Variations in the biomass of Antarctic krill (Euphausia superba) around the South Shetland Islands, 1996–2006

Summary

Researchers reexamined 11 years of underwater sound data (1996-2006) used to estimate krill populations around the South Shetland Islands, applying better mathematical models and improved methods for identifying different species. Their new physics-based stochastic distorted wave Born approximation (SDWBA) model generated krill biomass estimates that matched more closely with physical net sampling data than older calculation methods had achieved. The analysis revealed two significant population surges in 1996 and 2003 that corresponded with young krill recruitment events detected in traditional net surveys. Although this improved approach eliminated systematic measurement errors, it also increased data variability by excluding acoustic signals that were previously counted as krill, which may result in more cautious fishing quotas under current precautionary management frameworks.

The map shows the current AMLR research sampling area (2003–2006) with marked locations of permanent monitoring stations used for biological and water condition measurements, along with the broader survey region. The outlined areas represent the three US AMLR zones where krill population estimates are calculated. Depth contour lines indicate 500-meter and 1000-meter water depths.

Key Findings

Found that krill body orientation caused the greatest variation in acoustic signals, followed by body condition (fatness) for krill longer than 25 mm.

Showed that using the same acoustic identification criteria across all krill sizes and locations produces unreliable results, particularly for smaller krill under 30 mm.

Confirmed that Northern krill (M. norvegica) consistently produce positive acoustic differences between 38 and 120 kHz frequencies, unlike air-filled organisms.

Demonstrated that Northern krill can be acoustically distinguished from mesopelagic fish species when multiple frequencies are analyzed simultaneously.

Results showed that acoustic identification ranges must be adapted for different krill species, body sizes, and regional characteristics rather than using universal values.

Findings recommend adopting these enhanced methods for future krill population assessments and management decisions.

Abstract

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 (DSv), 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.

Published in

ICES Journal of Marine Science

2008

Authors

Reiss, C. S., Cossio, A. M., Loeb, V., and Demer, D. A.

Institutions

Southwest Fisheries Science Center, La JollaMoss Landing Marine Laboratories

Methods

DataBiological sampling FieldAcoustic

Read the full paper

Go to doi.org