Marine Scotland

ABSTRACTThe black‐legged kittiwake (Rissa tridactyla, hereafter ‘kittiwake’, conservation status ‘Vulnerable’) is a long‐lived, highly motile and wide‐ranging seabird. Breeding kittiwake colonies are abundant across the northern hemisphere. The kittiwake's life history and the spatial scale of its breeding distribution make understanding colony connectivity a challenge; current species management models kittiwake colonies as closed units. Here, we explored the use of Bayesian analysis of multilocus microsatellite genotypes in the program BayesAss (BA3) to infer dispersal and seasonal summer breeding movements (information‐gathering behaviour; prospecting) (collectively ‘connectivity’) of kittiwakes around the North Atlantic. This approach uses the concept of inheritance by descent (IBD) (the formulation of genotypes within a population mediated by inheritance) and Markov‐chain Monte Carlo (MCMC) resampling to quantify patterns of breeding movements among spatial aggregations of related individuals. Data comprised diploid microsatellites of the kittiwake and the common seabird tick (Ixodes uriae) sampled from the High Arctic to the lower southern boundary of the species between the years of 1992 and 2001. Kittiwake dispersal and summer breeding movements, the latter derived from tick microsatellites, were heterogenous among the sampled colonies. There was an east to west longitudinal trend in dispersal. Summer breeding movements were more localised, although still present at large spatial scales. Connectivity among kittiwake colonies was less likely across the Atlantic Ocean. This study supports the prevailing theory that geographic distance only weakly constrains connectivity among kittiwake colonies. Multimodal relationships between geographic distance and connectivity indicate that other factors, such as colony status and conspecific associations may be more important.

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.

Segregating alleles in natural populations can be driven to fixation or loss by genetic drift or directional selection, or may be maintained in a polymorphic state by balancing selection. Balancing selection in a panmictic population is theoretically well established, but not widely understood at the molecular level. In this study, we focus on the evolutionary processes affecting non-synonymous variants at eight functionally relevant loci (based on candidate SNP genotyping) in a deep-sea fish species (Coryphaenoides rupestris) that lives across habitat zones ranging from ~200 m to ~2000 m depth. At each of these loci, one allele is predominant in the deeper water. Across a shallower depth range, we find that minor allele frequencies show a highly significant increase or decline progressively across five defined age categories. At single depths below a threshold depth, the deep-water allele declines in frequency with age. Together, these data indicate segregation to different depths, either shallow or deep, and balancing selection to retain variants needed for each depth range. This is supported by signals for long-term balancing selection at these loci (based on published genomic data). We discuss alternative interpretations and conclude that balancing selection maintaining ecotype diversity is the best supported mechanism.

BACKGROUND:Familial chylomicronemia syndrome (FCS) is a rare autosomal recessive disorder. This study aimed to study the genotype distribution of FCS-causing genes in the United Kingdom, genotype-phenotype correlation, and clinical differences between FCS and multifactorial chylomicronemia syndrome (MCS).METHODS:The study included 154 patients (FCS, 74; MCS, 80) from the UK FCS national registry and the UK arm of the FCS International Quality Improvement and Service Evaluation Project.RESULTS:FCS was relatively common in non-Europeans and those with parental consanguinity (P<0.001 for both). LPL variants were more common in European patients with FCS (European, 64%; non-European, 46%), while the genotype was more diverse in non-European patients with FCS. Patients with FCS had a higher incidence compared with patients with MCS of acute pancreatitis (84% versus 60%; P=0.001), recurrent pancreatitis (92% versus 63%; P<0.001), unexplained abdominal pain (84% versus 52%; P<0.001), earlier age of onset (median [interquartile range]) of symptoms (15.0 [5.5–26.5] versus 34.0 [25.2–41.7] years; P<0.001), and of acute pancreatitis (24.0 [10.7–31.0] versus 33.5 [26.0–42.5] years; P<0.001). Adverse cardiometabolic features and their co-occurrence was more common in individuals with MCS compared with those with FCS (P<0.001 for each). Atherosclerotic cardiovascular disease was more prevalent in individuals with MCS than those with FCS (P=0.04). However, this association became nonsignificant after adjusting for age, sex, and body mass index. The prevalence of pancreatic complications and cardiometabolic profile of variant-positive MCS was intermediate between FCS and variant-negative MCS.CONCLUSIONS:The frequency of gene variant distribution varies based on the ethnic origin of patients with FCS. Patients with FCS are at a higher risk of pancreatic complications while the prevalence of atherosclerotic cardiovascular disease is lower in FCS compared with MCS. Carriers of heterozygous pathogenic variants have an intermediate phenotype between FCS and variant-negative MCS.

