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    Mapping encounters between Antarctic krill fishing vessels and air-breathing krill predators using acoustic data from the fishery

    Request Meeting Document
    Document Number:
    WG-EMM-2024/21
    Author(s):
    Bahlburg, D., S. Menze, B.A. Krafft, A.D. Lowther and B. Meyer
    Submitted By:
    Mr Dominik Bahlburg (Germany)
    Approved By:
    Professor Bettina Meyer (Germany)
    Abstract

    Assessing the spatial overlap between krill fisheries and krill predators is challenging due to the logistical and financial constraints associated with monitoring at the scale of management units. As a result, many existing studies are spatially and temporally limited. Here, we analysed more than 30'000 hours of echosounder data collected during commercial fishing operations by three vessels over six fishing seasons in CCAMLR Subareas 48.1-48.3 to investigate the temporal and spatial dynamics of direct encounters between krill fishing vessels, penguins and marine mammals. Penguins and whales/seals that dive under fishing vessels produce distinct signals in the acoustic data. Analysing their spatial distribution and annual dynamics showed that: 1. The South Orkney Islands, the main fishing area, are also a hotspot for predator encounters, which are often more frequent than in other Subareas. 2. Penguin encounter rates can be as high in winter as in summer. 3. The Antarctic Peninsula was primarily associated with whale/seal encounters, while the South Orkney Islands were the hotspot for penguin encounters. At South Georgia, penguin and whale/seal encounter rates could match those of the other two Subareas, but interannual variability was relatively high. Our results further demonstrate that a holistic approach is required to effectively reduce interactions between krill predators and fisheries, going beyond the protection of individual regions or predator colonies. Finally, acoustic data from fishing vessels provide a wealth of information that can be used to support fisheries management. They are highly cost-effective, have unique temporal and spatial coverage, and approaches such as ours could be developed into management tools that provide rapid and large-scale data that are highly complementary to other sampling programmes.