Understanding population structure is fundamental to the sustainable management of marine fish. Blue whiting (Micromesistius poutassou) plays a key ecological role in the Northeast Atlantic as a mid-trophic species linking zooplankton to top predators, while also supporting major commercial fisheries. This review synthesises available evidence on its population structure, revealing a complex metapopulation composed of resident and migratory subpopulations. Although currently assessed as a single stock, this management unit does not account for underlying biological structure, potentially limiting the effectiveness of assessment and management strategies. Our synthesis supports the presence of partial migration, with both migratory and resident contingents contributing to spatial complexity in population structure. Genetic, otolith, parasite, and life-history data indicate the existence of relatively discrete northern and southern subpopulations, mixing zones, and resident groups. We highlight the importance of adaptive, spatially explicit management approaches that account for temporal variability, support stakeholder engagement, and foster regional cooperation. Key knowledge gaps remain in fine-scale population structuring, life-history stage characterisation, and connectivity mechanisms. Addressing these will require integrative approaches using genomics, otolith chemistry, and biophysical modelling. While current stock boundaries encompass the species' range, integrating internal biological structure into assessments and management strategies will enhance their effectiveness and contribute to sustainable exploitation.

The influence of density-dependent effects on fish maturity is rarely considered when evaluating different harvest strategies, nor when formulating short-term catch advice. In cases where these effects are included, the spawning stock size is commonly used as the density variable. However, this approach is inadequate for a stock where juvenile and mature individuals have limited interaction. In such instances, using the abundance of the recruits of a cohort as a density variable is a more appropriate alternative. In this study, we have used the Norwegian spring-spawning herring (Clupea harengus) as a test stock to investigate this concept and develop a model for predicting future trends in maturity-at-age. This stock is an optimal candidate since previous publications have highlighted a spatial separation between juveniles and adults, and changes in maturity in response to historical stock dynamics have been observed and documented. Our approach provides increased accuracy for predicting maturity-at-age when compared to an assumption of density independence. Furthermore, a further expansion of this approach, i.e. applying a relationship with somatic growth, can contribute to more realistic simulations for predicting future stock dynamics, and more appropriate catch advice.

Impacts of climate change on ocean productivity sustaining world fisheries are predominantly negative but vary greatly among regions. We assessed how 39 fisheries resources-ranging from data-poor to data-rich stocks-in the North East Atlantic are most likely affected under the intermediate climate emission scenario RCP4.5 towards 2050. This region is one of the most productive waters in the world but subjected to pronounced climate change, especially in the northernmost part. In this climate impact assessment, we applied a hybrid solution combining expert opinions (scorings)-supported by an extensive literature review-with mechanistic approaches, considering stocks in three different large marine ecosystems, the North, Norwegian and Barents Seas. This approach enabled calculation of the directional effect as a function of climate exposure and sensitivity attributes (life-history schedules), focusing on local stocks (conspecifics) across latitudes rather than the species in general. The resulting synopsis (50-82 degrees N) contributes substantially to global assessments of major fisheries (FAO, The State of World Fisheries and Aquaculture, 2020), complementing related studies off northeast United States (35-45 degrees N) (Hare et al., PLoS One, 2016, 11, e0146756) and Portugal (37-42 degrees N) (Bueno-Pardo et al., Scientific Reports, 2021, 11, 2958). Contrary to prevailing fisheries forecasts elsewhere, we found that most assessed stocks respond positively. However, the underlying, extensive environmental clines implied that North East Atlantic stocks will develop entirely different depending upon the encountered stressors: cold-temperate stocks at the southern and Arctic stocks at the northern fringes appeared severely negatively impacted, whereas warm-temperate stocks expanding from south were found to do well along with cold-temperate stocks currently inhabiting below-optimal temperatures in the northern subregion.

Density-dependent growth, which might influence the effects of fisheries on a population, is often ignored when management strategies are evaluated, mainly due to a lack of appropriate models readily available to be implemented. To improve on this, we investigated if somatic growth in Norwegian spring-spawning herring (Clupea harengus) depends on cohort density using a formulation of the von Bertalanffy growth function on cohorts from 1921 to 2014 and found a significant negative correlation between estimated asymptotic length and density. This clearly indicates density-dependent effects on growth, and we propose a model that can be used to predict the size-at-age of Norwegian spring-spawning herring as a function of herring density (the abundance of two successive cohorts) in short-term predictions of catch advice, and in Management strategy evaluations, including estimation of their reference points such as F-MSY.

