S34.5: Mechanisms of prey-patch detection by foraging seabirds

1Section of Neurobiology, Physiology and Behaviour, University of California, Davis, California, 95616, USA, fax 530 752 5582, e-mail ganevitt@ucdavis.edu; ²Biology Department, The College of Staten Island, 2800 Victory Boulevard, Staten Island, NY 10314, USA, e-mail veit@postbox.csi.cuny.edu

The study of pelagic birds at sea increased dramatically in the 1970’s and since then analysis of shipboard data has focused on drawing inferences from patterns of spatial variation in abundance. It is the goal of this paper to describe how birds at sea can be studied to relate their behaviour to the spatial variation in the abundance of their prey. There are few published studies that have tried to quantify seabird behaviour on the basis of data collected from ships; we hope to inspire further work of this sort with this paper.

We begin by suggesting two important reasons why behaviour at sea needs to be researched in greater detail. First, in a comparative framework, pelagic seabirds are physiologically exceptional - they drink salt water, dive to remarkable depths, remain at sea for years on end, and some species (the procellariiforms) have developed an extraordinary sense of smell. Pelagic birds search for patches of prey that are sparsely and unpredictably spread out (e.g. Furness & Camphuysen 1997), so it is likely that selection for improving the efficiency of foraging has been strong. Second, it is becoming more and more evident that populations of seabirds throughout the world are threatened by man’s activities. There is increasing need to forecast how each species’ predicament may worsen, given climate change or resource depletion resulting from over-fishing or other human actions. Clearly, the simple existence of a prey stock is not sufficient to assure that birds that depend on that stock will fare well; birds must also be able to detect and locate prey with great efficiency to insure survival and reproduction. We would like, for example, to be able to predict the fate of a population of seabirds, given differing assessments of future stock sizes. To make such predictions, we have to be able to quantifiably link feeding success to prey stock size. We cannot accomplish this goal without understanding the details of how birds forage at sea.

While studying the behaviour of pelagic birds at sea presents formidable logistic problems, there are also advantages that render this system well suited to the analysis of foraging behaviour. Seabirds can be viewed without obstruction from the deck of a ship, and the distribution of their prey can be mapped continuously using acoustics or continuous plankton recorders. The apparent simplicity of the ocean environment thus presents a rare opportunity to match behavioural decisions with the geometric arrangement of resources within that environment.

Our objective here is to review the mechanisms of how pelagic seabirds find prey. The investigations we discuss combine controlled behavioural experimentation performed at sea with statistical analysis of seabird distribution patterns relative to prey abundance, as well as computer simulation. This paper is a preliminary analysis of the work that has been accomplished to date and suggests a need for future work in this area.

Work in this area has focused on experimental at-sea studies of procellariiform seabirds. Members of this group have among the largest olfactory bulbs of any bird, suggesting that olfaction plays a fundamental role in their life history and behaviour (Bang 1965; 1966; 1971; Minguez 1997). Results from several behavioural studies suggest that a pronounced sense of smell assists in foraging. For example, many species are attracted to fishy smelling odorants (e.g. cod liver oil, tuna oil or fish homogenate), suggesting that procellariiforms use their sense of smell to locate food sources (Grubb 1972; Hutchison & Wenzel 1980; Lequette et al. 1989; Verheyden & Jouventin 1994; Nevitt & Hunt 1996). However, it is still not known which natural aromatics are used to hunt for food under normal foraging conditions.

We have recently presented experimental evidence that many species within this group are highly attracted to a naturally occurring scented compound, dimethyl sulphide (DMS; Nevitt et al. 1995; Nevitt & Hunt 1996; Fig. 1). Marine DMS is a by-product of the metabolic decomposition of dimethyl sulphoniopropionate (DMSP) in marine phytoplankton (most notably, Phaeocystis pouchetii). Laboratory studies indicate that this process is dramatically accelerated during grazing by zooplankton (Dacey & Wakeham 1986; Kellor et al. 1989; Daly & DiTullio 1996). The ability to detect and recognise DMS as a feeding cue could thus be advantageous to a seabird trying to locate and exploit zooplankton-rich areas, especially as natural DMS emissions are not strictly ephemeral, but can persist for hours or even several days (Berressheim 1987). Since DMS tends to be high in areas where productivity is also high, this presents the possibility that birds may use natural odour landscapes to locate areas where food tends to be historically abundant (McTaggart & Burton 1992). Indeed, peak numbers of surface-foraging prions Pachyptila sp. have recently been reported to coincide with peaks in zooplankton abundance near Bird Island (Goss et al. 1997). These birds also respond to DMS in experimental trials (Nevitt et al. 1995). In addition our preliminary results correlating at-sea measurements of species densities with changing DMS concentrations suggest that members of this group are abundant in areas where DMS is naturally elevated (Nevitt, unpublished).

