Benthic life stages retain fjord-scale population structure despite pelagic dispersal

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.

1 Introduction

Many marine organisms have complex life cycles in which different stages have different environmental demands, occupy distinct habitats and experience different dispersal environments. As a result, population structure and temporal variability cannot be understood from a single life stage or the most conspicuous or easily sampled life stage alone. Instead, hidden or persistent stages may strongly influence local retention, connectivity, and recruitment, with important consequences for spatiotemporal population dynamics (Kinlan and Gaines, 2003; Marshall and Morgan, 2011). In marine systems, these stage-specific differences are especially important because dispersal potential, environmental sensitivity, recruitment success and persistence often vary strongly across the life cycle, shaping both local population structure and broader metapopulation dynamics (Cowen and Sponaugle, 2009; Sanford and Kelly, 2011; Marshall and Alvarez-Noriega, 2020; Cohen and Levin, 1991; Sunday et al., 2015; Ronce and Kirkpatrick, 2001).

Responses to environmental changes and variability are not uniform across species, or even within species, as different life stages and geographically distinct populations may respond differently to the same forcing due to local adaptation and environmental conditions (Sanford and Kelly, 2011; Sjöqvist et al., 2015; Pujolar et al., 2022; Burrows et al., 2019; Burrows et al., 2011; Edwards and Richardson, 2004; McPeek and Holt, 1992). In many marine invertebrate species, pelagic larval stages are the main source of dispersal leading to a largely passive transport by currents. Larval dispersal thus links distant populations and shapes population size, range dynamics, and connectivity (Marshall and Morgan, 2011; Leung and McAfee, 2020, Kinlan and Gaines, 2003; Levin, 2006; Pineda et al., 2007; Marshall et al., 2012; Marshall et al., 2018; Marshall et al., 2009).

Gelatinous zooplankton, however, differ fundamentally from the typical larval–adult framework. In scyphozoan jellyfish, a benthic polyp stage alternates with pelagic stages (egg, planulae, ephyrae and adult medusae), creating a life cycle in which both benthic persistence and pelagic dispersal can influence population dynamics (Arai, 1997; Boero et al., 2008; Lucas and Dawson, 2013). These stages differ markedly in longevity, environmental sensitivity, and ecological function (Goldstein et al., 2017). Polyps can persist locally and reproduce asexually under favorable conditions, whereas pelagic stages are more directly influenced by short-term environmental variability (Purcell et al., 2007; Holst, 2012). Unlike typical larvae, medusae may also exhibit active swimming and vertical positioning, which may further influence dispersal pathways (Ugland et al., 2014). As a result, population structure and temporal variability in jellyfish are affected both by interactions between locally persistent benthic populations and spatially variable pelagic transport (Boero et al., 2008; Lucas and Dawson, 2013; Dawson et al., 2015; Jaspers et al., 2025; Majaneva et al., 2026), thus leading to strong spatial and temporal variability of jellyfish populations, with large inter-annual fluctuations in abundance and bloom intensity. These population variations make reliable predictions of jellyfish blooms a central ecological challenge, as bloom dynamics have often been interpreted from the conspicuous medusa stage, while bloom formation depends on the interaction between the benthic source population and pelagic dispersal (Pauly et al., 2009; Graham and Kroutil, 2001; Lucas and Dawson, 2013). Blooms are commonly described as either “true” or “apparent”, depending on whether they arise from local production or from the redistribution of individuals, although many systems likely reflect a combination of both processes (Graham and Kroutil, 2001). Connectivity therefore plays a central role in shaping bloom dynamics: strong exchange among populations may promote apparent blooms, whereas limited exchange may increase the importance of local production. Differences in connectivity can thus influence bloom intensity, frequency, duration, and spatial extent across regions and years (Dawson et al., 2015; Pitt et al., 2013; Brotz, 2016; Jaspers et al., 2025; Majaneva et al., 2026).

Despite increasing recognition of the fact that complex life cycles can structure population dynamics, the extent to which different life stages shape connectivity and inter-annual variability remain poorly resolved in natural systems (Levin, 2006; Cowen and Sponaugle, 2009; Pineda et al., 2007; Riginos et al., 2016). In jellyfish, this gap is particularly pronounced because benthic and pelagic stages may contribute differently to local persistence and dispersal, yet few studies have focused on the population structure of the benthic polyp stage (van Walraven et al., 2016; Seo et al., 2021). Here, we used the cosmopolitan Scyphozoa Aurelia aurita (Linnaeus, 1758) in a well-studied fjord system to test how benthic and pelagic life stages jointly shape population structure and bloom dynamics. We combined field observations of polyps and medusae with genetic data and Lagrangian particle tracking models to assess how retention and hydrodynamically driven transport contribute to fjord-scale variability across years. By focusing on connectivity among life stages and regions we provide a framework for understanding how complex life cycle’s structure population dynamics in marine and estuarine systems.