The temporal and spatial resilience of abundance patterns of assemblages of organisms inhabiting transition zones between Arctic and boreal regions is an issue of concern in relation to climate change. The recognition that baseline information spanning such transition zones is required to facilitate future monitoring and assessments of temporal dynamics provided the motivation for the present study. One such transition area is the Svalbard archipelago of the Northeast Atlantic, located between the Arctic and the boreal Atlantic, where significant climate changes occur. The study aimed to utilize an existing data series from Svalbard to analyse and describe demersal fish assemblage structure and distributions. Norwegian bottom trawl surveys sampled the area annually in August–September 2007–2014, and the dataset is the first from this area which is sufficiently comprehensive to carry out assemblage analyses. The survey years analysed represent the recent unprecedented warm period in the Barents Sea–Svalbard region which started around 2004. The new baseline information improves the basis for future studies of resilience under changing environmental conditions. A key finding was that the major transition in species composition is that between deep Greenland Sea and Arctic Ocean assemblages (upper slope assemblages) and the shelf assemblages. In shallower shelf areas (<500 m depth) structuring is weaker with assemblages having many species in common. The expected association of fish assemblages with regional bathymetric and hydrographic features was confirmed. The observed patterns probably reflect a comparatively extensive Atlantic influence during the warm period.

Global warming drives changes in oceanographic conditions in the Arctic Ocean and the adjacent continental slopes. This may result in favourable conditions for increased biological production in waters at the northern continental shelves. However, production in the central Arctic Ocean will continue to be limited by the amount of light and by vertical stratification reducing nutrient availability. Upwelling conditions due to topography and inflowing warm and nutrient rich Atlantic Water may result in high production in areas along the shelf breaks. This may particularly influence distribution and abundance of sea mammals, as can be seen from analysis of historical records of hunting. The species composition and biomass of plankton, fish and shellfish may be influenced by acidification due to increased carbon dioxide uptake in the water, thereby reducing the survival of some species. Northwards shift in the distribution of commercial species of fish and shellfish is observed in the Barents Sea, especially in the summer period, and is related to increased inflow of Atlantic Water and reduced ice cover. This implies a northward extension of boreal species and potential displacement of lipid-rich Arctic zooplankton, altering the distribution of organisms that depend on such prey. However, euphausiid stocks expanding northward into the Arctic Ocean may be a valuable food resource as they may benefit from increases in Arctic phytoplankton production and rising water temperatures. Even though no scenario modelling or other prediction analyses have been made, both scientific ecosystem surveys in the northern areas, as well as the fisheries show indications of a recent northern expansion of mackerel (Scomber scombrus), cod (Gadus morhua), haddock (Melanogrammus aeglefinus) and capelin (Mallotus villosus). These stocks are found as far north as the shelf-break north of Svalbard. Greenland halibut (Reinhardtius hippoglossoides), redfish (Sebastes spp.) and shrimp (Pandalus borealis) are also present in the slope waters between the Barents Sea and the Arctic Ocean. It is assumed that cod and haddock have reached their northernmost limit, whereas capelin and redfish have potential to expand their distribution further into the Arctic Ocean. Common minke whales (Balaenoptera acutorostrata) and harp seals (Pagophilus groenlandicus) may also be able to expand their distribution into the Arctic Ocean. The abundance and distribution of other species may change as well - to what degree is unknown. (C) 2016 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license.

The seamounts of the southern Indian Ocean remain some of the most poorly studied globally and yet have been subject to deep-sea fishing for decades and may face new exploitation through mining of seabed massive sulphides in the future. As an attempt to redress the knowledge deficit on deep-sea benthic and pelagic communities associated mainly with the seamounts of the South West Indian Ridge two cruises were undertaken to explore the pelagic and benthic ecology in 2009 and 2011 respectively. In this volume are presented studies on pelagic ecosystems around six seamounts, five on the South West Indian Ridge, including Atlantis Bank, Sapmer Seamount, Middle of What Seamount, Melville Bank and Coral Seamount and one un-named seamount on the Madagascar Ridge. In this paper, existing knowledge on the seamounts of the southwestern Indian Ocean is presented to provide context for the studies presented in this volume. An account of the overall aims, approaches and methods used primarily on the 2009 cruise are presented including metadata associated with sampling and some of the limitations of the study. Sampling during this cruise included physical oceanographic measurements, multibeam bathymetry, biological acoustics, and net sampling of phytoplankton, macrozooplankton and micronekton/nekton. The studies that follow reveal new data on the physical oceanography of this dynamic region of the oceans, and the important influence of water masses on the pelagic ecology associated with the seamounts of the South West Indian Ridge. New information on the pelagic fauna of the region fills an important biogeographic gap for the mid- to high-latitudes of the oceans of the southern hemisphere.

