Effective ocean management and conservation of highly migratory species depends onresolving overlap between animal movements and distributions, and fishing effort.However, this information is lacking at a global scale. Here we show, using a big-data approach that combines satellite-tracked movements of pelagic sharks and global fishing fleets, that 24% of the mean monthly space used by sharks falls under the footprint of pelagic longline fisheries. Space-use hotspots of commercially valuable sharks and of internationally protected species had the highest overlap with longlines (up to 76% and 64%, respectively), and were also associated with significant increases in fishing effort.We conclude that pelagic sharks have limited spatial refuge from current levels of fishing effort in marine areas beyond national jurisdictions (the high seas). Our results demonstrate an urgent need for conservation and management measures at high-seas hotspots of shark space use, and highlight the potential of simultaneous satellite surveillance of megafauna and fishers as a tool for near-real-time, dynamic management.Industrialised fishing is a major source of mortality for large marine animals (marine megafauna) 1-6 . Humans have hunted megafauna in the open ocean for at least 42,000 years 7 , but international fishing fleets targeting large, epipelagic fishes did not spread into the high seas (areas beyond national jurisdiction) until the 1950s 8 . Prior to this, the high seas constituted a spatial refuge largely free from exploitation as fishing pressure was concentrated on continental shelves 3,8 . Pelagic sharks are among the widest ranging vertebrates, with some species exhibiting annual ocean-basin-scale migrations 9 , long term trans-ocean movements 10 , and/or fine-scale site fidelity to preferred shelf and open ocean areas 5,9,11 . These behaviours could cause extensive spatial overlap with different fisheries from coastal areas to the deep ocean. On average, large pelagic sharks account for 52% of all identified shark catch worldwide in target fisheries or as bycatch 12 . Regional declines in abundance of pelagic sharks have been reported 13,14 , but it is unclear whether exposure to high fishing effort extends across ocean-wide population ranges and overlaps areas in the high seas where sharks are most abundant 5,13 .Conservation of pelagic sharkswhich currently have limited high seas management 12,15,16would benefit greatly from a clearer understanding of the spatial relationships between sharks' habitats and active fishing zones. However, obtaining unbiased estimates of shark and fisher distributions is complicated by the fact that most data on pelagic sharks come from catch records and other fishery-dependent sources 4,15,16 .Here, we provide the first global estimate of the extent of space use overlap of sharks with industrial fisheries. This is based on the analysis of the movements of pelagic sharks tagged with satellite transmitters in the Atlantic, Indian and Pacific oceans, together with fishing vessel movements m...

These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.Scientific Data | (2020) 7:94 | https://doi.org/10.1038/s41597-020-0406-x www.nature.com/scientificdata www.nature.com/scientificdata/ circum-Antarctic synthesis yet exists that crosses species boundaries. This deficiency prompted the Expert Group on Birds and Marine Mammals (EG-BAMM) and the Expert Group on Antarctic Biodiversity Informatics (EGABI) of the Scientific Committee on Antarctic Research (SCAR; www.scar.org) to initiate in 2010 the Retrospective Analysis of Antarctic Tracking Data (RAATD). RAATD aims to advance our understanding of fundamental and applied questions in a data-driven way, matching research priorities already identified by the SCAR Horizon Scan 9,21 and key questions in animal movement ecology 22 . For these reasons, we worked on the collation, validation and preparation of tracking data collected south of 45 °S. Data from over seventy contributors (Data Contacts and Citations 23 ) were collated. This database includes information from seventeen predator species, 4,060 individuals and over 2.9 million at-sea locations. To exploit this unique dataset, RAATD is undertaking a multi-species assessment of habitat use for higher predators in the Southern Ocean 24 .RAATD will provide a greater understanding of predator distributions under varying climate regimes, and provide outputs that can inform spatial management and planning decisions by management authorities such as the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR; www.ccamlr.org). Our synopsis and analysis of multi-predator tracking data will also highlight regional or seasonal data-gaps.Scientific Data | (2020) 7:94 | https://doi.

International audienceSatellite telemetry data are a key source of animal distribution information for marine ecosystem management and conservation activities. We used two decades of telemetry data from the East Antarctic sector of the Southern Ocean. Habitat utilization models for the spring/summer period were developed for six highly abundant, wide-ranging meso- and top-predator species: Adélie Pygoscelisadeliae and emperor Aptenodytes forsteri penguins, light-mantled albatross Phoebetria palpebrata , Antarctic fur seals Arctocephalus gazella , southern elephant seals Mirounga leonina , and Weddell seals Leptony-chotes weddellii . The regional predictions from these models were combined to identify areas utilized by multiple species, and therefore likely to be of particular ecological significance. These areas were distributed across the longitudinal breadth of the East Antarctic sector, and were characterized by proximity to breeding colonies, both on the Antarctic continent and on subantarctic islands to the north, and by sea-ice dynamics, particularly locations of winter polynyas. These areas of important habitat were also congruent with many of the areas reported to be showing the strongest regional trends in sea ice seasonality. Th e results emphasize the importance of on-shore and sea-ice processes to Antarctic marine ecosystems. Our study provides ocean-basin-scale predictions of predator habitat utilization, an assessment of contemporary habitat use against which future changes can be assessed, and is of direct relevance to current conservation planning and spatial management efforts

Commercial sealing in the 18th and 19th centuries had a major impact on the Antarctic and subantarctic fur seal populations (Arctocephalus gazella and A. tropicalis) in the Southern Ocean. The intensive and unrestricted nature of the industry ensured substantial reductions in population sizes and resulted in both species becoming locally extinct at some sites. However, both species are continuing to recover, through the recolonization of islands across their former range and increasing population size. This study investigated the extent and pattern of genetic variation in each species to examine the hypothesis that higher levels of historic sealing in A. gazella have resulted in a greater loss of genetic variability and population structure compared with A. tropicalis. A 316-bp section of the mitochondrial control region was sequenced and revealed nucleotide diversities of 3.2% and 4.8% for A. gazella and A. tropicalis, respectively. There was no geographical distribution of lineages observed within either species, although the respective PhiST values of 0.074 and 0.19 were significantly greater than zero. These data indicate low levels of population structure in A. gazella and relatively high levels in A. tropicalis. Additional samples screened with restriction endonucleases were incorporated, and the distribution of restriction fragment length polymorphism (RFLP) and sequence haplotypes were examined to identify the main source populations of newly recolonized islands. For A. tropicalis, the data suggest that Macquarie Island and Iles Crozet were probably recolonized by females from Marion Island, and to a lesser extent Ile Amsterdam. Although there was less population structure within A. gazella, there were two geographical regions identified: a western region containing the populations of South Georgia and Bouvetoya, which were the probable sources for populations at Marion, the South Shetland and Heard Islands; and an eastern region containing the panmictic populations of Iles Kerguelen and Macquarie Island. The latter region may be a result of a pronounced founder effect, or represent a remnant population that survived sealing at Iles Kerguelen.