Institute of Marine Research

BackgroundJuvenile loggerhead sea turtles represent a crucial but understudied stage of the species life cycle. Most studies have been conducted at regional scales and there remains a need for a broader scale synthesis. In the North Atlantic, loggerheads encounter numerous threats such as fishing during their transoceanic journey, so it is important to get a broad view of their distribution, movement and habitat preferences.MethodsFor this study, we gathered tracking data from 124 juvenile loggerheads tagged along the Azores, Canary Islands, Madeira and in the western North Atlantic to develop a habitat model for the entire basin. We used a SSM to interpolate tracks to daily positions, simulated pseudo-absences with a correlated random walk for background data, and explored 17 environmental variables using boosted regression trees to select the best model in terms of biological realism and predictive power. The best model obtained (AUC = 0.988) was then used to predict habitat suitability for the North Atlantic for the period 1998–2022. Stranding records of loggerheads in France, UK and Ireland were used to discuss the predictions.ResultsAfter filtering, tracks of 105 individuals, covering most of the basin, were used in the model. Our predictions of habitat suitability show the importance of the Gulf Stream and the Azorean Current. Habitat suitability is predicted to be higher in the area between 30° and 45°N all year round, while open waters below 30°N, including Cape Verde, are not predicted to be a suitable habitat. In northern and eastern areas, like the Bay of Biscay and UK and Irish waters, habitat suitability varied seasonally, with colder seasons showing lower values. Accordingly, strandings in those areas occurred mostly during winter (December-February; 45.1%) and spring (March-May; 34.1%).ConclusionsThe model offers a first basin-scale prediction of the seasonal distribution of juvenile loggerheads in the North-Atlantic, which shows consistency with stranding and bycatch data in the basin. This study represents a first step towards a broader scale understanding of juveniles’ habitat preferences that can be used to quantify the magnitude and extent of the threats that they face.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40462-026-00640-2.

Abstract Monitoring stock status using fisheries-independent methods is essential for sustainable marine resource management. These methods help identify biases in fisheries-dependent data but often require comprehensive, long-term surveys. Recent advancements in spatiotemporal models enable the integration of fisheries-independent data from multiple sources, enhancing stock status estimates. We compiled bottom trawl survey data (over 43 000 trawl hauls from 1981 to 2024) for beaked (Sebastes mentella) and golden redfish (Sebastes norvegicus) from the Institute of Marine Research databases. Using spatiotemporal generalized linear mixed-effects models, we estimated trends and spatial distributions of these species in the Barents and Norwegian Seas. Model selection, conducted through 10-fold cross-validation, highlighted depth, spatial, and spatiotemporal random fields as crucial components for estimating survey indices. Beaked redfish had the highest biomass densities in the Central Barents Sea, while golden redfish dominated along the Norwegian Coast. Nursery areas for both species were primarily located in the Barents Sea, with beaked redfish juveniles distributed further north. We also detected distribution shifts: the Central Barents Sea has gained beaked redfish biomass, while the Southern Barents Sea and the close shore Norwegian coast are increasingly important for golden redfish. Additionally, we observed reductions in golden redfish biomass on the large banks south of Lofoten and in the Western and Central Barents Sea. Biomass indices indicated a positive trend for beaked redfish and a stable trend for golden redfish. Biomass changes in beaked redfish were correlated with rising bottom temperatures; however, golden redfish were only weakly correlated. The survey indices for both species correlated with commercial catches and total stock biomass estimates from current assessments. This study demonstrates the capability to track changes in species distribution over time, improving stock assessments. The methodology presented here is applicable for monitoring and managing marine species globally.

Aquaculture is the fastest-growing animal food-producing sector for human consumption globally. Increasing population size, density, and interconnectivity among farms are expected to markedly increase disease outbreak risks, threatening sector sustainability. Infectious diseases cause around a third of observed mortality in farmed salmon in Norway. Cardiomyopathy syndrome (CMS), caused by piscine myocarditis virus (PMCV), is one of the most frequently detected diseases and often causes high mortality in the late phase of salmon production, compromising fish welfare and causing significant economic losses. Despite its impact, the limited understanding of PMCV dispersal and its drivers hampers effective risk mitigation interventions. To address this, we generated one of the largest genomic datasets for any aquatic viral pathogen, focusing on PMCV collected from Scotland (United Kingdom) and Norway. Combined with detailed metadata, this enabled one of the most comprehensive phylodynamic analyses of a fish virus. Phylodynamic analyses reveal that PMCV likely emerged in farmed salmon concurrent with the global expansion of aquaculture, with a most recent common ancestor around the 1970s-1990s. We identify a distinctive national clustering of virus genomes, reflecting intranational spread interspersed with multiple introductions of distinct PMCV lineages into Scotland. We assess factors influencing virus spread, highlighting the importance of geographic proximity and at-sea farm density, and the possible role of boat connectivity in facilitating long-distance dispersal events. Overall, our study emphasizes the importance of viral genomics in understanding the evolutionary and dispersal dynamics of aquatic pathogens and informs targeted biosecurity strategies to mitigate the growing risk of viral disease in expanding aquaculture systems.

