Summary

This investigation has shown that during the five day surveys conducted at two sites around South Georgia there was high variability in both the number and characteristics of krill swarms. Strong correlation was observed between the number of krill swarms and mean areal krill density. The three-types of krill swarm used in the multi-variate partition analysis showed overlap with krill swarm types previously defined by Mauchline (1980) and Hamner and Hamner (2000). The three swarm types exhibited broadly agreed with swarm types seen by Lascara et al. (1999) on the Antarctic peninsula, as did the on/off shelf locations of the swarm types: high density swarms were found to persist in certain on shelf areas. It should be remembered however, that swarm metrics showed overlap (Figure 2.6), so the classification of swarm type, may not represent the underlying aggregative behaviour of krill.

The question still remains as to what the driving mechanisms are for the generally lower ˆρin the WCB compared to the ECB. Potentially this is caused by predation (Brierley et al., 1997b), but it may also be caused by different water masses advecting krill into the South Georgia area (Trathan and Murphy, 2003; Meredith et al., 2005). Are predators causing the ˆρ difference between boxes, or is the different predator distribution between boxes a consequence of the ˆρ difference? In the next chapter the large scale, core box, relationships between predator encounters and ˆρ are investigated.

Variability in the at-sea distribution

of air breathing krill predators off

South Georgia during three summer

surveys, 1997 to 1999

3.1

Introduction

This chapter examines spatial and temporal variation in the at-sea distribution of air- breathing krill predators around the island of South Georgia (54o_{S 35}o_{W). Sixteen preda-} tor species, classified into three functional groups, were recorded over two study sites, one to the northwest, the other northeast of South Georgia, on three summer cruises (1997 to 1999). Mean sea surface temperature and krill density, at the spatial-scale of the study site (80 x 100 km), were considered as potential drivers of variation in predator distribu- tion. Variance in predator encounters was also assessed using a newly created summary metric, the ’index of variability’.

3.1.1

Marine predator-prey interactions

Marine predators forage in a heterogeneous environment and are generally dependent on spatially- and temporarily-varying aggregations of food resources (Horne and Schneider, 1995; Boyd, 1996; Sims et al., 2006, 2008). Characterising the variation in the foraging areas of marine predators, in response to changes in environmental conditions and prey availability is important in determining their ecological role (Barlow and Croxall, 2002; Reid et al., 2005) and in determining potential conflicts between predators and fisheries (Murphy et al., 1997; Reid et al., 2004).

At large scales (60 to 120 km) there is often a position correlation between prey and predators (Reid et al., 2004). The repeated aggregation of prey may be caused

by areas that have either environmentally favourable properties (Fauchald et al., 2000), or because of physical forcing mechanisms, such as upwelling (e.g. Genin 2004). At smaller scales predator-prey interactions, which must take place for consumption to occur, are frequently difficult to observe and interpret. Prey may adopt various types of anti- predation behaviour in response to predators, making the spatial relationship between predators and prey at small scales less predictable or measureable. For example, when prey are diluted or dispersed (Hamilton, 1971) in response to predators, there will be a progressive development of a negative spatial association with predators. Further, at small spatial scales (0.1 to 10 km), the state in which the predator-prey interactions are observed in is unknown. Generally when prey are observed to be diluted or dispersed, the mechanism causing this behaviour cannot be determined: a low-density of prey may have been caused by predator grazing, with the predators no longer being co-located with the prey at the time of observation. Alternatively, if the prey have formed dense aggregations, or are in an environmental refuge (Horne and Schneider, 1994), there may be a positive association with predators (Murphy et al., 1988). Therefore, while at larger spatial scales (50 to 200 km), time is less influential, at small scales (0.1 to 10 km) both spatial and temporal factors interact to obscure the spatial relationship between predators and prey (Haury et al., 1985).

Antarctic krill are known to aggregate at a variety of spatial scales. At the small spatial-scale krill have been observed to use both dilation and aggregation as an anti- predation behaviour (O’Brien, 1987; Hamner and Hamner, 2000). At large spatial-scales it has been suggested that krill aggregate over rapid changes in bathymetry (Mackas et al., 1985; Watkins, 2000).

The response of prey to the presence of predators varies with spatial scale. At larger scales prey may not engage in anti-predation behaviour since predators may be track- ing a physical process as a proxy of prey distribution, rather than actively foraging. At smaller scales prey may exhibit anti-predation behaviour, in response to predator attack or localised predator searching behaviour. Fauchald et al. (2000) describe the varying spatial scale of prey (capelin) as a hierarchical patch structure, within which the small- scale aggregative behaviour of predators and prey is capable of masking the signal of predator-prey interactions at larger-scales. This is particularly problematic when preda- tors and prey aggregate at different scales. Variation in the spatial scale of schooling small pelagic fish was observed by Petitgas et al. (2001) with the number of schools in a groups of schools, or clusters, being related to cluster density. Observing predator-prey interactions, particularly in the marine environment, is not a trivial task. Ultimately, the goal of predator-prey studies is to observe the spatial and temporal structure of the prey and predators, thereby allowing the foraging strategy of the predators, including searching

for prey and feeding, to be elucidated (Croll et al., 1998). These predator-prey interac- tions maybe complex because of spatial and temporal variation, and are made especially complex when these interactions are comprised of multi-predator species interactions (e.g. Croxall and Prince 1997 and Silverman and Veit 2001), under which predator species may be locating prey by reference to the foraging activities of other predators (e.g. Harrison et al. 1991), rather than the prey itself.