Florian Berg

Although major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, we still lack a clear understanding about the extent of polymorphism and selection mechanisms dominantly driving it. Here, we use 29 haploid genome assemblies resolved by long-read sequencing to characterize MHC II genes in Atlantic herring, a pelagic fish and one of the most abundant vertebrates on Earth. We found nine MHC II loci in total distributed on four chromosomes, three of which were extremely polymorphic because of high sequence diversity, in particular at peptide binding sites, along with high copy number variation. This study reveals that the herring MHC class II genes are among the most, if not the most, polymorphic so far described in vertebrates.

How species genetically adapt to new environments is a central question in evolutionary biology. Here whole-genome sequencing combined with functional analysis is used to dissect how Atlantic herring, a marine fish, has adapted to the brackish Baltic Sea. Genes involved in reproduction and early development emerge as primary targets of natural selection, with key changes in a sperm-specific anion channel ( LRRC8C2 ), a zona pellucida protein ( ZPBA1 ), a cluster of three genes for fish transglutaminase ( FTG1-3 ), and a copy number expansion of a fish hatching enzyme gene ( HE1C ). The large diameter of LRRC8C2 homomers facilitates transport of ions and osmolytes, likely preventing swelling of sperm when spawning in low salinity. Altered ZPBA1 sequence together with modified FTG1-3 enzyme activity produces a harder egg envelope that prevents egg swelling in brackish waters, while the enhanced activity of the adapted HE1C enzyme enables larvae to digest this reinforced egg envelope during hatching. Baltic Sea herring populations reproducing in brackish water are fixed or nearly fixed for variant alleles at these four unlinked loci, each carrying multiple amino acid substitutions compared to the alleles prevalent in the Atlantic Ocean populations. The alleles at two of these loci ( FTG1-3, and HE1C ) have been introgressed from the sister species Pacific herring. These findings reveal concrete molecular mechanisms by which a marine species has adapted to a novel, low-salinity environment.

The European sprat is a small pelagic fish characterized by genetically distinct populations including (a) the Norwegian fjords, (b) the Baltic Sea, (c) an oceanic component ranging from the North Sea, Kattegat–Skagerrak, Celtic Sea and Bay of Biscay, as well as the southern groups such as (d) the Mediterranean (Adriatic) and (e) the Black Sea. Additionally, a self‐recruiting population established in Landvikvannet, a lake on the Norwegian coast of Skagerrak that turned brackish following artificial connection to the sea. Sprat was first reported in Icelandic waters in 2017, and in subsequent years it has become increasingly frequent and has spread along the south and west cost of the country. As the population of origin of this introduction was unknown, we used a panel of 91 SNP loci that display high genetic resolution in this species to characterize the genetic background of 64 sprat individuals collected in Icelandic waters in 2021. Comparison with existing reference data clearly identified the oceanic component as the likely source of the Icelandic sprat, and three potential scenarios can be considered to explain the colonization process. Because adult sprat generally exhibit limited long‐distance movement and are largely sedentary, a scenario involving adult migration into Iceland can be reasonably ruled out. Natural dispersal of eggs or larvae from the Faroe Islands cannot be entirely dismissed under specific conditions, given the complex oceanographic circulation southeast of Iceland. However, an anthropogenically mediated vector—most notably transport via ballast water—remains a more plausible mechanism.

Most of the previously large cod stocks in the North Atlantic are depleted to very low levels. A notable exception has been the Northeast Arctic cod inhabiting the Barents Sea. This cod stock reached a record high level around 2013, but since then has declined sharply, with older fish being fished out and few new recruits entering the stock. More specifically, since 2006 the average recruitment at age 3 per unit spawning stock biomass has dropped to a very low level. Here we review recent literature and data to evaluate potential causes of poor recruitment. We find that in most years the large spawning stock was successful in producing offspring up to the 0‐group stage, but the survival thereafter was reduced—leading to few recruits into the fishable stock. Evidence points to consequences of northwards shifts of spawning locations, reduced inflow of Calanus and density dependent factors influencing pre‐recruit survival at times when the spawning stock was at a record high level. However, large uncertainties in the causes of recruitment failure remain at a time when the Barents Sea ecosystem is experiencing unprecedented warming. A precautionary measure to avoid further decline and potential stock collapse in the current situation is to lower fishing pressure and improve management by setting reference points based on the recent period with low productivity. Including demographic characteristics like age diversity as explicit management targets to ensure spatial and temporal spread in spawning should be a goal for future method development.

