The Scotia Sea ecosystem is a major component of the circumpolar Southern Ocean system, where productivity and predator demand for prey are high. The eastward-flowing Antarctic Circumpolar Current (ACC) and waters from the Weddell-Scotia Confluence dominate the physics of the Scotia Sea, leading to a strong advective flow, intense eddy activity and mixing. There is also strong seasonality, manifest by the changing irradiance and sea ice cover, which leads to shorter summers in the south. Summer phytoplankton blooms, which at times can cover an area of more than 0.5 million km2, probably result from the mixing of micronutrients into surface waters through the flow of the ACC over the Scotia Arc. This production is consumed by a range of species including Antarctic krill, which are the major prey item of large seabird and marine mammal populations. The flow of the ACC is steered north by the Scotia Arc, pushing polar water to lower latitudes, carrying with it krill during spring and summer, which subsidize food webs around South Georgia and the northern Scotia Arc. There is also marked interannual variability in winter sea ice distribution and sea surface temperatures that is linked to southern hemisphere-scale climate processes such as the El Niño-Southern Oscillation. This variation affects regional primary and secondary production and influences biogeochemical cycles. It also affects krill population dynamics and dispersal, which in turn impacts higher trophic level predator foraging, breeding performance and population dynamics. The ecosystem has also been highly perturbed as a result of harvesting over the last two centuries and significant ecological changes have also occurred in response to rapid regional warming during the second half of the twentieth century. This combination of historical perturbation and rapid regional change highlights that the Scotia Sea ecosystem is likely to show significant change over the next two to three decades, which may result in major ecological shifts.

We used the instantaneous growth rate method to determine the effects of food, temperature, krill length, sex, and maturity stage on in situ summer growth of krill across the southwest Atlantic sector of the Southern Ocean. The main aims were to examine the separate effects of each variable and to generate a predictive model of growth based on satellite-derivable environmental data. Both growth increments in length on moulting (GIs) and daily growth rates (DGRs, mm d Ϫ1 ) ranged greatly among the 59 swarms, from 0.58-15% and 0.013-0.32 mm d Ϫ1 . However, all swarms maintained positive mean growth, even those in the low chlorophyll a (Chl a) zone of the central Scotia Sea. Among a suite of indices of food quantity and quality, large-scale monthly Chl a values from SeaWiFS predicted krill growth the best. Across our study area, the great contrast between bloom and nonbloom regions was a major factor driving variation in growth rates, obscuring more subtle effects of food quality. GIs and DGRs decreased with increasing krill length and decreased above a temperature optimum of 0.5ЊC. This probably reflects the onset of thermal stress at the northern limit of krill's range. Thus, growth rates were fastest in the ice edge blooms of the southern Scotia Sea and not at South Georgia as previously suggested. This reflects both the smaller size of the krill and the colder water in the south being optimum for growth. Males tended to have higher GIs than females but longer intermoult periods, leading to similar DGRs between sexes. DGRs of equivalent-size krill tended to decrease with maturity stage, suggesting the progressive allocation of energy toward reproduction rather than somatic growth. Our maximum DGRs are higher than most literature values, equating to a 5.7% increase in mass per day. This value fits within a realistic energy budget, suggesting a maximum carbon ration of ϳ20% d Ϫ1. Over the whole Scotia Sea/South Georgia area, the gross turnover of krill biomass was ϳ1% d Ϫ1.High-latitude ecosystems provide case studies of how environmental variability and change affect marine organisms. These ecosystems are characterized by low seasonal variation in temperatures, yet they are the fastest warming regions on the planet (Vaughan et al. 2003). They also exhibit great variability in phytoplankton abundance, which is related to narrow seasonal windows of primary production. Consequently, polar invertebrates tend to be stenothermal, sensitive even to slight changes in temperature, with life cycles 1 Corresponding author (aat@bas.ac.uk). AcknowledgmentsWe thank the captain, officers, and crew of the RRS James Clark Ross for their professional support during sampling, Peter Ward for running the 2002 cruise, Doug Bone for maintaining the nets, and Kate Arnold for her enthusiastic help with netting. Steve Nicol generously shared a design for the mass-rearing tanks for growth experiments and discussed methodology. Andrew Fleming accessed the SeaWiFS data, provided courtesy of NASA. Comments from two reviewers greatly i...