Information on stock identification and spatial stock structure provide a basis for understanding fish population dynamics and improving fisheries management. In this study, otolith shape analysis was used to study the stock structure of blue whiting (Micromesistius poutassou) in the northeast Atlantic using 1693 samples from mature fish collected between 37°N and 75°N and 20°W and 25°E. The results indicated two stocks located north and south of ICES Divisions VIa and VIb (54°5N to 60°5N, 4°W to 11°W). The central area corresponds to the spawning area west of Scotland. Sampling year effects and misclassification in the linear discriminant analysis suggested exchanges between the northern and southern stocks. The results corroborate previous studies indicating a structuring of the blue whiting stock into two stocks, with some degree of mixing in the central overlap area.

Northern blue whiting is a small abundant pelagic gadoid that is widely distributed in the northeast Atlantic and one of the most commercially valuable species west of the British Isles and Ireland. Over the last two decades the northeast Atlantic stock has undergone dramatic changes in abundance. The stock size decreased dramatically from 2007 to 2011, but has since shown signs of recovery. Changes in recruitment levels have occurred almost simultaneously with unusual changes in the north Atlantic ecosystem and oceanography. These links may suggest a causal linkage and the possibility of improving our understanding of the recruitment and spawning stock distribution. Here we use a set of geostatistical indices to describe the temporal and spatial patterns of the northeast Atlantic blue whiting stock in spring of 2006–2014. Geostatistical indices were computed to investigate changes in the spatial distribution, dynamics and variability of the stock in terms of density and location. Indices revealed 3 different distribution patterns over the time series. Main concentrations were either found around Rockall (first years), west of the Hebrides (2008–2013) or in the southern survey area (2014). The distribution was found to be age structured, with young blue whiting mainly concentrated in shallower areas (<1000m), along the shelf edge, and older specimens being more prominent in deeper waters (>1000m). A general additive mixed model (GAMM) was used to model the distribution of blue whiting according to environmental conditions and location.

The abundance and biomass of the Norwegian spring-spawning herring (NSSH) stock are assessed annually using a virtual population analysis (VPA) applied to catch-at-age data from the fishery and fishery-independent abundance indices derived from research vessel surveys for calibration (tuning'). The most important of these surveys is the International Ecosystem Survey in the Nordic Seas (IESNS) and this is highly influential for the outcome of the assessment. Until now, the abundance indices from the IESNS have been reported without any measure of uncertainty. In this study, the sampling errors associated with the density estimates of NSSH from the IESNS for the years 2009-2012 are estimated using design-based survey sampling theory. The annual survey estimates of number and biomass of herring per square nautical mile (nm(2)) were relatively precise for all age groups combined, with relative standard error (RSE) ranging from 8% to 15%, while for each individual age group (3-12) the RSE was less than 30% for most years. For age groups 1 and 2, and all age groups older than 12 years, the density estimates are highly imprecise, with RSE ranging from 30% to 100%. The precision in estimated density provided here indicates that the time series from the survey can be used to study trends in overall abundance and biomass of the stock. It is recommended that statistical assessment models that can account for sampling errors in input data from survey indices by age group and catch-at-age be tested in the assessments of the NSSH stock.

In contrast to generally sparse biological communities in open-ocean settings, seamounts and ridges are perceived as areas of elevated productivity and biodiversity capable of supporting commercial fisheries. We investigated the origin of this apparent biological enhancement over a segment of the North Mid-Atlantic Ridge (MAR) using sonar, corers, trawls, traps, and a remotely operated vehicle to survey habitat, biomass, and biodiversity. Satellite remote sensing provided information on flow patterns, thermal fronts, and primary production, while sediment traps measured export flux during 2007-2010. The MAR, 3,704,404 km(2) in area, accounts for 44.7% lower bathyal habitat (800-3500 m depth) in the North Atlantic and is dominated by fine soft sediment substrate (95% of area) on a series of flat terraces with intervening slopes either side of the ridge axis contributing to habitat heterogeneity. The MAR fauna comprises mainly species known from continental margins with no evidence of greater biodiversity. Primary production and export flux over the MAR were not enhanced compared with a nearby reference station over the Porcupine Abyssal Plain. Biomasses of benthic macrofauna and megafauna were similar to global averages at the same depths totalling an estimated 258.9 kt C over the entire lower bathyal north MAR. A hypothetical flat plain at 3500 m depth in place of the MAR would contain 85.6 kt C, implying an increase of 173.3 kt C attributable to the presence of the Ridge. This is approximately equal to 167 kt C of estimated pelagic biomass displaced by the volume of the MAR. There is no enhancement of biological productivity over the MAR; oceanic bathypelagic species are replaced by benthic fauna otherwise unable to survive in the mid ocean. We propose that globally sea floor elevation has no effect on deep sea biomass; pelagic plus benthic biomass is constant within a given surface productivity regime.

