Bjarki Þór Elvarsson

Greenland halibut ( Reinhardtius hippoglossoides ) is a deep‐water flatfish which lives at temperatures of 1°C–4°C and produces large eggs (> 3 mm). The combination of low temperatures and large eggs has resulted in an unusual ovary development cycle, with vitellogenesis taking more than 1 year. This means that fish with early vitellogenic oocytes (termed functionally immature) will not spawn during the next spawning season and should not be included in the Spawning Stock Biomass (SSB). During the Icelandic autumn groundfish survey, the ovary development of Greenland halibut has been evaluated using a 4‐stage maturity scale. The 4‐stage scale, unlike the 6‐stage scale developed specifically for Greenland halibut, does not separate fish in the first year and second year of vitellogenesis which can lead to inaccuracies in the estimation of SSB. The current study investigates whether the weight of the gonad, expressed as a percentage of total body weight, commonly known as gonadosomatic index (GSI), can be used to evaluate maturity for Greenland halibut. We show, from measurements of oocytes, for Greenland halibut collected in Iceland and East Greenland, 93% of Greenland halibut with a gonadosomatic index (GSI) > 1.5% are in their second year of vitellogenesis and should be considered sexually mature. In addition, 97% of fish with a GSI < 1.5% were considered sexually immature/functionally immature. Application of this GSI‐based approach to data collected during the Icelandic autumn groundfish survey demonstrates that it is a practical alternative to visually assessing maturity and can be retroactively applied to past data if gonad weight has been measured. Using GSI to discriminate sexually mature from sexually immature/functionally immature individuals resulted in a length at 50% maturity ( L ₅₀ ) 2.4–8.8 cm higher in comparison to visually assessing maturity with the 4‐point scale. The GSI‐based approach indicated that fish visually classified as ‘spent’ were misidentified and are a mix of other maturity stages, this is supported by the spawning season being 7–9 months prior to the survey. Our data indicates that L ₅₀ of Greenland halibut in Iceland increased in 2012, with L ₅₀ in the period 1996–2010 approximately 73–77 cm whereas in the period 2012–2023 it was approximately 78–81 cm. While, for years 2014–2023, when age was estimated, age at 50% maturity ( A ₅₀ ) was 18.2 years.

Despite their potential to inform sustainable regional harvest and climate‐resilient fisheries management, spatial stock assessment models remain underused for management advice. To identify barriers that inhibit broader use of these methods, we conducted a blinded international simulation experiment mimicking real‐world stock assessment development when confronting spatial complexity. Seven analyst teams built spatially aggregated and spatially explicit assessment models using data simulated from high‐resolution operating models based on Indian Ocean yellowfin tuna and Ross Sea Antarctic toothfish dynamics. Each team documented how assessment software platform, data analyses, model building approach, and diagnostics influenced model complexity and realism. A consensus emerged on key assessment building approaches: (1) conduct high‐resolution data analyses to identify appropriate spatial structure; (2) start with simplified models and incrementally add complexity; (3) iteratively evaluate diagnostics to determine necessary spatial complexity; and (4) maintain models with different spatial structures to aid interpretation. The experiment also revealed several valuable insights for parameterising assessments, including consideration of data pre‐processing with spatiotemporal models to better inform data‐sparse regions; regression trees to identify fleet and spatial structure; trade‐offs in complexity between productivity and movement dynamics to achieve tractable and stable model structures; and ensemble modelling approaches to address structural uncertainty. Our findings demonstrate that international collaborations and simulation experiments are crucial for addressing challenges in implementing spatial stock assessments and for evaluating whether their added complexity is justified given management objectives. Broader collaborations are encouraged to foster innovation in fisheries management and to help recognise the practical trade‐offs between model parsimony and complexity.

Understanding how fishers react to incentives created by fisheries policy, fish density, and market conditions is essential to understanding and predicting the impact of industrial fishing on the development of marine fish stocks. While most empirical studies focus on demersal species, this study explores the behavior of pelagic fisheries as a recent expansion of Northeast Atlantic mackerel (Scomber scombrus), due to its dynamic geographical nature, brought a new lucrative fishery to Iceland. We fit a spatial choice model for the time period 2011–2020 to understand the importance of environmental and socioeconomic predictors and their impact on individual fisheries behavior. Several models were tested, with the best model predicting 86% of the overall choices correctly. The inclusion of fish price, oil price, vessel size, processing type (frozen/fresh), expected catch, distance to ports, biological parameter of fish density, and environmental parameters such as surface temperature and net primary production played a significant role in improving the model’s accuracy. This highlights the importance of considering both cost-related factors and ecological conditions in understanding fishing location choices.

