Poleward shifts in marine fisheries under Arctic warming

As global warming makes the Arctic Ocean more accessible, concerns have been raised about the environmental consequences of a possible expansion of commercial fisheries into pristine marine ecosystems. Using a recently released global dataset, we quantify for the first time how fishing activities are responding to diminishing sea ice and a warmer Arctic Ocean. We show that trawling dominates Arctic fisheries and that this activity penetrates rapidly into Arctic shelf areas previously protected by extensive ice-cover as a response to interannual sea ice loss. We model the development of trawling activity under a climate change scenario and use the model to identify areas with high risk of increased trawling activity and estimate the amount of trawling avoided in recently established fishery protection zones. Stronger responsibility must be undertaken by Arctic coastal states to regulate increased fishing pressure and protect vulnerable Arctic shelf ecosystems.publishedVersio

An appraisal of the drivers of Norwegian spring‐spawning herring (Clupea harengus) recruitment

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Ecosystem-related monitoring, assessments and management advices for the Norwegian, Barents and North Seas

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Gyrodactylus triglopsi n. sp. (Monogenea: Gyrodactylidae) from the Gills of Triglops nybelini Jensen, 1944 (Teleostei: Cottidae) in the Barents Sea

Introduction Monogeneans of the genus Gyrodactylus were found on the gills of specimens of the bigeye sculpin Triglops nybelini Jensen, 1944 caught by trawl in the Barents Sea in January–February 2016. Methods Morphological preparations of the parasites were examined and photographed under a microscope at magnifications of × 100–1000 and morphometric analyses were carried out on 22 specimens using ImageJ2 software. Eight of the specimens used for the morphological comparisons were also subjected to molecular analyses by sequencing a region of the ribosomal DNA spanning partial 18S, the internal transcribed spacers 1 and 2 (ITS1 and 2), 5.8S and partial 28S and comparing this with other species through a BlastN-search in GenBank and through phylogenetic analyses. Results The morphology of the species from T. nybelini was markedly different to that of any of other species of Gyrodactylus. It is characterized by having relatively long hamulus roots, a character that it shares with two other species described from marine sculpins (Cottidae); G. armatus and G. maculosi. It also has a narrow rectangular ventral bar membrane with a posterior notch which it shares with G. maculosi only. Compared with all the seven species from marine Cottidae described so far, it has the smallest opisthaptoral hard parts. A comparison of the internal transcribed spacer (ITS) rDNA sequence with available sequences in GenBank and a phylogenetic analyses also showed it to be highly divergent from other sequences. Therefore, a new species is proposed, Gyrodactylus triglopsi n. sp. Conclusion Both the morphological and molecular analyses support the status of G. triglopsi as a new species. This is to our knowledge the first species of Gyrodactylus described from Triglops nybelini and the description extends the list of Gyrodactylus species found on fish in the Barents Sea to 17.publishedVersio

Multiple stakeholders’ perspectives of marine social ecological systems, a case study on the Barents Sea

The Barents Sea ecosystem components and services are under pressure from climate change and other anthropogenic impacts. Following an Ecosystem-based management approach, multiple simultaneous pressures are addressed by using integrative strategies, but regular prioritization of key issues is needed. Identification of such priorities is typically done in a ‘scoping’ phase, where the characterization of the social-ecological system is defined and discussed. We performed a scoping exercise using an open and flexible multi-stakeholder approach to build conceptual models of the Barents Sea social-ecological system. After standardizing vocabulary, a com plex hierarchical model structure containing 155 elements was condensed to a simpler model structure con taining a maximum of 36 elements. To capture a common understanding across stakeholder groups, inputs from the individual group models were compiled into a collective model. Stakeholders’ representation of the Barents Sea social-ecological system is complex and often group specific, emphasizing the need to include social scientific methods to ensure the identification and inclusion of key stakeholders in the process. Any summary or simpli fication of the stakeholders’ representation neglects important information. Some commonalities are highlighted in the collective model, and additional information from the hierarchical model is provided by multicriteria analysis. The collective conceptual stakeholder model provides input to an integrated overview and strengthens prioritization in Ecosystem-based management by supporting the development of qualitative network models. Such models allow for exploration of perturbations and can inform cross-sectoral management trade-offs and prioritiespublishedVersio

Contaminants reach everywhere: Fish dietary samples should be surface decontaminated prior to molecular diet analysis

Knowledge of trophic interaction is necessary to understand the dynamics of ecosystems and develop ecosystem-based management. The key data to measure these interactions should come from large-scale diet analyses with good taxonomic resolution. To that end, molecular methods that analyze prey DNA from guts and feces provide high-resolution dietary taxonomic data. However, molecular diet analysis may also produce unreliable results if the samples are contaminated by external sources of DNA. Employing the freshwater European whitefish (Coregonus lavaretus) as a tracer for sample contamination, we studied the possible route of whitefish in beaked redfish (Sebastes mentella) guts sampled in the Barents Sea. We used whitefish-specific COI primers for diagnostic analysis, and fish-specific 12S and metazoa-specific COI primers for metabarcoding analyses of intestine and stomach contents of fish samples that were either not cleaned, water cleaned, or bleach cleaned after being in contact with whitefish. Both the diagnostic and COI metabarcoding revealed clear positive effects of cleaning samples as whitefish were detected in significantly higher numbers of uncleaned samples compared to water or bleach-cleaned samples. Stomachs were more susceptible to contamination than intestines and bleach cleaning reduced the frequency of whitefish contamination. Also, the metabarcoding approach detected significantly more reads of whitefish in the stomach than in intestine samples. The diagnostic analysis and COI metabarcoding detected contaminants in a higher and comparable number of gut samples than the 12S-based approach. Our study underlines thus the importance of surface decontamination of aquatic samples to obtain reliable diet information from molecular data.publishedVersio

Quantifying diets for small pelagic fish: effects of weight versus occurrence methods and sampling effort

In the Norwegian Sea, assessment of diet composition relies on annual cruise activity combined with visual identification and weight determination of prey from fish stomachs. This weight-based method is labour intensive, and suggestions to reduce cost include moving from the weight-based to the occurrence-based method and/or reducing sampling effort. Studies have suggested that the occurrence-based method may be more robust while providing similar results as the weight-based method. Here we re-analyse data from >14.000 stomachs for herring, mackerel, and blue whiting. We compare diet composition estimates and quantify the uncertainty using both methods. We also quantify the impact of reducing sampling effort (number of trawl stations and fish per station) on the diet uncertainties. Our results confirm that occurrence-based estimates are more precise than those based on weight. In addition, they are better at capturing year-to-year fluctuations. The occurrence-based method provides similar results to the weight-based method. Differences between methods arise primarily from disparities in the mean weight of prey in stomachs. Decreasing the number of stations sampled leads to increased uncertainty, while reducing the sampling effort from 10 to 5 fish per station has little impact on uncertainty estimates. These results provide quantified insights to guide future diet monitoring programmes.publishedVersio