2 Methods

2.1 Study site

The study was conducted in Trondheimsfjorden (Norway), a temperate estuarine environment with characteristic physical, biological oceanographic features (Hegseth and Sakshaug, 1983; Jacobson, 1983; Ellingsen, 2004; Aberle et al., 2024). Trondheimsfjorden (63°29′59.99″ N, 10°27′59.99″ E) is a 126 km long fjord with an average depth of approximately 165 m and divided into three main basins by the Agdenes (195 m), Tautra (100 m), and Skarnsund (140 m) sills (Bakken, 2023). Circulation in the fjord is primarily driven by freshwater runoff, tidal forcing, wind, and density-driven exchange with coastal waters associated with the Norwegian Coastal Current. Freshwater input forms a brackish surface layer that generally flows seaward, while more saline water enters at depth, creating a two-layer estuarine circulation (Jacobson, 1983). Periodic inflow events renew deep basin waters and contribute to vertical and horizontal mixing within the system r (Jacobson, 1983, Jacobson, 1983; Ellingsen, 2004). These hydrographic features, together with the presence of multiple sills, create spatial heterogeneity in water exchange and particle transport both within the fjord and between the fjord and adjacent coastal waters. As a result, Trondheimsfjorden provides a suitable system for investigating how local retention and exchange processes influence population connectivity across life stages.

2.2 Field sampling

Pelagic specimens of Aurelia aurita medusa were collected during 12 research cruises with NTNU’s RV Gunnerus between 2018 and 2020 across different seasons along a transect spanning the outer to the inner part of the fjord (Figure 1; Supplementary Table 1).To sample a broad size range and multiple pelagic life stages, from planula larvae to adult medusae, we used a combination of a WP2 net (mesh size 180 μm, opening 0.25 m²), a modified WP3 net with a non-filtering cod-end (mesh size 780 or 1000 μm, opening 1 m²), and a bottom trawl (shrimp trawl, 35 mm stretched mesh, with 11 mm inner lining in the cod-end). Specimens were sorted immediately after sampling, and total A. aurita abundance and biomass were recorded. Medusa size was measured as coronal diameter (CD) rounded to the nearest centimeter, and individuals weighing more than 1 g were weighed fresh on a Marel M1100 scale right after sampling. For size-weight relationships, a subset of 20 small (< 10 cm CD) and 30 large (> 10 cm CD) specimens were measured. Further details on medusae sampling are provided in Aberle et al., 2023. When possible, a minimum of 30 specimens per sampling event were preserved in >70% ethanol for molecular analysis.

Figure 1

Adult medusa specimens collected from Oslofjorden were used as a reference dataset to contextualize genetic patterns observed in Trondheimfjorden, allowing comparison between geographically separated populations. These reference samples of A. aurita from Oslofjorden were sampled opportunistically by landing net from pier-side at MariusBrygge and EngoBrygge between 05 and 18 May 2020. Tissue samples from individual A. aurita medusa were taken using a knife by excising small part at the rim of the bell, and placed into a 1.5 mL Eppendorf tube, and filled up with 95% ethanol for molecular analysis.

Sessile benthic polyp stages of A. aurita were collected from intertidal areas along a transect spanning the outer to inner part of Trondheimsfjorden during the same sampling period (Figure 1). Sampling targeted habitats previously identified as suitable for scyphozoan polyps including sheltered bays with macroalgae canopy or hard substrate providing appropriate microhabitats (Östman, 1997; Lucas et al., 2012; van Walraven et al., 2016). In addition, settling plates were deployed in autumn to sample newly attached polyps. When possible, at least 30 specimens were preserved in >70% ethanol for molecular analysis. Further details on polyp sampling are provided in Rekstad et al. (2021).

