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A new dataset on the diet of Atlantic cod in the Barents Sea from the 1930s to the present day has been compiled to produce one of the largest fish diet datasets available globally. Atlantic cod is one of the most ecologically and commercially important fish species in the North Atlantic. The stock in the Barents Sea is by far the largest, as a result of both successful management and favourable environmental conditions since the early 2000s. As a top predator, cod plays a key role in the Barents Sea ecosystem. The species has a broad diet consisting mainly of crustaceans and teleost fish, and both the amount and type of prey vary in space and time. The data – from Russia, Norway and the United Kingdom – represent quantitative stomach content records from more than 400 000 fish and qualitative data from 2.5 million fish. Many of the data are from joint collaborative surveys between Norway and Russia. The sampling was conducted throughout each year, allowing for seasonal, annual and decadal comparisons to be made. Visual analysis shows cod diets have changed considerably from the start of the dataset in the 1930s to the present day. There was a large proportion of herring in the diets in the 1930s, whereas in more recent decades capelin, invertebrates and other fish dominate. There are also significant interannual asynchronous fluctuations in prey, particularly capelin and euphausiids. Combining these datasets can help us understand how the environment and ecosystems are responding to climatic changes, and what influences the diet and prey switching of cod. Trends in temperature and variability indices can be tested against the occurrence of different prey items, and the effects of fishing pressure on cod and prey stocks on diet composition could be investigated. The dataset will also enable us to improve parametrization of food web models and to forecast how Barents Sea fisheries may respond in the future to management and to climate change. The Russian data are available through joint projects with the Polar Branch of the Russian Federal Research Institute of Fisheries and Oceanography (VNIRO). The UK and Norwegian data (Townhill et al., 2020) are being released with this paper at 10.21335/NMDC-2139169383. [ABSTRACT FROM AUTHOR]

A new dataset on the diet of Atlantic cod in the Barents Sea from the 1930s to the present day has been compiled, to produce one of the largest fish diet datasets available globally. Atlantic cod is one of the most ecologically and commercially important fish species in the North Atlantic. The stock in the Barents Sea is by far the largest, as a result of both successful management and favourable environmental conditions since the early 2000s. As a top predator, cod plays a key role in the Barents Sea ecosystem. The species has a broad diet consisting mainly of crustaceans and teleost fish, and both the amount and type of prey vary in space and time. The data, from Russia, Norway and the United Kingdom, represents quantitative stomach contents records from more than 400,000 fish, and qualitative data from 2.5 million fish. Much of the data is from joint collaborative surveys between Norway and Russia. The sampling was done throughout each year allowing for seasonal, annual and decadal comparisons to be made. Visual analysis shows cod diets have changed considerably from the start of the dataset in the 1930s to the present day. There was a large proportion of herring in the diets in the 1930s, whereas in more recent decades, capelin, invertebrates and other fish dominate. There are also significant interannual asynchronous fluctuations in prey, particularly capelin and euphausiids. Combining these datasets can help us understand how the environment and ecosystems are responding to climatic changes, and what influences the diet and prey switching of cod. Trends in temperature and variability indices can be tested against the occurrence of different prey items, and the effects of fishing pressure on cod and prey stocks on diet composition could be investigated. The dataset will also enable us to improve parametrisation of food web models, and to forecast how Barents Sea fisheries may respond in the future, to management and to climate change. The Russian data is available through joint projects with Polar branch of VNIRO. The UK and Norwegian data (Townhill et al., 2020) is being released with this paper at https://doi.org/10.21335/NMDC-2139169383. [ABSTRACT FROM AUTHOR]

Large‐scale patterns in species diversity and community composition are associated with environmental gradients, but the implications of these patterns for food‐web structure are still unclear. Here, we investigated how spatial patterns in food‐web structure are associated with environmental gradients in the Barents Sea, a highly productive shelf sea of the Arctic Ocean. We compared food webs from 25 subregions in the Barents Sea and examined spatial correlations among food‐web metrics, and between metrics and spatial variability in seawater temperature, bottom depth and number of days with ice cover. Several food‐web metrics were positively associated with seawater temperature: connectance, level of omnivory, clustering, cannibalism, and high variability in generalism, while other food‐web metrics such as modularity and vulnerability were positively associated with sea ice and negatively with temperature. Food‐web metrics positively associated with habitat heterogeneity were: number of species, link density, omnivory, path length, and trophic level. This finding suggests that habitat heterogeneity promotes food‐web complexity in terms of number of species and link density. Our analyses reveal that spatial variation in food‐web structure along the environmental gradients is partly related to species turnover. However, the higher interaction turnover compared to species turnover along these gradients indicates a consistent modification of food‐web structure, implying that interacting species may co‐vary in space. In conclusion, our study shows how environmental heterogeneity, via environmental filtering, influences not only turnover in species composition, but also the structure of food webs over large spatial scales. [ABSTRACT FROM AUTHOR]