, Paulino, Serrão, Duarte, & Arnaud-Haond, 2013). Severe overestimation of genotypic diversities may thus have led to strongly misleading conclusions as to the resilience of the studied populations, enhanced by their supposedly high R value, as well as to their ability to rely on dispersal of seeds due to recurrent events of sexual reproduction (Kendrick et al., 2012, 2017; McMahon et al. , 2017). A case-by-case re-evaluation is thus needed to determine what may hold true for some species, depending on their life history traits (particularly longevity and turnover), but be completely incorrect for others.