2.3 Molecular work

DNA was extracted from >300 pelagic stages and >150 polyp specimens to maximize coverage across sampling locations, periods and size classes. For small tissue pieces, DNA was extracted using a modified Chelex rapid-boiling procedure following Granhag et al. (2012). A fragment of the Cytochrome c oxidase subunit 1 (mtCOI, app. 600 bp) was amplified using the scyphozoan specific primers ScyCOIf and ScyCOIr (van Walraven et al., 2016). PCR amplifications were performed in 20 µL reaction containing 0,4 µL Phire^® Hot Start DNA polymerase, 4 µL of Phire ^® reaction buffer, 1µL of each primer (final concentration 0.2 mmol), 1 µL of DNA template, 0,4 µL of DNTP, 0,6 µL of 3% DMSO and 1,6 µL nuclease-free water. The cycling regime started with initial denaturing period of 5 min at 98 °C followed by 40 cycles of 98 °C (5s), 60 °C (5s), 72 °C (20s), with a final extension for 2 min at 72 °C. PCR products were purified using purification kit following the procedure recommended by the manufacturer (Illustra GFX PCR DNA and Gel Band Purification Kit). All PCR products were sequenced by commercial service (Eurofins Sequencing Service, Germany) and Macrogen (Macrogen Europe, Netherlands). The sequences are available in the European Molecular Biology Laboratory (EMBL) Nucleotide Sequence Database (GenBank accession numbers: PZ729172 - PZ729670).

Sequence electropherograms were inspected visually for poor base calls and overall sequence quality using Chromas Lite 2.1 (Technelysium Pty Ltd). The high-quality sequences were assembled in BioEdit (Hall, 1999) and aligned using the MAFFT online service (Katoh et al., 2019) with the Q-INS-i strategy. Alignments were checked visually, identical sequences were removed, and poorly aligned regions were excluded prior to the analyses. Alignments are available on request.

Because polyp stages are difficult to identify morphologically (Holst, 2012; van Walraven et al., 2016; Rekstad et al., 2021) and the genus Aurelia includes cryptic species (Dawson and Jacobs, 2001), specimens’ identity was confirmed using Bayesian phylogenetic analysis in MrBayes 3.2.7a (Ronquist et al., 2012). Two independent runs with four Markov chains and 1600000 generations were carried out (average standard deviation of split frequencies 0.0094). Rather than selecting a single substitution model a priori, the analysis sampled across the GTR model space with gamma-distributed rate variation across sites and a proportion of invariable sites. The resulting estimates (e.g., tree topology) were posterior probability weighted averages of the models. Maximum likelihood bootstrap support values were calculated from 1000 replicates, using GARLI 2.0.1019 (Zwickl, 2006) with jModelTest 0.1.1 (Posada 2008) AICc criterion selected model (TIM2+I+G). Data available on request.

2.4 Population genetic analysis and statistics

Genetic variation was assessed across life stages, seasons, and geographic regions using standard population genetic metrics. Nucleotide diversity (p) and haplotype diversity (h) were estimated using the program DnaSP v5 (Librado and Rozas, 2009). Genetic differentiation among samples was calculated using pairwise FST values with 10,000 permutations in ARLEQUIN 3.1 (Excoffier et al., 1992) within an analysis of molecular variance (AMOVA) framework (Excoffier et al., 1992). A median-joining network showing the relationships between the mtDNA haplotypes was constructed using the PopART (https://popart.maths.otago.ac.nz/; Bandelt et al., 1999). To assess signals of population expansion, we calculated Tajima’s D and Fu’s FS in DnaSP v5 (Ramos-Onsins and Rozas, 2002). Significance levels were corrected using the Bonferroni correction.

2.5 Modelling

To evaluate how hydrodynamic transport may shape connectivity among life stages and regions, a Lagrangian particle tracking model to simulate the dispersal of A. aurita ephyrae and medusae within Trondheimsfjorden and adjacent coastal waters was used. The particle tracking framework was implemented within the ocean model system SINMOD, which has been previously applied in this region and proven to reproduce observed current patterns with good agreement (e.g., Broch et al., 2020). The hydrodynamic module of SINMOD is described in detail by Slagstad and McClimans (2005), and the particle tracking module applies a fourth-order Runge–Kutta scheme for numerical integration. In the current study, we applied a model configuration covering the coastal and fjord regions off Mid-Norway (Figure 1), with a horizontal resolution of 800 m. To ensure realistic forcing, boundary conditions (currents, tides, and hydrography) were derived through a nested modelling approach, starting from a regional model with 20 km resolution. The model was further forced with high-resolution atmospheric data from the Norwegian Meteorological Institute (met.no) and daily freshwater discharge estimates from the Norwegian Water Resources and Energy Directorate (NVE). The hydrodynamic model spans one year prior to particle release.

