GLORIA

GEOMAR Library Ocean Research Information Access

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Oxford University Press  (1)
  • 2010-2014  (1)
Document type
Years
Year
  • 1
    Publication Date: 2014-11-18
    Description: Antarctic krill ( Euphausia superba ) are a key species in Southern Ocean ecosystems, maintaining very large numbers of predators, and fluctuations in their abundance can affect the overall structure and functioning of the ecosystems. The interannual variability in the abundance and biomass of krill was examined using a 17-year time-series of acoustic observations undertaken in the Western Core Box (WCB) survey area to the northwest of South Georgia, Southern Ocean. Krill targets were identified in acoustic data using a multifrequency identification window and converted to krill density using the Stochastic Distorted-Wave Born Approximation target strength model. Krill density ranged over several orders of magnitude (0–10 000 g m –2 ) and its distribution was highly skewed with many zero observations. Within each survey, the mean krill density was significantly correlated with the top 7% of the maximum krill densities observed. Hence, only the densest krill swarms detected in any one year drove the mean krill density estimates for the WCB in that year. WCB krill density ( µ , mean density for the area) showed several years (1997/1998, 2001–2003, 2005–2007) of high values ( µ 〉 30 g m –2 ) interspersed with years (1999/2000, 2004, 2009/2010) of low density ( µ 〈 30 g m –2 ). This pattern showed three different periods, with fluctuations every 4–5 years. Cross correlation analyses of variability in krill density with current and lagged indices of ocean (sea surface temperature, SST and El Niño /Southern Oscillation) and atmospheric variability (Southern Annular Mode) found the highest correlation between krill density and winter SST (August SST) from the preceding year. A quadratic regression ( r 2 = 0.42, p 〈 0.05) provides a potentially valuable index for forecasting change in this ecosystem.
    Print ISSN: 1054-3139
    Electronic ISSN: 1095-9289
    Topics: Biology , Geosciences , Physics
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...