The Mid Atlantic Ridge (MAR) has been identified as an important component of the lower bathyal (800−3500m depth) benthic biogeographic province in the North Atlantic Ocean. We performed a multi-scale characterization of seafloor topography of the MAR. In the basin-scale analysis, we have used the 30″ General Bathymetric Chart of the Oceans (GEBCO) grid to estimate the area of different components of lower bathyal habitat in the main North Atlantic basin and to produce a corresponding depth–area relationship. The regional-scale investigation is based on swath bathymetry surveys which show the flanks to MAR to comprise a series of sediment-draped flat plains (37.65% of area) with intervening gentle slopes ranging from 5° to 30° (56.70% of area) and slopes steeper than 30° (5.65% of area). The steep slopes have significant areas of hard substrate (70%) comprising bare cliff faces and rock outcrops. Within the local-scale approach, detailed surveys of such steep areas were done by multi-beam sonar and cameras mounted on a Remotely Operated Vehicle (ROV). In several locations, the terrace-like seafloor topography has also been identified. Overall, it has been shown that the MAR lower bathyal is 95% covered with soft sediment.

Report of the Benchmark Workshop on Pelagic Stocks (WKPELA 2012), 13–17 February 2012 Copenhagen, Denmark

Direct and indirect effects of global warming are expected to be pronounced and fast in the Arctic, impacting terrestrial, freshwater and marine ecosystems. The Barents Sea is a high latitude shelf Sea and a boundary area between arctic and boreal faunas. These faunas are likely to respond differently to changes in climate. In addition, the Barents Sea is highly impacted by fisheries and other human activities. This strong human presence places great demands on scientific investigation and advisory capacity. In order to identify basic community structures against which future climate related or other human induced changes could be evaluated, we analyzed species composition and diversity of demersal fish in the Barents Sea. We found six main assemblages that were separated along depth and temperature gradients. There are indications that climate driven changes have already taken place, since boreal species were found in large parts of the Barents Sea shelf, including also the northern Arctic area. When modelling diversity as a function of depth and temperature, we found that two of the assemblages in the eastern Barents Sea showed lower diversity than expected from their depth and temperature. This is probably caused by low habitat complexity and the distance to the pool of boreal species in the western Barents Sea. In contrast coastal assemblages in south western Barents Sea and along Novaya Zemlya archipelago in the Eastern Barents Sea can be described as diversity "hotspots"; the South-western area had high density of species, abundance and biomass, and here some species have their northern distribution limit, whereas the Novaya Zemlya area has unique fauna of Arctic, coastal demersal fish. (see Information S1 for abstract in Russian).

Ovary development in Greenland halibut (Reinhardtius hippoglossoides) is complex, with several cohorts of developing oocytes present during vitellogenesis; this is unusual for a determinate spawner. There are also speculations that Greenland halibut are not capable of spawning every year. To investigate this possibility, ovaries from Greenland halibut caught throughout the year were examined histologically, and successive cohorts of oocytes were tracked through development. Results showed that the initial maturation of the ovaries from immature to spawning takes more than 1 year. The ovary initially develops as far as early vitellogenesis; however, the time scale for this is unclear. During the final year of development, the cohort of vitellogenic oocytes splits to form two cohorts; the larger cohort increases in size and is spawned in the coming spawning season. The smaller cohort also continues to develop, but at a much lower rate, in preparation for development for spawning in the following year. Within each month, there is a large range of oocyte sizes between fish; this leads to the extended spawning season that is known in many populations of this species. This complicates the assessment of maturity, and a more accurate microscopic maturity scale is proposed.