Particles representing ephyrae were released 4 times per hour from multiple locations in gridpoints close to land corresponding to observed polyp beds within Trondheimsfjorden during March and April (Rekstad et al., 2021). The released particles were tracked until the end of August. In the model, A. aurita individuals were assumed to have negligible horizontal swimming ability and were therefore transported passively by currents. Vertically, particles were constrained to the upper 20 m of the water column by imposing an upward swimming velocity of 1 m h^-¹ when transported below this depth. This assumption is supported by observations indicating that ephyrae are commonly distributed in the upper water column, particularly within the upper 10 m, where prey availability is also highest (Ishii and Watanabe, 2003; Lucas, 2001; Båmstedt et al., 2001).

3 Results

3.1 Aurelia aurita occurrence

Occurrence of Aurelia aurita medusae, with species identity confirmed by molecular analyses (see methods), was recorded at all stations in Trondheimsfjorden during the three sampling years (2018-2020), occurring from June to September (Supplementary Table 1). Total biomass and abundance varied among years with 140 kg sampled in 2018 (n= 712), 117 kg in 2019 (n= 1145) and 151 kg in 2020 (n= 558). Biomass and abundance varied strongly across sites and sampling dates, ranging from 0.2 kg at Tautra in September 2019 (n = 3) to 134 kg at Ytterøy in July 2018 (n = 649). Medusae size showed similarly pronounced variability, with the largest individuals recorded at Ytterøy in August 2020 (mean CD of 25.2 cm, mean weight 622 g) and the smallest in June 2020 (CD of 0.8 cm, mean weight 1g). Field surveys and settling plate deployments revealed A. aurita polyp colonies, following molecular confirmation of species identity (see Rekstad et al., 2021), at multiple locations throughout Trondheimsfjorden, indicating widespread settlement and persistence of the benthic stage. Polyps were recorded on 70 substrates of different material types in shallow littoral zones. Sheltered sites with reduced current exposure, often associated with dense macroalgae or complex local topography, supported a higher polyp occurrence than more exposed areas with low epibiont coverage (Rekstad et al., 2021).

3.2 Population diversity

Aurelia aurita exhibited high genetic diversity within Trondheimsfjorden based on the mtCOI locus, with a total of 70 haplotypes, defined by 65 polymorphic sites, including 38 parsimony informative sites. A small number of common haplotypes were shared across locations and between life stages, while the majority of haplotypes occurred at low frequencies (Figure 2). More than half of the haplotypes (56%) were singletons, and only nine haplotypes were logged in more than 10 individuals. Haplotype composition differed markedly between life stages. Most haplotypes were restricted to a single stage, with 58% detected only in medusae and 40% only in polyps, whereas fewer than 3% of haplotypes were shared between both stages. It is also worth noting that mtCOI haplotype network of polyp stage (Figure 2A), haplotypes were broadly shared among samples collected from natural substrates and artificial settlement plates without clear clustering, and multiple haplotypes were connected by few mutational steps, indicating a diverse but closely related haplotype assemblage. Adults on the other hand showed a star-like structure centered around a few dominant haplotypes.

Figure 2

Haplotype diversity (H) and nucleotide diversity (π) were quantified across life stages and geographic regions (Table 1). Overall haplotype diversity was high (mean H = 0.91), whereas the corresponding nucleotide diversity was substantially lower (mean π = 0.05). Across all samples, H ranged from 0.33 to 0.96 and π from 0.066 to 0.938. Diversity patterns differed between life stages and regions.

Polyp populations consistently exhibited high haplotype diversity across sites (H = 0.78–0.95), with moderate nucleotide diversity. In contrast, medusa populations showed stronger spatial and temporal variability, with both high diversity at some sites (e.g. Ytterøy and Beistadfjord) and reduced diversity at others (e.g. Verrasundet). Populations from the Oslofjorden region consistently displayed lower haplotype and nucleotide diversity than those from Trondheimsfjorden. Across all sites and years, haplotype and nucleotide diversity remained relatively high even when nucleotide diversity was low, for example, at Verrasundet where populations showed reduced nucleotide diversity (π ≈ 0.10) but still maintained moderate haplotype diversity (H ≈ 0.60–0.81.