Determining how climate fluctuations affect ocean ecosystems requires an understanding of how biological and physical processes interact across a wide range of scales. Here we examine the role of physical and biological processes in generating fluctuations in the ecosystem around South Georgia in the South Atlantic sector of the Southern Ocean. Anomalies in sea surface temperature (SST) in the South Pacific sector of the Southern Ocean have previously been shown to be generated through atmospheric teleconnections with El Niñ o Southern Oscillation (ENSO)-related processes. These SST anomalies are propagated via the Antarctic Circumpolar Current into the South Atlantic (on time scales of more than 1 year), where ENSO and Southern Annular Mode-related atmospheric processes have a direct influence on short (less than six months) time scales. We find that across the South Atlantic sector, these changes in SST, and related fluctuations in winter sea ice extent, affect the recruitment and dispersal of Antarctic krill. This oceanographically driven variation in krill population dynamics and abundance in turn affects the breeding success of seabird and marine mammal predators that depend on krill as food. Such propagating anomalies, mediated through physical and trophic interactions, are likely to be an important component of variation in ocean ecosystems and affect responses to longer term change. Population models derived on the basis of these oceanic fluctuations indicate that plausible rates of regional warming of 1 o C over the next 100 years could lead to more than a 95% reduction in the biomass and abundance of krill across the Scotia Sea by the end of the century.

Interannual variability is a characteristic feature of the Southern Ocean ecosystem, yet the relative roles of biological and physical processes in generating these fluctuations are unknown. There is now extensive evidence that there are years when there is a very low abundance of Antarctic krill (Euphausia superba) in the South Georgia area, and that this variation affects much of the ecosystem, with the most obvious impacts on survival and breeding success of some of the major predators on krill. The open nature of the South Georgia ecosystem means this variability has large‐scale relevance, but even though there are unique time series of data available, information on some key processes is limited. Fluctuations in year‐class success in parts, or all, of the krill population across the Scotia Sea can generate large changes in the available biomass. The ocean transport pathways maintain the large‐scale ecosystem structure by moving krill over large distances to areas where they are available to predator colonies. This large‐scale physical system shows strong spatial and temporal coherence in the patterns of the interannual and subdecadal variability. This physical variability affects both the population dynamics of krill and the transport pathways, emphasizing that both the causes and the consequences of events at South Georgia are part of much larger‐scale processes.

The growth rates of postlarval krill (Euphausia superba) were measured across a wide range of environments in the Scotia Sea and around South Georgia using the Instantaneous Growth Rate (IGR) method. Each IGR experiment determined the intermolt period (IMP) and growth increment at molt (GI) of an average of 120 individuals incubated for 5 d in through-flowing ambient, filtered seawater. We examined the results from 51 IGR experiments involving 5,927 animals ranging between 25 mm and 62 mm. Animals were collected from an area that covered a latitudinal range of 10Њ and surface temperatures of between Ϫ0.85ЊC and 4.75ЊC. The measurement of IMP has rarely been achieved in IGR experiments because synchronous molting biases estimates. We overcame this by applying a binary logistic regression model to our data. This related IMP to temperature, body length, and maturity stage. Food did not influence IMP. Our model estimated that krill within our experiments had IMPs ranging from 9 d to 57 d. Temperature affected the IMP of females more than that of males. The IMPs of females were shortest around 2ЊC and increased at lower and higher temperatures. IMP increased with body size and altered according to gender, with male IMPs being 50% longer than those of equivalently sized females. One of the main assumptions of the IGR method is that the GI measured in the first few days reflects the in situ conditions experienced by krill in the previous intermolt period. However, we found that the GIs declined immediately and rapidly after capture, particularly when growth was initially high. Thus, conditions at time of molt also influence GI. We developed a method of correcting measured GIs to natural growth in field conditions. These refinements to IGR methodology (IMP and GI estimation) enable more accurate and precise predictions of krill growth rates in summer to be made.

Oceanographic data collected to the north of South Georgia were examined for three consecutive summers (1996/97, 1997/98, 1998/99). The results show the existence of a shelf break front during each period. The most reliable means of defining the front was the potential density anomaly at the near‐surface potential temperature minimum. In each year, off‐shelf waters were separated from on‐shelf waters by water with a potential density anomaly between 27.22 and 27.29 kg m−3. During 1997/98, the near‐surface potential temperature minimum was much colder and much shallower than in other years and was consistent with waters originating from much further south than South Georgia; these differences were further evident at a single deep off‐shelf station. The oceanographic changes during 1997/98 were consistent with a mesoscale or large‐scale movement of the southern Antarctic Circumpolar Current front. Acoustically determined densities of Antarctic krill, Euphausia superba, at South Georgia showed consistent patterns between years. Densities were substantially higher over the shelf compared with off‐shelf, with the highest densities at the shelf edge; densities were also higher to the east of the island. During 1997/98, acoustic densities of krill were substantially higher than in other years. The coincidence of the elevated acoustic density and the cooler oceanographic conditions was explored. When data from all years were combined and analysed by Generalized Additive Model, an inverse relationship between acoustic density and temperature was apparent. Historical data were also examined and it was noted that the only other occurrence of such a high estimate of krill density at South Georgia, was when oceanographic conditions were also colder.

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 (r2 = 0.42, p < 0.05) provides a potentially valuable index for forecasting change in this ecosystem.

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