Journal
ICES JOURNAL OF MARINE SCIENCE
Volume 65, Issue 4, Pages 497-508Publisher
OXFORD UNIV PRESS
DOI: 10.1093/icesjms/fsn033
Keywords
acoustic survey; Antarctic krill; biomass densities; Euphousia superba; target identification; target strength.
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The time-series of acoustically surveyed Antarctic krill (Euphausia superba) biomass near the South Shetland Islands (SSI) between 1996 and 2006 is re-estimated using a validated physics-based model of target strength (TS), and a species-discrimination algorithm based on the length-range of krill in plankton samples to identify krill acoustically, derived from TS-model predictions. The SSI area is surveyed each austral summer by the US Antarctic Marine Living Resources Program, and the acoustic data are used to examine trends in krill biomass and to assess the potential impact of fishing to the reproductive success of land-based predators (seals and penguins). The time-series of recomputed biomass densities varies greatly from that computed using an empirical log-linear TS-model and fixed-ranges of differences in volume-backscattering strengths (Delta S-v), conventionally used to identify krill acoustically. The new acoustic estimates of biomass are significantly correlated with both proportional recruitment and krill abundance estimated from zooplankton samples. Two distinct peaks in biomass (1996 and 2003) are in accord with recruitment events shown by net-based krill time-series. The foundation for the new TS-model and the associated krill-discrimination algorithm, coupled with the agreement between acoustic- and net-survey results, provides strong support for the use of the new analytical technique. Variable biases in the re-estimated krill biomass have been greatly reduced. However, survey variability increased as a result of the increased rejection of acoustic backscatter previously attributed to krill. Management of Southern Ocean krill stocks based on a precautionary approach may therefore result in decreased allocations of krill, given its dependence on the variability of survey estimates.
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