Genetic differentiation differs between life stages. No significant population structure was detected among adult medusae within Trondheimsdfjorden in 2019 and 2020, whereas polyp population showed evidence of weak but significant spatial structuring. (Tables 2, 3). Overall, pairwise differentiation values were low (FST < 0.13), indicating limited genetic differentiation among sites. However, several population pairs showed significant differences. The highest differentiation was observed between Slettvik and Mausund areas (FST = 0.129). In particular, the Slettvik polyp population was significantly differentiated from other sites, including newly settled polyps collected from artificial settlement plates at the same location.

Pairwise genetic differentiation among medusa populations varied across sites and years (Table 3), with FST values ranging from −0.03 to 0.57. Within Trondheimsfjorden, differentiation was generally low, particularly among temporally replicated samples from the same locations (e.g. Beistadfjord and Verrasundet), indicating limited interannual genetic change at these sites. In contrast, higher differentiation was observed between geographically distant sites. Comparisons involving Oslofjorden samples consistently showed elevated differentiation relative to Trondheimsfjorden populations, with the strongest divergence detected between Oslofjorden and Ytterøy. Within Trondheimsfjorden spatial patterns were heterogenous. Some locations, such as Ytterøy and Trollet/TBS, exhibited moderate to high genetic differentiation from several other sites. These patterns indicate that, while pelagic populations are relatively well mixed within the fjord, connectivity is more limited between fjord systems, leading to pronounced regional differentiation.

3.3 Simulated dispersion

Dispersion patterns of Aurelia particles differed markedly between coastal and fjord environments. Particles originating from coastal locations, such as Mausund, were mixed into coastal waters and transported northward with the Norwegian Coastal Current, whereas particles originating inside Trondheimsefjorden were generally transported seaward toward the coast (Figure 3, Supplementary S1, S2). The brackish surface outflow from Trondheimsfjorden acted as a barrier to surface transport into the fjord, limiting inward dispersal from coastal areas. Entry of coastal Aurelia particles into the fjord would therefore likely require positioning deeper in the water column below the brackish layer or occur during episodic wind-driven reversals of the surface outflow. Strong tidal currents in the outer fjord near Slettvik may also facilitate particle exchange across the fjord–coastal boundary.

Figure 3

Connectivity patterns revealed clear spatial differences across the system. In the inner fjord region of Verrasundet, most particles present in late summer originated from local ephyra releases, indicating strong local retention. Additional contributions were traced back to Beistadfjord and the region around Ytterøy. Similarly, particles observed in Beistadfjord were primarily linked to local releases earlier in the season, with smaller inputs from adjacent inner fjord regions. Further seaward, connectivity expanded across larger parts of the fjord. The Trolla/TBS region was connected to release sites throughout the fjord but showed no contributions from coastal sources in 2018 (Supplementary S1). Størnfjorden displayed a similar pattern, with connectivity largely confined to the fjord system. In contrast, the Slettvik region showed contributions from both fjord and coastal sources, reflecting its transitional position between fjord and open coast. Forward simulations of particle dispersal supported these patterns. Particles released from Hø showed the highest concentrations around Ytterøy, with some dispersion into the basin and occasional transport into gyres in Frohavet. Particles released from TBS were transported both seaward and landward into the middle basin, indicating the influence of eddies and wind-driven currents despite the dominant seaward surface flow. For coastal release locations, particles from Slettvik were partly advected northward along the coast with the Norwegian Coastal Current, whereas particles released from Mausund were mainly dispersed into Frohavet and the coastal waters around Frøya. Connectivity varied among locations, with low connectivity for Slettvik and Hø, moderate connectivity for Mausund, and high connectivity for TBS within the fjord. A comparable spatial structure in connectivity was observed in 2020 (Supplementary S2), although the relative contributions from different source regions differed between years.

Model simulations for 2018–2020 indicated generally weak connectivity between Trondheimsfjorden and adjacent coastal regions. However, coastal circulation exhibited substantial interannual variability when simulations were extended to the period 2012–2017 showed that connectivity patterns varied between years. Backtracking results for the outer basin of Trondheimsfjorden (Figure 4), tracing particles three months prior to their observed positions, revealed that in most years particles originated within the fjord system. In contrast, results for 2013 showed particles tracing back to coastal regions, indicating periods of enhanced exchange between coastal waters and the fjord.