Chapter 6 Biodiversity Patterns and Processes on the Mid-Atlantic Ridge Michael Vecchione, Michael Vecchione NMFS National Systematics Laboratory, National Museum of Natural History, MRC-153 Smithsonian Institution, P.O. Box 37012 Washington, DC 20013-7012, USASearch for more papers by this authorOdd Aksel Bergstad, Odd Aksel Bergstad Institute of Marine Research, Flødevigen, NO-4817 His, NorwaySearch for more papers by this authorIngvar Byrkjedal, Ingvar Byrkjedal University of Bergen, Bergen Museum, Department of Natural History, P.O. Box 7800, NO-5020 Bergen, NorwaySearch for more papers by this authorTone Falkenhaug, Tone Falkenhaug Institute of Marine Research, Flødevigen, NO-4817 His, NorwaySearch for more papers by this authorAndrey V. Gebruk, Andrey V. Gebruk P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow 117997, RussiaSearch for more papers by this authorOlav Rune Godø, Olav Rune Godø Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this authorAstthor Gislason, Astthor Gislason Marine Institute of Iceland, Skélagötu 4, 121 Reykjavik, IcelandSearch for more papers by this authorMikko Heino, Mikko Heino University of Bergen, Department of Biology, P.O. Box 7803, NO-5020 Bergen, NorwaySearch for more papers by this authorÅge S. Høines, Åge S. Høines Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this authorGui M. M. Menezes, Gui M. M. Menezes Departamento de Oceanografia e Pescas, Universidade dos Açores, PT-9901-862, Horta, PortugalSearch for more papers by this authorUwe Piatkowski, Uwe Piatkowski Leibniz-Institut für Meereswissenschaften, IFM-GEOMAR, Forschungsbereich Marine Ökologie, Düsternbrooker Weg 20, D-24105 Kiel, GermanySearch for more papers by this authorImants G. Priede, Imants G. Priede University of Aberdeen, Oceanlab, Newburgh, Aberdeen AB41 6AA, Scotland, UKSearch for more papers by this authorHenrik Skov, Henrik Skov DHI, Agern Allé 5, DK-2970 Hørsholm, DenmarkSearch for more papers by this authorHenrik Søiland, Henrik Søiland Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this authorTracey Sutton, Tracey Sutton Virginia Institute for Marine Science, College of William and Mary, P.O. Box 1346, Gloucester Point, Virginia 23062, USASearch for more papers by this authorThomas de Lange Wenneck, Thomas de Lange Wenneck Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this author Michael Vecchione, Michael Vecchione NMFS National Systematics Laboratory, National Museum of Natural History, MRC-153 Smithsonian Institution, P.O. Box 37012 Washington, DC 20013-7012, USASearch for more papers by this authorOdd Aksel Bergstad, Odd Aksel Bergstad Institute of Marine Research, Flødevigen, NO-4817 His, NorwaySearch for more papers by this authorIngvar Byrkjedal, Ingvar Byrkjedal University of Bergen, Bergen Museum, Department of Natural History, P.O. Box 7800, NO-5020 Bergen, NorwaySearch for more papers by this authorTone Falkenhaug, Tone Falkenhaug Institute of Marine Research, Flødevigen, NO-4817 His, NorwaySearch for more papers by this authorAndrey V. Gebruk, Andrey V. Gebruk P.P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Moscow 117997, RussiaSearch for more papers by this authorOlav Rune Godø, Olav Rune Godø Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this authorAstthor Gislason, Astthor Gislason Marine Institute of Iceland, Skélagötu 4, 121 Reykjavik, IcelandSearch for more papers by this authorMikko Heino, Mikko Heino University of Bergen, Department of Biology, P.O. Box 7803, NO-5020 Bergen, NorwaySearch for more papers by this authorÅge S. Høines, Åge S. Høines Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this authorGui M. M. Menezes, Gui M. M. Menezes Departamento de Oceanografia e Pescas, Universidade dos Açores, PT-9901-862, Horta, PortugalSearch for more papers by this authorUwe Piatkowski, Uwe Piatkowski Leibniz-Institut für Meereswissenschaften, IFM-GEOMAR, Forschungsbereich Marine Ökologie, Düsternbrooker Weg 20, D-24105 Kiel, GermanySearch for more papers by this authorImants G. Priede, Imants G. Priede University of Aberdeen, Oceanlab, Newburgh, Aberdeen AB41 6AA, Scotland, UKSearch for more papers by this authorHenrik Skov, Henrik Skov DHI, Agern Allé 5, DK-2970 Hørsholm, DenmarkSearch for more papers by this authorHenrik Søiland, Henrik Søiland Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this authorTracey Sutton, Tracey Sutton Virginia Institute for Marine Science, College of William and Mary, P.O. Box 1346, Gloucester Point, Virginia 23062, USASearch for more papers by this authorThomas de Lange Wenneck, Thomas de Lange Wenneck Institute of Marine Research, P.O. Box 1870 Nordnes, NO-5817 Bergen, NorwaySearch for more papers by this author Book Editor(s):Alasdair D. McIntyre, Alasdair D. McIntyre The University of Aberdeen, Scotland, UKSearch for more papers by this author First published: 08 October 2010 https://doi.org/10.1002/9781444325508.ch6Citations: 19 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary This chapter contains sections titled: Introduction Discoveries Knowledge Gaps Recommendations Conclusions Acknowledgments References Citing Literature Life in the World's Oceans: Diversity, Distribution, and Abundance RelatedInformation