Recommendations

1. Integrated studies are useful for small-scale analyses for ecosystem monitoring (Atkin- son et al., 2001; Boyd and Murphy, 2001). A combination of satellite tracking, acous- tic moorings (Brierley et al., 2006) and ship-based predator and acoustic surveys are required to examine predator-prey interactions with a sufficiently high spatial and temporal sampling resolution to successfully elucidate predator-prey interactions. Such an integrated study could include predator diving activity as recorded from

(a) time 0 (b) time 1

(c) time 2 (d) time 3

(e) time 4 (f) time 5

Figure 4.8: The location of 100 x 100 m box (parallelogram above base of triangle) for observing predator observations from the RRS James Clark Ross was highly susceptible to ship motion, and is potentially a large source of error when spatially aligning predator and acoustic observations. Photographs are between 1 and 2 s apart.

biologging data to estimate availability bias in visual air-breathing predator surface observations. However, such corrections are not trivial and are outside the scope of this chapter, and cannot correct small spatial-scale observations.

2. Due to acoustic reverberation from wind and wave noise, the JCR hull mounted (depth 6 m) acoustic transducers cannot observe krill between the sea surface to a depth of c. 10 to 20 m. This prevents the acoustic assessment of krill density in this important shallow region, where many of the species in the large and small bird groups, and indeed many diving species, are constrained to forage. Consequently, it is not possible to observe krill air-breathing predator interactions using conventional hull-mounted acoustics, and this is potentially a severe limitation in determining krill X flying bird spatial overlap. An inclined or upward looking transducer could be used to observe this region (see Everson and Bone 1986; Hewitt and Demer 1996). 3. A simulation could be used to address the question of whether non-adaptive, ship-

based, line transect surveys are useful for identifying marine predator-prey spatial interactions. This simulation could be used to investigate the recovery of predator- prey interaction using a simulated krill distribution and a predator distribution with a known spatial overlap. Various line-transect methods could be applied to these data to obtain estimates of the simulated spatial overlap parameters. If the observa- tion technique used in this investigation doesn’t successfully recover the simulated predator-prey relationships, but other techniques do, then these other techniques should be adopted for future investigations.

4. The probable existence of availability bias in the visual observations make the preda- tor data considered here a n > 0 dataset. If no predators were sighted within a given transect length, it cannot be determined if this is a true absence of predators or caused by predators diving out of sight. This might also explain the increased cross correlation between predator species compared to predators X krill: since for facultative feeding to occur the predator species taking their foraging cue from the other predator species must be able to detect that predator species, which is impos- sible if the foraging species is underwater. There may be an abundance threshold at which a single predator species aggregation can be detected, since all the individuals in a larger foraging aggregation are unlikely to all be simultaneously underwater. Establishing a relationship between environmental covariates such as chlorophyll or sea surface temperature and predator abundance may allow the proportion of true absences in the sightings data to be estimated (see Zaniewski et al. 2002; Wintle et al. 2005).

5. The inter-survey variation in detectability of krill predators cannot be estimated. This research has implicitly assumed constant detectability. The collection of dis- tance data (see Buckland et al. 2001) to diving species, such as Antarctic fur seals, would allow detectabilty to be quantified. When combined with dive behaviour mod-

els, detectability could be used to estimate availability bias and, combined, these two models would allow abundance to be estimated and predator krill consumption rates calculated.

6. The weak cross-correlations may have been caused by a mismatch in the sampling volumes between the predator and the krill echosounder observations. The next chapter will use a multibeam echsounder, that samples a much larger volume of water, to assess very small scale (<500 m) predator-prey interactions in an effort to overcome this limitation.

Multibeam acoustic sampling of

Antarctic krill swarms

The research in this chapter has been submitted us:

Cox, M.J., Demer, D.A., Warren, J.D., Cutter, G.R. and Brierley, A.S. (submitted). Multibeam echosounder observations of Antarctic krill (Euphausia superba) swarms provide new insight to interactions between krill and air breathing predators. Marine Ecology Progress Series.

Cox, M.J., Demer, D.A., Warren, J.D., Cutter, G.R. and Brierley, A.S. (submitted). Three dimensional observations of Antarctic krill (Euphausia superba) swarms made using a multi-beam echosounder. Deep Sea Research II.

5.1

Introduction

Antarctic krill play a pivotal role in the Southern Ocean ecosystem (Atkinson et al., 2001; Mangel and Nicol, 2000), but are difficult to sample because of their extremely patchy distribution: much krill biomass is contained in a relatively few high-density swarms (Brierley et al., 1999b; Hofmann et al., 2004). Efforts to understand interactions between krill and their predators at sea have been hampered because of an inability to sample krill over appropriate scales (Logerwell et al., 1998; Hewitt and Demer, 2000). Attempts to link krill and predator distributions from observations along survey transects have been largely unsuccessful because the downward looking echosounders used to estimate krill abundance fail to detect krill swarms just off the track line that predators observed in the vicinity of the research vessel may be feeding upon. Conventional echosounders sample only a narrow cone (typically 7 degrees) beneath the research vessel. For a research vessel with a draft of 5 m this provides a window of observation just 3 m wide at 30 m depth.

vation to the sides of the survey track, and can effectively extend from the 2 dimensional view provided by vertical echosounders to 3 dimensions (Gerlotto et al. 1999 see Figure 5.1). This chapter describes field observations of krill made by a MBE, and reports 3D characteristics of krill swarms. The objective of the field observation programme was to assess the capability of a MBE system to sample krill. If MBE sampling is appro- priate for krill, it may enable collection of data leading to improved understanding of krill predator-prey interactions, krill swarm morphology and behaviour and, ultimately, perhaps to improved acoustic estimates of krill biomass.

Figure 5.1: Illustration of variation between sampling volumes of a vertically downward- looking split-beam echosounder (EK500, Simrad, Norway) and a Reson multi-beam echosounder (MBE, Seabat 6012, Reson, Denmark) vertically mounted with a 90o _swath width (from Fr´eon and Misund 1999). Note the MBE used in the investigation reported in this thesis had a 120o _{swath width, with the centre beam oriented vertically downward.} For the MBE to be a viable acoustic tool for biomass estimation, development of the current krill target strength (TS) models is required (Demer and Conti, 2003, 2005). TS models are used to scale acoustic observations to determine the numerical or biomass density of target organisms observed by an echosounder (MacLennan and Simmonds, 1992). In addition to body material composition, TS models are driven by animal length (l) and the dorsal angular orientation with respect to echosounder transducer face (θ) that is usually mounted looking vertically downwards. The varition of animal orientation relative to the various MBE beams means that so far it is not possible to estimate biomass using a MBE since for many species TS as a function of angle is unavailable.