Investigations with DMS suggest that procellariiforms may use this odour to identify a general area where prey is likely to be found, but can birds smell prey such as Antarctic Krill Euphausia superba directly? If so, is there a species-specific attraction to krill aromatics as there appears to be for DMS? Finally, could a species-specific difference in olfactory responsiveness reflect differences in diet or foraging strategies? In terms of what we know, both whole krill homogenates and component aromatics derived from krill, including trimethylamine (TMA) and pyrazene (PYR), appear to attract Leach’s Storm-petrels Oceanodroma leucorhoa in breeding colonies on Kent Island, New Brunswick (Clark & Shah 1992), but little information is available for Antarctic species. Results from pilot experiments suggest that some Antarctic procellariiform species are highly attracted to surface oil slicks spiked with krill homogenate but other species respond indifferently to krill odours. Cape Petrels Daption capense, for example, responded five times as much to experimental vegetable oil slicks scented with krill homogenate as compared to plain vegetable oil slicks, whereas Wilson's and Black-bellied Storm-petrels (Oceanites oceanicus and Fregetta tropica) showed no such difference (Nevitt in press). These distinctive olfactory responses may indeed reflect differences in foraging strategies since storm-petrels showed highly significant responses to DMS-scented slicks whereas Cape Petrels did not (Nevitt et al. 1995). Pilot trials suggest that PYR and TMA also attract foraging Antarctic procellariiforms, but species-specific responses have not yet been addressed.

It is likely that procellariiforms use odour cues in at least two distinct types of foraging activity. As has been commonly noted, birds may zigzag upwind to focus activity near the source of an odour plume (e.g. Hutchison & Wenzel 1980; see below). Alternatively, tubenoses may use ‘odour landscapes’ to identify general regions where prey is likely to be found (Nevitt et al.1995). This behaviour does not imply that birds follow odour gradients to locate a likely feeding target, but that potentially rich feeding grounds share an olfactory signature that the long distance forager recognises upon arrival. Elevated sea and atmospheric levels of DMS are known to be associated with shelf breaks, seamounts and areas of general upwelling (McTaggart & Burton 1992). These localities represent areas of high primary productivity where many species of procellariiform seabirds are known to forage. Odour cues associated with these regions would logically provide birds with a direct and instantaneous means of assessing the potential productivity of such historically rich areas. Such site-specific olfactory cues may also trigger a behavioural bias or ‘switch’ in long distance foragers to engage upon arrival in visual search strategies aimed at pinpointing feeding activity by other seabirds and marine mammals.

For visual searches, we have explored two possible search tactics: ‘Area-Restricted Searches’ (ARS) and ‘Local Enhancement’ (LE). ARS is a method of restricting one’s search to areas where the likelihood of prey encounter is high (e.g. Kareiva & Odell 1987). LE uses other foraging seabirds or marine predators as cues for locating prey (Bayer 1983; Clark & Mangel 1984; Brown 1988; Buckley 1996).

ARS is one of the simplest search modes. It only requires that a bird can distinguish between areas of high and low prey density within a local region. The basic hypothesis is that once a bird detects prey, it increases its turning rate (Fig. 2). This action, changing from a straight-line flight to a series of course changes, has the consequence of keeping the forager within the vicinity of the prey. The sensory cues that trigger this switch from a straight-line flight to ARS need to be determined but probably involve a combination of olfactory, visual and probably other inputs. We have not yet explored ARS in the context of olfaction so the discussion here will focus on visual ARS.

Despite its simplicity, ARS can be effective, in the sense that it can result in aggregations of foragers around patches of prey. Most demonstrations of ARS in the wild have been for insects (e.g. Kareiva & Odell 1987). However, the use of ARS has also been described in thrushes (Smith 1974) and some species of pelagic birds (Veit et al. 1994; Nevitt et al. 1995; Veit & Prince 1997). ARS is relatively simple to monitor at sea. Observers, blind to the amount of prey in the area, target a bird with binoculars and record each time a bird turns by ~90 degrees or more over a given period of time. Each turning event is entered into a laptop computer and thus receives a time-stamp for when it occurred. The length of time between turns is called a ‘step-length’ and serves as a reflection of how tightly a bird mills around a given area (Fig. 2).