The Greenland halibut (Reinhardtius hippoglossoides) is an ecologically and economically important marine fish species in the Northern Hemisphere. In the North Atlantic, the current spatial management units comprise four large offshore stocks and eight additional inshore stocks. However, the underlying biological basis for stock separation is uncertain. This may risk misrepresenting key population characteristics and reference points for sustainable management. To identify population structuring and boundaries for Greenland halibut, we here apply a spatial statistical approach using an extensive collection of scientific bottom trawl-surveys. Our analysis demonstrates two overall clusters separating the Northwest and Northeast Atlantic. Our findings are broadly consistent with recent studies on population structuring based on available tagging data and population genetics. However, it is still challenging to establish whether the results of clustering accurately reflect the true population boundaries, especially at a finer spatial scale. Therefore, we call for a broader synthesis of knowledge on population structuring of Greenland halibut utilizing all available sources of information to facilitate the designation of ecologically relevant management units and boundaries.

Marine ecosystem-based management requires the understanding of species interactions and what species are harvested together. This study combines two major questions: the first regarding what drives the probability that a métier (species assemblages, with spatial distribution and seasonality) will be observed as catch, and the second regarding the level of control fishers have over this catch mix. To address these questions, we analysed highly resolved logbook records of an Arctic and sub-Arctic industrial demersal fishery operating in Icelandic waters. The study employs a multi-class random forest model to identify predictors of métier occurrence and consistency of predictions using a dataset of >100 000 hauls over 4 years (2016–2019). The overall accuracy of the random forest model is 69–70%, indicating moderate predictability of catch mix based on known environmental, vessel, and company characteristics. We find that habitat-related variables (depth and temperature) are most important to predict catch mix. Still, company, trip, and vessel characteristics are also very important (e.g. vessel and trip length, distance to port). Beyond these more traditional bio-economic variables, important predictors include variables related to harvesting strategies, such as quota diversity and a vessel’s mobility. These findings contribute to a fuller picture of fisher decision-making in mixed fisheries.

Temperature fluctuations impact the distribution of various marine fish species and typically result in distributional changes, seeing either a geographical expansion or, possibly, a retraction. Survival and fitness in the new habitat depend, however, on the species’ adaptability capacity. Here, we describe changes in geographical distribution of Icelandic haddock (Melanogrammus aeglefinus) based on annual survey data for a 38-year period, 1985–2022. Most of the stock is in the warm waters off the south and west coasts of Iceland (south area), but a small proportion in colder water masses off the north and east coasts (north area). Due to high recruitment, density increased greatly in both areas in the years 2001–2005. Haddock density was usually higher in the south area in 1985–2004, in the north area in 2005–2014, but similar in both areas in 2015–2022. Haddock condition was found to be influenced by both temperature and haddock density. Density-dependent factors influenced haddock mean weight, which dropped considerable during times of high haddock density. Capelin was of great importance as a diet, especially in the south, where stomach fullness decreased considerably when capelin was not a part of the diet. Food availability seems to be highly variable between the two areas but more stable in the north, where fluctuations in capelin fullness were small. Even though favourable environmental conditions may result in increased haddock density in the colder waters in the north, lower condition indicates that the northern area may be less suitable for this species.

Understanding the genetic differentiation among populations of most marine fish requires investigating the differences among spawning grounds. However, this can be challenging as spawning grounds for some species are not well known, or spawning fish are difficult to collect. An alternative is to collect juvenile fish in nursery habitats closely associated with potential spawning grounds. Greenland halibut is a deep-dwelling, commercially important species with at least two identified major offshore spawning grounds in the North Atlantic and weak genetic differentiation across the Atlantic. In this study, we sampled juveniles from three sites representing the Davis Strait spawning area in the northwest Atlantic and one site in the northeast Atlantic representing the primary spawning area along the western slope of the Barents Sea. We applied genotype by sequencing and discovered 90 genetic markers that could be used to assess genetic differentiation among the four sites. The northeast and northwest Atlantic showed major genetic differentiation, supporting the existence of the two primary spawning clusters. Additionally, we found genetic differentiation between the three northwest Atlantic samples implying the existence of more than one spawning area in the northwest.