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- Materials and methods
Broad-scale telemetry studies have greatly improved our understanding of the ranging patterns and habitat-use of many large vertebrates (Wiig, Born & Pedersen 2003; Baumgartner & Mate 2005). However, there often remains considerable uncertainty over the function of different areas or the factors influencing habitat selection. Further insights into these processes can be obtained through analyses of finer-scale movement patterns. For example, animals influence their encounter rates with prey by modifying search behaviour in response to food distribution and abundance (Hill, Burrows & Hughes 2003; Biesinger & Haefner 2005). Within the marine environment, prey are often distributed in patches (Boyd 1996) and predators can take advantage of the spatial autocorrelation of prey density by using area-restricted search behaviours (Dixon 1959; Kareiva & Odell 1987; Wolf & Hainsworth 1990). Animals may intensify search effort within a prey patch by lowering speed and increasing turning rate. In areas of poorer food quality an extensive search mode is expected, where rapid, straight-line travel minimizes the time spent between patches and reduces search redundancy (Zollner & Lima 1999). Consequently, perception of food quality can dictate directly which mode of search behaviour is employed, and has an important effect on the movement patterns of animals (Fortin 2003).
The relationship between search patterns and the distribution of food has rarely been documented for large free-ranging animals (Ward & Saltz 1994; Mårell, Ball & Hofgaard 2002). In marine systems, the spatial distribution of fish prey is poorly known at small temporal and spatial scales, making comparison between predator search effort and prey density extremely difficult. Marine predators also mainly forage beneath the surface, so that observations of feeding are rare (Heithaus et al. 2002). Quantitative analysis of movement paths can therefore provide an important technique to overcome these challenges and improve our understanding of the foraging strategies of marine predators.
The increasing use of radio and satellite telemetry has resulted in a rapid rise in the amount of movement data available (Hays et al. 2003; Wilson et al. 2005), but analysis techniques have developed more slowly. Studies of marine mammal movements have been largely descriptive or involved single measures such as distance travelled or swimming speed (McConnell et al. 1999; Whitehead & Rendell 2004). An alternative approach is a correlated random walk model (CRW). Predicted moves are determined by a random selection from empirical distributions of move lengths and turning angles. The preference for an animal to move in the direction of its head is accounted for by assuming a distribution of turning angles centred around 0° (Turchin 1998). Deviations from this model can provide insights into the search strategy adopted (Ward & Saltz 1994). For example, significant differences in speed and move length were found between grey seal trajectories fitting and deviating from a CRW (Austin, Bowen & McMillan 2004).
Animals not only make decisions about their foraging path, but also how long to stay within each patch. The time allocated to an area should provide an indication of the profitability of the patch and the trade-off between diminishing returns and the cost of finding another prey patch (Pyke, Pulliam & Charnov 1977). This time allocation can be measured using first-passage time (FPT) (Johnson, Milne & Wiens 1992). Fauchald & Tveraa (2003) extended this technique so that the spatial scale and location of concentrated search effort could be determined. This has been applied recently to the paths of foraging albatrosses, in which 85% of these exhibited an area-restricted search pattern and scale-dependent adjustments were made in relation to environmental features (Pinaud & Weimerskirch 2005). However, data obtained from satellite transmitters generally provide data on relatively coarse spatial (several kilometres) and temporal scales (generally less than seven localizations per day). This will prevent adjustments made at finer scales being identified. In this paper, movement pattern models will be applied to the tracks of bottlenose dolphins (Tursiops truncatus Montagu), derived from land-based theodolite surveys that record accurately the animals’ fine-scale position.
Within their home range, predators are known to exhibit differential habitat use (Ingram & Rogan 2002). In the inner Moray Firth (Scotland), sightings of bottlenose dolphins were concentrated in three small regions, suggesting that these may be important foraging areas (Wilson, Thompson & Hammond 1997). However, these areas are all narrow channels so it remains possible that they could be acting as bottlenecks, aggregating the animals and inflating the sighting rate. Thus, these areas may not provide critical habitat, but simply a passageway to other favourable sites. If this is the case, one would expect directed travel behaviour through the channel. In contrast, if these areas are important for foraging, movements are likely to be characterized by convoluted tracks indicative of searching behaviour. Analyses of dolphin movement paths can therefore provide additional insight into the function of these areas.
The objectives of this study were to use the fine-scale trajectories of bottlenose dolphins within one of these channels to establish whether the area was a preferred site for foraging or a bottleneck. The applicability of a CRW model was examined to test if the dolphins were moving randomly. FPT analysis was used to measure time allocation in different areas and to determine whether foraging behaviours occurred primarily within the intensively searched areas.
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- Materials and methods
Modelling movement as a CRW provides a firm foundation from which to investigate the foraging strategies of animals and develop more complex models. This has rarely been used to quantify the movement of large animals and generally at only coarse spatial and temporal scales. The FPT approach allowed quantification of the time allocation to patches and enabled both the identification of the spatial scale and location of areas where search effort was concentrated (Fauchald & Tveraa 2003).
