Turtle tracking and diving behavior

Nine adult female leatherback turtles that had nested on the north shore of Grenada, Caribbean (12°12′ N, 61°36′ W) were tracked using satellite relayed dataloggers (SRDLs) linked to the Argos system. As well as providing location data, SRDLs also transmitted comprehensive information about turtle diving behavior, including depth and duration of individual dives (see Appendix A).

Argos location inaccuracies mean that speed of travel estimates determined from successive locations may still be subject to large error (Hays et al. 2001). We therefore determined the speed of travel by using pairs of locations that were at least three days apart. Because many locations could be obtained each day, often there was some overlap in the dates covered by successive speed of travel calculations, i.e., the procedure provided repeated independent estimates of speed of travel. Following procedures outlined previously (Hays et al. 2001) we confirmed the robustness of these speed calculations by identifying a strong autocorrelation between successive speed estimates. Finally, using all the independent estimates of speed, we determined the mean daily speed of travel for each individual.

Mapping tracks on remote-sensed imagery

Location and oceanographic data were incorporated into a geographic information system (GIS; ESRI 2004) allowing the overlay and analysis of biological and oceanographic spatial data. High resolution data sets covering the ocean surface include measurements taken from various types of sensors (including radiometers, scatterometers, and radars). Data on the sea surface temperature were acquired from the AVHRR (advanced very high resolution radiometer) on board the NOAA 14 satellite. The data used from June 2002 to September 2004 were received as a 4-km product as monthly composites. Pixel values were calibrated to temperature values in intervals of 0.1°C, areas with temperatures of less than −3°C were defined as cloud and were masked out, and a land mask of the North Atlantic coastline was applied to each image. Additional monthly composites of sea surface temperature data from the NOAA Geostationary Operational Satellite (GOES satellite) provided data free from cloud contamination (available online).⁵ The GOES images have a spatial resolution of 5.6 km and an accuracy of ±0.5°C.

The measurements of sea surface height anomalies (SSHA) were made from TOPEX/Poseidon satellite altimetry data, with a sea level measurement accuracy of 4.2 cm. The satellite images were incorporated into the GIS for spatial and temporal analysis. Fourteen-day maps of turtle tracks and remotely sensed images were combined for illustrative purposes.

Chlorophyll a concentration has been estimated from monthly composites (from June 2002 to September 2004) from the Sea-viewing Wide Field-of view Sensor (SeaWiFS satellite) LAC (Local Area Coverage), with a spatial resolution of 9 km². Pixel values were calibrated to 0.1 mg/m³; cloud and land masks were applied to the images. Data from the MODIS satellite-based sensor allowed analysis of higher resolution (4 km) monthly images (available online).⁶

Speed of movement of mesoscale features

To assess how mesoscale features moved within the North Atlantic we used TOPEX/Poseidon altimetry data to identify 10 cyclonic and 10 anticyclonic features that spanned a range of latitudes (0–60° N) and dates (July 2002–September 2004). TOPEX/Poseidon weekly composites were attained from the Colorado Center for Astrodynamics Research (available online).⁷ We used a GIS to identify the middle of each feature and then measured the distance moved by each feature at seven-day intervals until the feature was no longer visible.

Regional fidelity

Despite the fact that it is now widely reported that leatherback turtles may range across very large scales (many thousands of kilometers; Luschi et al. 2003, Ferraroli et al. 2004, Hays et al. 2004b, James et al. 2005b), there is increasing evidence that individuals may maintain at least some broad level of fidelity to different foraging ranges. For example, leatherbacks equipped with satellite tags on foraging grounds off Nova Scotia have been shown to move widely, traveling back to low latitudes in the winter before northerly summer movements back to broadly the same area occupied the previous year (James et al. 2005b). Similarly, two turtles that we tracked moving northward from the Caribbean to the northeastern coast of North America, confined their movements to the western Atlantic. The five individuals that we tracked heading northeast from the Caribbean in the direction of northern Europe, always stayed in the eastern Atlantic, and the two individuals tracked heading eastward from the Caribbean confined their movements to the tropical Atlantic. This evidence suggests that leatherbacks might leave their breeding sites heading toward some broad geographic region, e.g., western Atlantic, eastern Atlantic, or tropical Atlantic to which they maintain fidelity.

