Skip to main content

    Interannual variability in Antarctic krill (Euphausia superba) density at South Georgia, Southern Ocean: 1997 – 2013

    Request Meeting Document
    Document Number:
    S. Fielding, J. Watkins, P. Trathan et al.
    Submitted By:
    Mr Doug Cooper (CCAMLR Secretariat)
    ICES J. Mar. Sci., in press

    This paper, now in press in ICES Journal of Marine Science, presents krill density estimates for a 17 year time series of acoustic surveys of the Western Core Box at South Georgia.  Krill targets were identified in acoustic data using the approved CCAMLR protocol, that is using a multi-frequency identification window and converted to krill density using the Stochastic Distorted-Wave Born Approximation (SDWBA) target strength model. Krill density ranged over several orders of magnitude (0 to 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 (1997-8, 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 to 5 years. Cross correlation analyses of variability in krill density with current and lagged indices of ocean (Sea Surface Temperature, SST) and atmospheric variability (Southern Annular Mode, SAM and El Niño/Southern Oscillation, ENSO) found the highest correlation between krill density and winter sea-surface temperature (August SST) from the preceding year. A quadratic regression (r2 = 0.42, P<0.05) provides a potentially valuable index for forecasting change in this ecosystem.

    In addition to the paper, we present an additional table (Table 0) which takes the values of krill density from the paper, derives the total krill biomass for the survey area and provides commercial krill catches for SSMUs within subarea 48.3. Note that commercial catches within SGW are very small in comparison to the biomass in the WCB and even total commercial catch in subarea 48.3 is frequently less than 10% of the biomass within the WCB.