Seaweed represents a diverse group of marine organisms rich in bioactive compounds that have attracted interest for their potential relevance in neurological research. Recent studies highlight their ability to modulate neuroinflammation, oxidative stress, synaptic plasticity, and pathways implicated in neurodegeneration in preclinical models. Extracts from brown, red, and green algae contain polysaccharides, polyphenols, carotenoids, and fatty acids that exhibit neuroprotective, antioxidant, and anti-inflammatory activities in vitro and in vivo, although these findings remain limited to experimental systems. This review synthesizes current evidence on the neurological activities of seaweed-derived compounds, emphasizing mechanistic findings while clearly distinguishing between experimental observations and unvalidated clinical implications. Challenges related to bioavailability, pharmacokinetics, safety, and clinical translation are discussed, alongside considerations for future research. Evidence in humans remains scarce and indirect, and no seaweed-derived compound has demonstrated neuroprotection or disease-modifying effects in clinical settings.

Larval drift connects sub-populations within metapopulations of species with long lasting pelagic larval phases, like northern shrimp ( Pandalus borealis ), which inhabits patches of soft bottom along the Norwegian coast. The key objective of this study was to investigate whether northern shrimp in Northern Norwegian fjords constitute distinct fjord-based sub-populations, or if they form a coherent coastal population due to advection of larvae along the coast and between fjords. Shrimp larval fluxes within and out of a Northern Norwegian fjord, Kvænangen, were studied with a particle tracking model combined with a high-resolution hydrodynamic model, and we estimated the retention of shrimp larvae released within the fjord and the export of larvae with the currents to neighbouring fjords. Kvænangen is an open fjord with a deep sill dividing the inner and outer fjord. The model particles, representing shrimp larvae, were given a temperature dependent development rate and a diurnal vertical swimming behaviour dependent on development stage. Larval drift was modelled for the years 2018–2021 to capture interannual variability of oceanographic conditions. The dispersal of shrimp larvae varied from local settlement within the fjord, to long range advection (>250 km) to other fjords downstream or farther to the Barents Sea. Within Kvænangen, more larvae settled in the inner fjord basins behind the sill than in the outer fjord. Shrimp in the inner fjord seem to constitute a self-sustained sub-population, while the population outside the sill lost most of its spawning products offshore and therefore relies on import from the inner fjord and upstream populations for recruits. These results have implications for the management of shrimp fisheries and how the management units of shrimp should be defined. Our findings are also relevant for management of the salmon aquaculture industry; since shrimp larvae disperse throughout Kvænangen, there is no place in the fjord where chemicals from delousing baths can be released without potentially harming shrimp larvae. • Larval dispersal varied from local retainment to long range advection (>250 km). • Currents, wind and fjord-coast water exchange determined retainment and advection. • Connectivity between shrimp fields in Troms and western Finnmark is high. • The retention of larvae in inner Kvænangen is sufficiently large for possibly maintaining a self-sustained population.

Abstract Following the ROBUST Living Lab methodology, the Lisbon Living Lab was designed and carried out following multi-stakeholder dialogue structured in interactive workshops, with a bottom-up governance arrangement in working groups led by the stakeholders to tackle a real-word problem. In this context, one of the working groups aimed to address the improvement of the Green Infrastructure Strategic Plan for the metropolitan area of Lisbon based on the Ecosystem Services concept. The purpose was to bring coherence to the existing detached patchwork of local green infrastructures. This chapter reports on how the governance arrangements created played out in the Lisbon Living Lab process. Consequently, following analysis of the outcome and evaluation of the process, a conceptual model for Collaborative Green Infrastructure Planning is proposed.

Abstract Advice on fishing opportunities is based on stock assessment models. Modern stock assessment frameworks are designed to account for uncertainty in model parameters. However, some parameters are often fixed at specific values and assumed to be known precisely. Paradoxically, these fixed values often relate to parameters we understand the least—such as the natural mortality rate. For example, in the assessment of Norwegian Spring-Spawning Herring, the natural mortality rate is assumed to be exactly 0.9 for age 2 fish and 0.15 for older fish. In this study, we investigate how sensitive the assessment results—and, more specifically, the resulting fishing quotas (total allowable catch, TAC)—are to assumptions regarding natural mortality and maturity-at-age for both Norwegian Spring-Spawning Herring and North-East Arctic Cod. The assessment models for both stocks are formulated within the SAM framework. Furthermore, we explore a simple approach for adjusting harvest control rules that seeks to preserve the TACs when fundamental fixed assumptions are altered. Our intention is that this serves as an exploratory tool to investigate sensitivity to new assumptions, and is not intended to replace a more formal process for defining new biological reference points and harvest control rules. The results indicate that, under the current harvest control rules, the TACs for both herring and cod may be sensitive to assumptions regarding natural mortality rates and maturity-at-age. For herring, sensitivity to natural mortality is significantly greater than is reflected by the estimation uncertainty in model parameters. However, when basic assumptions are changed, it is also natural to consider corresponding adjustments to the harvest control rules. Our proposed simple adjustments to the control rules reduce sensitivity to these assumptions in many cases, though not in all.