New insights into the population genetics of partially clonal organisms: When seagrass data meet theoretical expectations.

Seagrass meadows are among the most important coastal ecosystems in terms of both spatial extent and ecosystem services, but they are also declining worldwide. Understanding the drivers of seagrass meadow dynamics is essential for designing sound management, conservation and restoration strategies. However, poor knowledge of the effect of clonality on the population genetics of natural populations severely limits our understanding of the dynamics and connectivity of meadows. Recent modelling approaches have described the expected distributions of genotypic and genetic descriptors under increasing clonal rates, which may help us better understand and interpret population genetics data obtained for partial asexuals. Here, in the light of these recent theoretical developments, we revisited population genetics data for 165 meadows of four seagrass species. Contrasting shoot lifespan and rhizome turnover led to the prediction that the influence of asexual reproduction would increase along a gradient from Zostera noltii to Zostera marina, Cymodocea nodosa and Posidonia oceanica, with increasing departure from Hardy-Weinberg equilibrium (F ), mostly towards heterozygote excess, and decreasing genotypic richness (R). This meta-analysis provides a nested validation of this hypothesis at both the species and meadow scales through a significant relationship between F and R within each species. By empirically demonstrating the theoretical expectations derived from recent modelling approaches, this work calls for the use of Hardy-Weinberg equilibrium (F ) rather than only the strongly sampling-sensitive R to assess the importance of clonal reproduction (c), at least when the impact of selfing on F can be neglected. The results also emphasize the need to revise our appraisal of the extent of clonality and its influence on the dynamics, connectivity and evolutionary trajectory of partial asexuals in general, including in seagrass meadows, to develop the most accurate management strategies.