Evidence for the use of ARS by seabirds has been accumulating from the Antarctic and Subantarctic. Cape Petrels at South Georgia change their flight directions five times as often when near a krill swarm than when over krill-less water (Veit et al. 1994; Veit & Prince 1997; Fig. 3). Similarly, giant-petrels increase their turning rate by a factor of five over krill swarms, and White-chinned Petrels turn significantly more when presented with DMS aerosols (Nevitt et al. 1995). However, ARS by albatrosses occurs at a much larger spatial scale: with these birds, long periods of straight-line flight are interspersed with periods of milling (Prince et al. 1992; Veit & Prince 1997). These large-scale ARS patterns may be of particular value for using seabirds as monitors of krill or other prey: as a consequence, birds travel farther when prey stocks are scarce than when they are plentiful, resulting in lowered densities of birds at sea.

It has been evident for years (Collins 1884; Murphy 1936) that seabirds use each other as cues for locating food. However, pelagic seabird biologists need to work hard to dispel the folklore (birds of a feather..) that pelagic birds search for food as co-ordinated groups. Most seabirds search individually, while carefully monitoring the actions of others. There have been many detailed descriptions of this process (e.g. Hoffman et al. 1980; Porter & Sealy 1982; Bayer 1983; Grover & Olla 1983; Chilton & Sealy 1987; Harrison et al. 1991, Mahon et al. 1992, Silverman & Nevitt 1995), but more effort is needed to quantify the potential benefits (Fraser et al. 1989). We do not wish to imply that hunting in flocks never occurs and carries no advantages to foraging seabirds. Gotmark et al. (1986) have shown in a laboratory setting how capture success of individual gulls is higher when those individuals are part of a flock. Individuals in flocks benefit from prey (fish) being simultaneously startled by many predators at once. This kind of benefit may well be important to seabirds, but it is different from a benefit arising from the combined searches of numerous individuals.

The quantitative evidence suggesting a benefit of LE is mostly theoretical (Haney et al. 1992; Bretagnolle 1993). We have recently simulated foraging trajectories of seabirds over computer-generated krill swarms (Veit & Barnes, unpublished; Meir 1997). Using simulated birds that each have their own flight speed, radius of prey detection and probability of detecting a patch within the radius, we found that LE would be beneficial under a particular set of circumstances (Fig. 4). We hypothesised that one reason LE should be beneficial is that other feeding birds should be visible from a much greater horizontal distance than are swarms of krill, or whatever prey the seabird seeks. So we simulated albatrosses searching for krill patches, and varied in each simulation the farthest distance at which an albatross could detect a flock of foraging birds. This distance was expressed in terms of a multiple of the distance at which an albatross could detect a krill patch directly. Our simulation showed that, for albatrosses to benefit from LE, flocks of foraging birds ought to be visible from at least 10-100 times farther away than are krill patches (Fig. 4A). We also have begun to identify conditions that would benefit an albatross if it searched for flocks of penguins that have located krill, rather than searching for krill directly. Our simulations suggest that albatrosses will benefit by searching for penguins only if penguins are 5-10 times more likely to detect a krill patch than they are (Fig. 4B). This may be true, given the much greater depth-range exploited by penguins (Ancel et al. 1992), but more work needs to address the underlying sensory capabilities of these seabirds before any firm conclusions can be drawn.

Perhaps more importantly, if birds do gain by monitoring the foraging success of other birds, fish, and mammals, this suggests a mutualistic relationship that is likely to have consequences at a population level. That is, it stands to reason that if individual seabirds catch more food when watching the actions of others, then reproductive success is likely, within a range of values, to be positively related to population size. Thus it is possible that, below some threshold, reproductive success will be lowered due to the difficulty that lone birds have in locating prey swarms. There is evidence that spatial distributions of species at sea reflect a mutual association: in the South Atlantic, abundance relationships among species that share the same habitats are generally positive (Veit 1995). This pattern would be expected if species ‘used’ each other to locate prey, to mutual benefit (e.g. Hunt et al. 1992; Silverman & Nevitt 1995). Clearly these and the other behavioural tactics reviewed here need to be evaluated when devising conservation recommendations for marine birds. This paper thus stands as a plea that more attention be focused in this area to insure effective management and conservation for the future.

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Fig. 1. Experimental data from olfactory trials performed at sea near South Georgia. This graph illustrates the remarkably similar olfactory responses of Wilson’s Storm-petrels to DMS (black squares) and cod liver oil (white squares). While the ship was stationed, either a control, DMS, or cod liver oil scented slick was deployed off the stern. A team of two observers blind to the treatments being tested entered numbers, behaviours and species of birds into handheld computers. Observations were made every minute starting at two minutes before deployment. Data are combined from 10 paired trials for DMS and 6 paired trials for cod liver oil and are normalised to the numbers of birds present in the visual area before slicks were deployed. Responses to control slicks have been subtracted (from Nevitt et al. 1995).