Figure 4

3.4 Distribution of common haplotypes across life stages and drift simulations

The relative frequencies of the ten most common haplotypes differed among polyp populations, adult medusae, and drift-model simulations (Table 4). In polyp populations (Table 4A), haplotype composition varied among sites, with several haplotypes occurring at high frequencies at individual locations. For example, haplotype 052 dominated at TBS (36%) and Verrasundet (36%), whereas haplotype 017 was most frequent at Hø (36%). Multiple haplotypes were absent or rare at several sites, resulting in site-specific frequency profiles.

Adult medusa populations (Table 4B) showed pronounced shifts in haplotype frequencies relative to polyp populations. At several sites, one or two haplotypes dominated the assemblage, including haplotype 065 at Tautra (45%), haplotype 052 at Slettvik (38%), and haplotype 077 at TBS (75%). In contrast, some adult populations exhibited more even distributions among haplotypes or complete absence of several common polyp haplotypes, as observed at Ytterøy, where haplotype frequencies were restricted to a small subset.

Under the drift simulation (Table 4C), haplotype frequencies converged toward similar distributions across sites. The most common haplotypes were consistently represented at comparable relative frequencies, with haplotypes 017, 032, and 052 typically comprising 20–30% of the assemblage across locations. Low-frequency haplotypes were retained across sites, and extreme dominance patterns observed in adult populations were not reproduced in the simulated data. Several haplotypes present in polyp populations from the outer fjord, including haplotypes 065 and 056, were not detected in adult populations within the fjord. The absence of these haplotypes in adults was also reproduced in the drift−model simulations.

4 Discussion

4.1 Life stage differences in genetic diversity

A central finding of this study is the contrasting genetic structure between the two Aurelia aurita life stages. Polyp populations maintained high haplotype diversity, characterized by numerous closely related haplotypes, consistent with long-lived benthic polyp stages potentially acting as reservoirs of genetic variation where multiple genotypes can persist over several years. In contrast, despite reflecting only a single seasonal cohort, medusae exhibited a star-like haplotype network dominated by a single central haplotype shared across all sampled regions, a pattern indicative of strong connectivity and/or recent population expansion (Bayha et al., 2015; Parisod et al., 2005; Seo et al., 2021), a pattern commonly observed in bloom-forming taxa. This suggests mixing among the fjord system, with limited geographic structuring, supporting the role of pelagic dispersal in promoting gene flow over larger spatial scales. At the same time, medusae exhibited spatial and temporal variability, indicating that local and interannual processes —such as variation in oceanographic conditions, influences the population structure at finer spatial scales and between years, a pattern that was evident even in locations with limited sample sizes.

In scyphozoan jellyfish, such as A. aurita, with a metagenetic life cycle, this contrast is biologically plausible: the benthic polyp stage is long-lived, reproduces asexually, and repeatedly generates pelagic cohorts through strobilation, whereas the abundance and demographic structure of medusae depend on successful progression through several environmentally sensitive life stages (Lucas, 2001; Goldstein and Steiner, 2020; Jensen et al., 2023). Although the longevity of individual polyps remains uncertain, they can persist for years, reproduce clonally, and release large numbers of ephyrae (Lucas, 2001; Goldstein and Steiner, 2020; Rekstad et al., 2021), providing the benthic stages` the capacity to accumulate and retain genetic variation even when pelagic populations fluctuate strongly through time (Lucas, 2001; van Walraven et al., 2016). In contrast, successful transition between life stages, from planulae to polyps, polyp to ephyrae, and ephyrae to medusae is sudden and strongly influenced by local environmental conditions, including temperature, and food availability which can differentially favor some genotypes over others (Goldstein and Steiner, 2020; Myrvold, 2020; Aditya, 2021; Jensen et al., 2023; Loveridge et al., 2024; Jaspers et al., 2025; Cant et al., 2025). This demographic asymmetry resembles the biphasic life cycles of many marine organisms, where planktonic, often larval, stages connect relatively sitting benthic adult populations. In such systems, population structure emerges from the interaction between dispersal, settlement, and post-settlement survival (White et al., 2019; Nishizaki and Ackerman, 2019). In contrast to the typical metazoan life cycle, the functional roles of the two stages in A. aurita are effectively reversed, with polyps rather than medusae acting as the primary stage responsible for local persistence and population maintenance, despite not being the sexually reproductive adult stage. Overall, these patterns are consistent with the idea that benthic polyp banks may contribute to the maintenance of genetic diversity over time. More broadly, our results suggest that in organisms with complex life cycles, population structure may not be determined solely by the most dispersive stage but may also be shaped by the stage that controls persistence and recruitment.

