Elucidating the migrations of European seabass from the southern north sea using mark-recapture data, acoustic telemetry and data storage tags.

The movement ecology of European seabass, Dicentrarchus labrax, remains poorly understood, especially in the northern ranges of its distribution. To investigate migration patterns of seabass from the southern North Sea, we combined data from different projects from four countries using various tagging techniques. This resulted in 146 recaptures (out of 5598 externally marked seabass), 138 detected animals (out of 162 seabass fitted with an acoustic transmitter) and 76 archived depth and temperature series (out of 323 seabass with an archival tag). Using geolocation modelling, we distinguished different migration strategies, whereby individual fish migrated to the eastern English Channel (15.1%), the western English Channel (28.3%), the Celtic Sea and the norther part of the Bay of Biscay (17.0%), or stayed in the North Sea (39.6%). A high number of seabass exhibited fidelity to the North Sea (90.5% of recaptures, 55.3% for acoustic transmitters and 44.7% of archival tags). Although seabass are generally considered to migrate southwards in winter, a large number of individuals (n = 62) were observed in the southern North Sea, where spawning might potentially occur in a particular deep location along the coast of Norfolk in the UK. Our results highlight the need to consider fine-scaled population structuring in fisheries assessment, and indicate that current seasonal fisheries closures are not aligned with the ecology of seabass in the North Sea.

Combining acoustic telemetry with archival tagging to investigate the spatial dynamic of the understudied pollack, Pollachius pollachius.

Combining fish tracking methods is a promising way of leveraging the strengths of each approach while mitigating their individual weaknesses. Acoustic telemetry provides presence information as the fish move within receiver range, eliminating the need for tag recovery. Archival tags, on the other hand, record environmental variables on tag retrieval, enabling continuous path reconstruction of a fish beyond coastal regions. This study capitalizes on the combination of both methods for geolocating pollack, Pollachius pollachius, an understudied species of the northeast Atlantic, where declining stocks are raising concern. Essential knowledge of population structure and connectivity between essential habitats is critically lacking and could help inform stock assessment and management. The aims of the study were (1) to evaluate the feasibility of double-tagging pollack, known for being challenging to tag, and (2) to track seasonal movements across the Channel to gain first insights into pollack spatial ecology. In 2022, an extensive network of acoustic receivers was been deployed in the Channel along the French, English, and Belgian coasts as part of the Fish Intel project. We tagged 83 pollack with acoustic transmitters, among which 48 were double-tagged with data storage tags. Post-tagging survival assessment, conducted on a subset of 35 individuals, revealed a successful procedure with a 97% short-term survival rate. By October 2023, the acoustic telemetry network detected 30 out of 83 pollack at least once, with no large-scale movements observed across the Channel. Presence in the network fluctuates seasonally, peaking in summer, particularly among immature fish. Integrating acoustic detections with temperature and depth time series in a geolocation model enabled trajectory reconstruction of 10 recaptured pollack, seven of which were detected by the network. This combined tracking approach revealed coastal movements along the coast of Brittany in France, highlighting the ecological significance of the Iroise Sea for pollack throughout the year, particularly in summer. The geolocation model also suggested movements towards the entrance of the western Channel. This study highlights the complementarity of acoustic telemetry and archival tagging in reconstructing fish movements in their natural environment. As data accumulate, these innovative tracking methods promise to continually unveil new insights into the spatial ecology of the understudied pollack, which is essential for the species' management.

Temporal variations in scale cortisol indicate consistent local-and broad-scale constraints in a wild marine teleost fish.

Environmental changes can alter the nursery function of coastal areas through their impact on juveniles' growth and survival rates, an effect mediated by individuals' chronic stress response. Fish chronic stress can be quantified using scale cortisol but no study has yet been quantified the spatio-temporal variations in scale cortisol and its relationship with growth in wild nurseries. We collected wild sea bass juveniles (Dicentrarchus labrax, four years, three nurseries) and found that scale cortisol levels increased consistently with age and across cohorts in 2019 and 2020 probably due to greater stress history in older fish and/or heatwaves that occurred in summers of 2018 and 2019. Growth was impaired in fish with high scale cortisol in 2019 and 2020, confirming the usefulness of scale cortisol as a biomarker of broad and local constraints in wild fish; longer time series will enable us to identify environmental factors underpinning these temporal variations.

