| Summary: | The study seeks to increase our knowledge on deepwater demersal fish assemblages and the biological adaptations of Antimora rostrata. This widespread deep-living demersal teleost is essentially used as an example species. Managing deepwater resources and communities is especially difficult since our knowledge of the community structure, ecology and biology of individual species is limited, and fishery independent information is scarce. In this account focus is directed towards the use of longlines in describing deepwater assemblages. New information on the biology of A. rostrata is presented, and experimental and alternative ageing methods are explored. The study was an element of MAR-ECO, a field project of the Census of Marine Life (www.coml.org), studying the diversity and biology of biota along the mid-Atlantic Ridge (MAR). As part of the 2004 MAR-ECO expedition to the mid-Atlantic Ridge, the chartered Norwegian fishing vessel M/S Loran deployed longline sets across the ridge axis, sampling a depth range of about 4000 m. Overall, chondrichthyans dominated the catches on the MAR and contributed nearly 60% in terms of weight and numbers. Multivariate analysis (MDS) using species-by-station data indicated an assemblage distribution that related primarily to factors varying by depth and latitude. Grouping patterns of stations were not very pronounced, suggesting a gradual rather than abrupt change in species composition by depth or latitude. Catch rates peaked at the shallower stations in the Charlie-Gibbs Fracture Zone (CGFZ), and generally decreased with depth. Relatively large individuals dominated, and the overall mean weight was 2.4 kg. Average fish weight was higher in the sub-area sampled just north of the Azores archipelago than in the CGFZ sub-area. No depth-related pattern of individual fish size was found. The findings suggest that the use of longline is a valuable and possibly necessary tool for describing the larger scavenging fish assemblages on rough bottom at greater depths. Among the many ...
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