Variations in the biomass of Antarctic krill (Euphausia superba

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...

Full description

Bibliographic Details
Main Authors: Christian S. Reiss, Anthony M. Cossio, Valerie Loeb, David A. Demer
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2008
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.595.9481
http://swfsc.noaa.gov/uploadedFiles/Divisions/AERD/Publications/Reiss et al., 2008.pdf
Description
Summary: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 acous-tic- 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