The European sprat is a small pelagic fish characterised by genetically distinct populations including the Norwegian fjords, the Baltic Sea, the oceanic component ranging from the North Sea, Kattegat–Skagerrak, Celtic Sea and Bay of Biscay, as well as the southern groups such as the Mediterranean (Adriatic) and Black Seas. Additionally, a self-recruiting population evolved in Landvikvannet, a lake on the Norwegian coast of Skagerrak that turned brackish following artificial connection to the sea. Sprat was first reported in Icelandic waters in 2017, and in subsequent years it has become increasingly frequent and has spread along the south and west cost of the country. As the population of origin of this introduction was unknown, we used a panel of 91 SNP loci that display high genetic resolution in this species to characterize the genetic background of 64 sprat individuals collected in Icelandic waters in 2021. Analysis of Icelandic sprat, compared with existing reference data, clearly identified the oceanic component as the likely source of the introduction. While this aligns with expected colonisation routes along the Greenland-Scotland Ridge associated with range-expansion, it does not preclude an anthropogenically-driven vector, such as transport via ballast water.

Stock assessments are often based on age-structured data obtained by interpreting calcified structures. Due to readability and human error, the observed age may be wrong. We propose a parametric model for age-reading error matrices, which is more realistic and robust than the commonly used empirical matrices. The parameters have meaningful interpretations, allowing for direct comparison of age-reading properties. We compare different species (Atlantic mackerel ( Scomber scombrus) and herring ( Clupea harengus)), stocks (North Sea autumn-spawning vs. Norwegian spring-spawning herring), and calcified structures (otoliths vs. scales). Three out of four data sets had an asymmetry tendency towards reading higher ages than the true age. The estimated probability of reading the wrong age was lower for scales than for otoliths. The true age is often unknown and assumed to be the modal age. We assess the systematic bias due to this assumption. Finally, when including age-reading error in stock assessment, the dominating age classes were estimated to be larger and spawning stock biomass lower. Our study contributes with methods and insight for including age-reading error in stock assessment.

Sustainable fisheries management is important for the continued harvest of the world's marine resources, especially as they are increasingly challenged by a range of climatic and anthropogenic factors. One of the pillars of sustainable fisheries management is the accurate identification of the biological units, i.e., populations. Here, we developed and implemented a genetic baseline for Atlantic herring harvested in the Norwegian offshore fisheries to investigate the validity of the current management boundaries. This was achieved by genotyping > 15,000 herring from the northern European seas, including samples of all the known populations in the region, with a panel of population‐informative SNPs mined from existing genomic resources. The final genetic baseline consisted of ~1000 herring from 12 genetically distinct populations. We thereafter used the baseline to investigate mixed catches from the North and Norwegian Seas, revealing that each management area consisted of multiple populations, as previously suspected. However, substantial numbers (up to 50% or more within a sample) of herring were found outside of their expected management areas, e.g., North Sea autumn‐spawning herring north of 62° N (average = 19.2%), Norwegian spring‐spawning herring south of 62° N (average = 13.5%), and western Baltic spring‐spawning herring outside their assumed distribution area in the North Sea (average = 20.0%). Based upon these extensive observations, we conclude that the assessment and management areas currently in place for herring in this region need adjustments to reflect the populations present. Furthermore, we suggest that for migratory species, such as herring, a paradigm shift from using static geographic stock boundaries towards spatial dynamic boundaries is needed to meet the requirements of future sustainable management regimes.

The identification and quantification of prey ingested is a limiting factor in trophic ecology studies and is fundamental for assessing the impact of a predator on prey populations. Vendace (Coregonus albula) and whitefish (C. lavaretus) are two congeneric species, which are commonly preyed on by Baltic ringed seals (Pusa hispida). The otoliths of these two species are, however, very similar and distinguishing between them in the seal diet using visual inspection has so far been challenging. Here, otolith shape outline analyses were used in combination with machine learning techniques to discriminate between eroded vendace and whitefish otoliths from ringed seal diet samples. An experiment of in vitro digestion of the otoliths was performed to train a machine learning model. Our model is able to self-assign known digested otoliths back to their species of origin with >90% accuracy. Furthermore, 89% (N = 690) of the otoliths collected from digestive tract samples could be successfully assigned to species level, i.e. vendace or whitefish. This method is readily applicable for improved understanding of ringed seal feeding habits and predator–prey interactions, as well as large-scale applications to generate seal-predation matrix inputs for stock assessments of vendace and whitefish. Further development of the machine learning techniques to discriminate between prey species in seal and other piscivorous diets is strongly encouraged.