The consistently high haplotype diversity combined with comparatively low to moderate nucleotide diversity suggests that A. aurita populations in Trondheimsfjorden are structured by many closely related haplotypes rather than deeply divergent lineages. This pattern is commonly interpreted as a signature of recent demographic expansion or recurrent recruitment from multiple lineages differing by only a few mutations, rather than long-term persistence of highly divergent mitochondrial clades (Grant and Bowen, 1998; Avise, 2000). In the present context, this implies that polyp populations may receive genetically diverse recruits potentially including medusae originating from different regions and, in some years, from outside the fjord, whereof only a subset of these genotypes contributes to the medusa population each year. Thus, a valuable next step would be to follow the same polyp populations over multiple years to better resolve temporal dynamics in recruitment and genotype persistence. The suggested pattern is consistent with demographic or selective filtering during the benthic-to-pelagic transition, where local conditions reshape diversity not at the time of recruitment, but during later stages of survival, strobilation, and medusa production (Lucas, 2001; Goldstein and Steiner, 2020; Jensen et al., 2023). Importantly, this finding was supported by the drift-model simulations. While the drift-model predicted relatively homogeneous haplotype distributions across the different sites in Trondheimsfjorden, the observed medusae populations showed strong dominance of a few haplotypes and reduced diversity at several locations. This mismatch indicates that hydrodynamic transport alone cannot fully explain population structure, and that stage-specific demographic processes—such as selective survival, local retention, or differential strobilation success—may also play a role in shaping connectivity, although sampling effects, temporal turnover, and differences in life-stage persistence may also contribute to the observed patterns. Yet, this interpretation is consistent with broader work on A. aurita, where bloom dynamics and realized medusae production are highly sensitive to stage-specific ecology rather than simply reflecting the size of the initial recruit pool (Lucas, 2001; Holst, 2012; Goldstein and Riisgård, 2016).

Although A. aurita has substantial dispersal potential through its several planktonic stages (planulae, ephyrae and medusae), the present study revealed pronounced spatial heterogeneity in genetic diversity among fjord populations, with some sites consistently exhibiting high diversity and others showing reduced variation across years. The observed pattern is consistent with the hypothesis that realized population structure is not determined by dispersal potential alone, but by the interaction between connectivity and local retention, with hydrographic conditions potentially limiting the effective export of individuals from local populations (e.g. in Beistadfjord). However, because these inferences are based on a single mitochondrial marker (mtCOI), they should be interpreted with appropriate caution. As a maternally inherited locus, mtCOI captures only part of the population history and may be influenced by historical demographic events or selective processes. Furthermore, in species, such as A. aurita, exhibiting both sexual and asexual reproduction, mitochondrial marker variation alone may not fully resolve the relative contributions of clonal propagation, sexual recruitment, and contemporary gene flow to observed population patterns. Genome-wide approaches using multiple loci would provide a more comprehensive assessment of population connectivity, demographic processes, and genetic structure (e.g. Sunnucks, 2000; Carling and Brumfield, 2007; Farhadi et al., 2022). More generally, in species with complex life cycles, different stages may contribute unequally to dispersal, and the stage with the highest dispersal capacity does not necessarily determine population structure (Strathmann, 1986; Levin, 2006; Cowen and Sponaugle, 2009). In marine systems, fine-scale patchiness and genetic structures can persist despite high dispersal potential of the pelagic stages when hydrographic conditions and basin topography promote retention and self-recruitment, thereby limiting effective exchange among neighboring areas (Selkoe et al., 2016). For example, studies from Norwegian fjords have demonstrated that local circulation, stratification, and retention of early life stages can generate small-scale population structure even in species that are expected to be highly connected (Knutsen et al., 2003; Jorde et al., 2007; Johannesson et al., 2023). Similarly, work on A. aurita across the Baltic–North Sea transition has shown that environmental gradients and restricted exchange can lead to regional differentiation and reduced gene flow despite its metagenic life cycle and dispersive pelagic stages (Holst and Laakmann, 2014; Jaspers et al., 2025).

