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°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°N) (Hare et al.,

An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, encompassing both biotic and abiotic variables, and describing the ecological dynamics of the observed species. In this context, imaging devices are valuable tools that complement other biological and oceanographic monitoring devices. Nevertheless, large amounts of images or movies cannot all be manually processed, and autonomous routines for recognizing the relevant content, classification, and tagging are urgently needed. In this work, we propose a pipeline for the analysis of visual data that integrates video/image annotation tools for defining, training, and validation of datasets with video/image enhancement and machine and deep learning approaches. Such a pipeline is required to achieve good performance in the recognition and classification tasks of mobile and sessile megafauna, in order to obtain integrated information on spatial distribution and temporal dynamics. A prototype implementation of the analysis pipeline is provided in the context of deep-sea videos taken by one of the fixed cameras at the LoVe Ocean Observatory network of Lofoten Islands (Norway) at 260 m depth, in the Barents Sea, which has shown good classification results on an independent test dataset with an accuracy value of 76.18% and an area under the curve (AUC) value of 87.59%.

No abstract

Killer whales Orcinus orca have a cosmopolitan distribution with a broad diet ranging from fish to marine mammals. In Norway, killer whales are regularly observed feeding on overwintering Norwegian spring-spawning (NSS) herring Clupea harengus inside the fjords. However, their offshore foraging behavior and distribution are less well understood. In particular, it is not known to what degree they rely on the NSS herring stock when the herring move to deeper offshore waters. Satellite telemetry data from 29 male killer whales were analyzed to assess whether their offshore foraging behavior is linked to herring distribution. Unlike most marine predator-prey studies that use indirect proxies for prey abundance and distribution, our study utilized 2 herring density estimates based on (1) direct observations from acoustic trawl survey data and (2) simulations from a fully coupled ecosystem model. Mixed effects models were used to infer the effect of herring density and light intensity on whale movement patterns. Our results suggest that killer whales follow NSS herring over long distances along the coast from their inshore overwintering areas to offshore spawning grounds. All whales changed from fast, directed, to slow, non-directed movement when herring density increased, although individuals had different propensities towards movement. Our data indicated that whales continue to feed on herring along the Norwegian shelf. We conclude that NSS herring constitute an important prey resource for at least some killer whales in the northeastern Atlantic, not only during the herring overwintering period, but also subsequently throughout the herring spawning migration.