Coupling spectral analysis and hidden Markov models for the segmentation of behavioural patterns.

BACKGROUND: Movement pattern variations are reflective of behavioural switches, likely associated with different life history traits in response to the animals' abiotic and biotic environment. Detecting these can provide rich information on the underlying processes driving animal movement patterns. However, extracting these signals from movement time series, requires tools that objectively extract, describe and quantify these behaviours. The inference of behavioural modes from movement patterns has been mainly addressed through hidden Markov models. Until now, the metrics implemented in these models did not allow to characterize cyclic patterns directly from the raw time series. To address these challenges, we developed an approach to i) extract new metrics of cyclic behaviours and activity levels from a time-frequency analysis of movement time series, ii) implement the spectral signatures of these cyclic patterns and activity levels into a HMM framework to identify and classify latent behavioural states. RESULTS: To illustrate our approach, we applied it to 40 high-resolution European sea bass depth time series. Our results showed that the fish had different activity regimes, which were also associated (or not) with the spectral signature of different environmental cycles. Tidal rhythms were observed when animals tended to be less active and dived shallower. Conversely, animals exhibited a diurnal behaviour when more active and deeper in the water column. The different behaviours were well defined and occurred at similar periods throughout the annual cycle amongst individuals, suggesting these behaviours are likely related to seasonal functional behaviours (e.g. feeding, migrating and spawning). CONCLUSIONS: The innovative aspects of our method lie within the combined use of powerful, but generic, mathematical tools (spectral analysis and hidden Markov Models) to extract complex behaviours from 1-D movement time series. It is fully automated which makes it suitable for analyzing large datasets. HMMs also offer the flexibility to include any additional variable in the segmentation process (e.g. environmental features, location coordinates). Thus, our method could be widely applied in the bio-logging community and contribute to prime issues in movement ecology (e.g. habitat requirements and selection, site fidelity and dispersal) that are crucial to inform mitigation, management and conservation strategies.

Interannual Changes in Biomass Affect the Spatial Aggregations of Anchovy and Sardine as Evidenced by Geostatistical and Spatial Indicators.

Geostatistical techniques were applied and a series of spatial indicators were calculated (occupation, aggregation, location, dispersion, spatial autocorrelation and overlap) to characterize the spatial distributions of European anchovy and sardine during summer. Two ecosystems were compared for this purpose, both located in the Mediterranean Sea: the Strait of Sicily (upwelling area) and the North Aegean Sea (continental shelf area, influenced by freshwater). Although the biomass of anchovy and sardine presented high interannual variability in both areas, the location of the centres of gravity and the main spatial patches of their populations were very similar between years. The size of the patches representing the dominant part of the abundance (80%) was mostly ecosystem- and species-specific. Occupation (area of presence) appears to be shaped by the extent of suitable habitats in each ecosystem whereas aggregation patterns (how the populations are distributed within the area of presence) were species-specific and related to levels of population biomass. In the upwelling area, both species showed consistently higher occupation values compared to the continental shelf area. Certain characteristics of the spatial distribution of sardine (e.g. spreading area, overlapping with anchovy) differed substantially between the two ecosystems. Principal component analysis of geostatistical and spatial indicators revealed that biomass was significantly related to a suite of, rather than single, spatial indicators. At the spatial scale of our study, strong correlations emerged between biomass and the first principal component axis with highly positive loadings for occupation, aggregation and patchiness, independently of species and ecosystem. Overlapping between anchovy and sardine increased with the increase of sardine biomass but decreased with the increase of anchovy. This contrasting pattern was attributed to the location of the respective major patches combined with the specific occupation patterns of the two species. The potential use of spatial indices as auxiliary stock monitoring indicators is discussed.