Only a quarter of the track sections were classed as CRW movement, despite the key assumptions of no serial correlation in move lengths or turning angles being satisfied. In contrast to the CRW model, in which directionality is determined internally based on the previous move direction, a BRW is characterized by external directionality as a fixed compass direction is followed. This suggests that the dolphins are capable of using cues based not only on their recent prior experience to find suitable foraging areas, but over a larger temporal and spatial scale. It may also indicate a preference for particular habitat characteristics to aid them in finding food, as the dominant compass direction followed the main northern deep channel through the study area.
BRW movement was characterized by significantly smaller turning angles than those trajectories moving very short net distances (overpredicted by the CRW model). Turning behaviour is therefore an important factor determining whether movement is strongly directional or concentrated within a small area. The identification of distinct behaviour types, which may occur within the same track, reveals that the animals switch between different types of movement on relatively fine-scales. Such switches in behaviour have also been demonstrated in several other species (Morales & Ellner 2002; Jonsen, Flemming & Myers 2005). Morales et al. (2004) found that to describe elk movement, models with two movement states usually outperformed the single model. Although two distinct movement types were identified in our study, a high degree of variability in the movement parameters, turning angle and move length, between tracks may reflect responses to local environmental conditions (Kareiva & Shigesada 1983; Jonsen & Taylor 2000) or individual variability (Pinaud & Weimerskirch 2005).
The presence of two distinct modes of behaviour provides evidence that the dolphins were displaying area-restricted search behaviours. When prey are present in clumps, this tactic can achieve a higher energy gain than using only one mode or moving randomly (Nolet & Mooij 2002). These behaviours may therefore be in response to the patchy distribution of prey, as has been demonstrated in copepods (Tiselius 1992). In plaice, intensive search behaviour was characterized by short movements and frequent turning (Hill, Burrows & Hughes 2000). Tuna displayed both an increase in turning rate and lower swimming speeds (Newlands, Lutcavage & Pitcher 2004).
The FPT approach revealed that animals varied the amount of time they allocated to different areas along their movement paths. Although the study area encompasses the only route to more inshore parts of the Moray Firth, the movement patterns recorded in this study indicate that it does not act solely as a passageway. On the majority of occasions, dolphins spent large amounts of time in small, localized areas within the channel. Furthermore, they often did not continue on to the higher reaches of the Firth, but returned outwards. This suggests that the entrance to the Inverness Firth is a site selected specifically by the dolphins and is not simply acting as a bottleneck. The sites of concentrated search effort appeared to be foraging locations and may explain the dolphins’ preference for this area.
Search activity was confined generally to relatively small areas (< 300 m radius). Pienkowski (1983) found that plovers moved less far after taking large prey than after taking small or no prey. This suggests that the small search radii could be a consequence of large, highly nutritional prey being taken in this area. Alternatively, it may reflect the size of the prey patches. Nolet & Mooij (2002) found that there was a match between the scale of food clumps (pondweed tubers) and the movement patterns of swans, indicating that they were causally linked. The scale and location could also be representative of the areas in which prey could be caught. There may be specific habitat characteristics or fish school sizes that enable prey to be caught more easily by the dolphins. Studies on killer whales have found that they feed on small schools of herring in an area where herring is mainly present in large shoals (Similä 1997). It is possible that smaller groups make it easier for the predator to target individual prey.
Overlap in search effort was highest in three key areas. The area off one of the peninsulas, Chanonry Point, was used the most frequently. It also tended to have the longest search durations and hence time allocation, indicating that foraging success was greatest in this area. The other frequently searched sites were off the peninsula on the other side of the channel and in the centre of the main channel. These three sites all have steep seabed slopes and rapidly reach depths of over 40 m. The water current speed around the peninsulas and in the centre of the deep-water channel is also considerable, and may reach 3·5 knots during the spring tide (Admiralty Chart 1077). High frequencies of cetacean sightings off headlands and narrow channels have also been observed in other areas (Ingram & Rogan 2002; Simard, Lavoie & Saucier 2002). These features may aid the capture of fish by increasing their ability to detect or manipulate prey and provide barriers against which to herd them (Hastie et al. 2004).
Predators may be attracted to predictable aggregations of prey rather than to areas with the highest prey densities, as they have incomplete knowledge of prey distributions (Begg & Reid 1997). Hydrographic processes can result in features that provide such predictable aggregations of prey. Associations between fronts and seabirds (Decker & Hunt 1996; Skov & Prins 2001) and marine mammals (Brown & Winn 1989; Tynan 1997; Mendes et al. 2002) have been observed, suggesting a preference for predictable food sources by these animals. A tidal front forms in the area at the centre of the main channel (Helen Bailey unpublished data) where overlap of search effort was high, indicating that the dolphins regularly foraged there. The results from this study can be examined in relation to environmental factors such as these. In the marine environment, water currents can have a significant effect on the direction and speed of movement over ground and their impact could also be further investigated using these techniques.
This study has provided insight into the fine-scale movement patterns of bottlenose dolphins and demonstrated the use of two quantitative techniques to further our understanding of their foraging strategies. Evidence of both extensive and intensive search behaviours are likely to be in response to the patchy distribution of prey, and indicates that this spatial autocorrelation can be used by marine predators to find food. These movement patterns can therefore be used to determine the function of different habitats and identify sensitive areas. The techniques have the potential to be applied to a wide variety of species, particularly as the accuracy of tracking technology continues to increase (Ryan et al. 2004), and are valuable analysis tools where prolonged visual observation of the subject is not feasible.