Abstract The deep sea remains the biggest challenge to biodiversity exploration, and anthropogenic disturbances extend well into this realm, calling for urgent management strategies. One of the most diverse, productive, and vulnerable ecosystems in the deep sea are sponge grounds. Currently, environmental DNA (eDNA) metabarcoding is revolutionising the field of biodiversity monitoring, yet complex deep-sea benthic ecosystems remain challenging to assess even with these novel technologies. Here, we evaluate the effectiveness of whole-community metabarcoding to characterise metazoan diversity in sponge grounds across the North Atlantic by leveraging the natural eDNA sampling properties of deep-sea sponges themselves. We sampled 97 sponge tissues from four species across four North-Atlantic biogeographic regions in the deep sea and screened them at the universal COI barcode region. We recovered unprecedented levels of taxonomic diversity per unit effort, especially across the phyla Chordata, Cnidaria, Echinodermata and Porifera, with at least 406 metazoan species. These assemblages identify strong spatial patterns in relation to both latitude and depth, and detect emblematic species currently employed as indicators for these vulnerable habitats. We unveil the remarkable performance of sponges as high-resolution natural samplers of environmental DNA from across the whole animal kingdom and illustrate their vast potential as accurate, low-impact biomonitoring solutions for highly diverse, vulnerable deep-sea ecosystems.

With the increasing trend of energy transition to low-carbon economies, the rate of offshore structure installation and removal will rapidly accelerate through offshore renewable energy development and oil and gas decommissioning. Knowledge of the location and size of offshore infrastructure is vital in the management of marine ecosystems and also for safe navigation at sea. The availability of multimodal data enables the systematic assessment of offshore infrastructure. In this article, we propose an automatic solution for the geolocation and size evaluation of offshore infrastructure through a data fusion model of Sentinel-1 synthetic aperture radar (SAR) data and Sentinel-2 multispectral instrument imagery. The use of the Sentinel-1 (SAR) data aims to quickly localize candidate offshore energy infrastructure with its all-weather imaging capabilities, while the high-resolution optical data provided by the Sentinel-2 can enable more accurate localization and measurement of the offshore infrastructure. To be specific, a candidate detection model is applied to a time series of Sentinel-1 images to extract the “guided area” of the infrastructure, followed by morphological operation-based precise localization within an individual Sentinel-2 image, as well as estimating the size of each structure. With validation against the ground truth data of the Scottish waters from the baseline and closing bays, to the limit of the exclusive economic zone of Scotland, an area of 371 915 km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , our method has automatically identified 332 objects with an omission error of 0.3% and a commission rate of 0%. Our method was comprehensively compared with two state-of-the-art offshore energy infrastructure detection algorithms. The results validate that our method achieves the highest overall accuracy of 99.70%, surpassing the compared ones by 3.84%–12.50%. For the size evaluation, the achieved mean errors of the topside area size of oil/gas platforms and diameter length measurement of wind turbines both are 1 pixel in Sentinel-2 images, providing an effective technique for the identification and estimation of offshore infrastructure.

Abstract Anchoring and mooring systems are identified as a key area of innovation in the context of recent increasing demand in Floating Offshore Wind (FLOW) installations. This paper presents the technology assessment of the JAVELIN Anchor developed by Reflex Marine Ltd for FLOW application in the JAVELIN anchor demonstration program. The deepset JAVELIN Tensile anchor provides a competitive anchoring solution for FLOW installed with low cost work vessel and proven drilling technique. Several design criteria have to be met: i) sufficient strength of the material in ultimate limit state and the fatigue limit state. ii) anchor design to have low installation and capital cost. iii) efficient in various type of geotechnical formation. The strength of the material is analysed in finite element package, namely Ansys. A Tensile Member in Carbon Steel met the design requirement with a diameter 0.2 m for 1000 t application. In addition, the maximum load cases are modeled in hydrodynamic software, namely Orcaflex to simulate the dynamics of the JAVELIN anchor for several sea state, soil resistance and mooring configurations, taking into account the coupled dynamics between wind turbine, floater and mooring systems. For water depths varying from 200–400 m, the tension values are lower than the load cases studied in the strength of the material.