4.2 Local demographic processes

These findings provide a basis to explain why fjord populations appear to behave as semi-independent demographic units. Local sites, such as Beistadfjord, which consistently maintained high diversity, likely represent relatively large and persistent local populations in which effective population size buffers against drift. In contrast, sites with low(er) diversity such as inner fjord regions (e.g. Verrasundet) seem to reflect stronger demographic instability, including founder effects, local bottlenecks, or repeated disturbance. Similar patterns have been observed in other marine systems, where high mitochondrial diversity coexists with pronounced spatial differentiation, indicating that populations can remain genetically distinct despite their dispersal potential, and that local retention and recruitment history may outweigh simple geographic proximity (Palumbi, 1994; Levin, 2006; Hellberg, 2009; Selkoe et al., 2016). The resulting pattern seems to be a spatial mosaic in which fjord-scale processes, such as retention, habitat stability, episodic disturbance, local oceanographic conditions and recruitment success, shape genetic variation more strongly than larger scale dispersal alone. The present results support a general framework in which connectivity supplies genetic variation, but local demographic processes determine whether that variation is retained and expressed (Levin, 2006; Cowen and Sponaugle, 2009) although interpretation is limited by temporal sampling constraints and potential interannual variability.

4.3 Interannual variability patterns

A third pattern detected was that the temporal stability seemed to differ markedly in the different fjord regions. Some regions maintained consistently high genetic diversity across years, whereas others showed more interannual variability, indicating that populations differ in how stable they are over time. Although sample sizes were limited at some sites and years, and sampling individuals merging from same polyps may introduce some degree of non-independence, the overall pattern is consistent with known interannual variability patterns observed for A. aurita populations from other regions (Lucas, 2001; Jaspers et al., 2021; Cant et al., 2025). The drift model results additionally revealed interannual variability across sites, indicating that dispersal patterns vary between years, driven by changes in oceanographic conditions such as currents, stratification, and temperature, although particle tracking models represent passive transport and do not fully capture organismal behavior. Previous studies have shown that A. aurita populations can vary substantially among years in terms of abundance, timing of appearance, growth, and reproductive output, even within the same system (Lucas, 2001; Purcell et al., 2007; Holst, 2012). Stage-structured studies further demonstrate that even moderate changes in environmental conditions, such as winter temperature or food availability, can strongly alter transitions between life stages, thereby affecting “boom-and-bust” dynamics across years (Lucas, 2001; Goldstein and Steiner, 2020). Experimental studies also indicate that key life-stage transitions, such as the medusa-to-polyp transition, are highly sensitive to variations in seasonal conditions i.e. temperature anomalies, and maternal provisioning, thus allowing short-term environmental variations to propagate through the life cycle and affecting population structure (Goldstein and Riisgård, 2016; Loveridge et al., 2024). In the present study, this variability is reflected not only by abundance patterns in the observed and modeled results but also in genetic differentiation, suggesting that interannual variation in environmental conditions acts as a selective and demographic filter that reshapes the genetic structure of the medusa population from year to year. As a result, genetic patterns observed in the pelagic stage may primarily reflect short-term ecological conditions rather than long-term equilibrium population structure.

5 Conclusion

Our observed, genetic and modelled findings suggest that temporally stable sites can harbor persistent polyp banks that buffer populations against genetic drift and episodic recruitment failure, whereas more variable sites with a higher degree of disturbance can experience recurrent genetic turnover driven by irregular recruitment, variable survival, and stochastic medusa production. Therefore, the composition observed in medusae at any given time reflects not only the diversity stored in the benthic stage, but also the outcome of recent environmental filtering and oceanographic conditions. This provides a plausible explanation for the contrasting diversity patterns observed between life stages: while the benthic polyp stage maintains a broader and relatively stable reservoir of genetic variation, the pelagic medusae population represents a transient and environmentally filtered subset of the diversity. This finding supports a two-stage demographic framework in which dispersal and recruitment generate genetically diverse benthic populations, while interannual variability in local environmental conditions determines which genotypes are expressed in the pelagic stage. In this context, the hydrodynamic model provides a mechanistic baseline for potential connectivity, while the genetic data reflect realized connectivity shaped by demographic and biological processes. The apparent mismatch between potential and realized connectivity therefore represents a qualitative pattern rather than a formal model validation, underscoring the exploration nature of the comparison. In addition, future studies using genome-wide approaches with multiple loci would further improve understanding by providing a more comprehensive assessment of population connectivity, demographic processes, and genetic structure. These results highlight that population connectivity and structure in marine organisms with complex life cycles cannot be understood from the dispersal potential of individual life stages alone but emerge from the interaction between life-stage-specific processes, environmental variability, and local demographic dynamics.

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