Abstract
Understanding how population structure and connectivity emerge in organisms with complex life cycles remains a central challenge in marine ecology, particularly in pelagic systems where dispersal potential is often high. In this study, how life-stage–specific processes shape population structure in the scyphozoan jellyfish Aurelia aurita across a fjord system was investigated. Field observations of benthic polyps and pelagic medusae with population genetic analyses and results from a Lagrangian particle-tracking model were combined to assess connectivity across spatial and temporal scales. Genetic diversity differed between life stages. Benthic polyp populations seemed to maintain consistently high haplotype diversity, whereas pelagic medusa populations showed more spatial and interannual variability. Despite high dispersal potential, genetic structure was spatially heterogeneous within the fjord, with some regions showing persistent diversity and others exhibiting reduced variation. Drift simulations predicted relatively homogeneous mixing but failed partly to reproduce the dominance patterns observed in medusa populations, indicating that hydrodynamic transport alone cannot explain the observed population structure. Instead, the results suggest that connectivity may be shaped by the interaction between dispersal and stage-specific demographic processes. This suggests that the benthic polyp stage can act as a persistent reservoir of genetic diversity, while the short-lived pelagic medusa population represents a transient and environmentally filtered subset of that diversity. Interannual variability further modulates this relationship, with environmental conditions influencing which genotypes are expressed in the pelagic stage in given region. Together, these findings demonstrate that population connectivity in marine organisms with complex life cycles cannot be inferred from dispersal potential alone but emerges from the interplay between life-stage complexity, environmental variability, and local demographic processes.