Behavioral plasticity

Within their broad fidelity to different regions of the North Atlantic, leatherbacks dive as they travel. This contrasts with some other marine vertebrates, such as penguins, which travel near the surface as they commute to prey patches close to their breeding sites (Radl and Culik 1999). The implication is that leatherback turtles continually forage as they travel. There have been a number of recent studies examining the variation in leatherback turtle behavior as they move large distances (Hughes et al. 1998, Hays et al. 2004a, James et al. 2005a, b, Sale et al. 2006). The results we present here are consistent with a general pattern for behavioral plasticity in this species, presumably reflecting changing prey fields. In the Atlantic, the changes in turtle dive behavior appear to be regionally specific. Turtles entering the Atlantic following the end of the breeding season show consistent increases in dive duration presumably reflecting increasing prey encounter (Hays et al. 2004a) as well as a diel component in diving that probably reflects feeding on vertical migrating plankton (Eckert et al. 1986, 1989, Hays et al. 2004a). A diel pattern of vertical migration, deep in the day and shallow at night, has been seen in many species of zooplankton, including jellyfish (for review see Hays 2003), and therefore in the daytime prey are probably too deep for leatherbacks to forage profitably, so less time is spent diving. The dive pattern exhibited once turtles entered the Atlantic was, however, not invariant. For example, one of the clearest patterns was for periods of very short shallow dives at high latitudes. This pattern has been seen recently for turtles equipped with satellite tags near Nova Scotia, Canada, and probably reflects the continuous near surface distribution of gelatinous prey at such latitudes (James et al. 2005a), with turtles bringing jellyfish to the surface for consumption. Indeed leatherback turtles at the surface have been directly observed in both the northwestern and northeastern Atlantic feeding on large jellyfish (Duron 1978, James and Herman 2001). In contrast to these two general patterns, at the southern-most latitudes (<9° N) that turtles reached after long periods of travel, we saw a pattern of diving mostly at dusk and dawn. Such a pattern is probably another manifestation of turtles feeding on vertically migrating prey. Yet in this case, prey come so close to the surface at night that deep dives are not required. Deep dives occur only at dawn and dusk as zooplankton migrate downward and upward, respectively, and are still shallow enough to make diving profitable.

It is known in general terms that gelatinous zooplankton may sometimes show patterns of normal diel vertical migration (DVM; Andersen et al. 1992, 1997, Youngbluth and Båmstedt 2001), but may sometimes also be found near the surface during the daytime (Brodeur et al. 2002, Graham et al. 2003). However, overall descriptions of basin-wide patterns of diel vertical migration in gelatinous zooplankton are not available. Our latitudinal changes in turtle dive behavior provide strong evidence that there is a systematic change in the depth distribution of gelatinous zooplankton in the North Atlantic with, for example, a preponderance of shallow living forms at high latitude vs. deeper living forms exhibiting strong DVM at midlatitudes. This conclusion is supported by other telemetry studies with leatherback turtles in the North Atlantic (James et al. 2005a).

There is increasing evidence that a wide variety of marine vertebrates show such behavioral plasticity in diving. For example, Galapagos fur seals have been shown to vary their dive depth in association with the lunar cycle, diving deeper on a full moon and vice versa, presumably because their prey within the deep-scattering layer are found deeper in the water column on brighter nights (Horning and Trillmich 1999). Similarly long-term tracking of basking sharks has shown a switch from deeper diving during the night to deeper diving during the day in different parts of this species range in association with differing behaviors (normal DVM vs. reverse DVM) of the prey (Sims et al. 2005). Taken together in combination with our findings, these results suggest that behavioral plasticity in diving behavior in response to local prey behavior is probably a common feature of marine vertebrates, being found in marine mammals, fish, reptiles, and most probably other groups such as marine birds as well.

Associations with mesoscale oceanographic features

Plankton are patchily distributed in the world's oceans, although certain factors may combine to lead to elevated levels of productivity at mesoscales (tens of kilometers), including the presence of oceanographic features such as rings, eddies, and fronts (Lévy et al. 1999, Lima et al. 2002). These features are essentially static relative to the normal swimming speeds of leatherback turtles in the North Atlantic. The speed and direction of travel for any marine animals will be a consequence of the swimming speed and direction of the individual as well as the currents, i.e., it is possible that in a strong current an animal might not be swimming but will still be advected horizontally (e.g., Luschi et al. 2003). Oceanographic conditions will vary in different ocean basins and sometimes mesoscale features may move fast or be ephemeral. However, the relatively static nature of mesoscale features in the North Atlantic suggests that any leatherbacks targeting these features for foraging would show a clear signal of reduced travel speed. It has previously been reported that marine vertebrates, including turtles, may slow down and forage in association with mesoscale features, presumably because of elevated abundance of food at such sites. However the intuitive appeal of these associations may mask a more complicated picture. First, plankton biomass and productivity are not universally elevated in association with oceanographic features (Graham et al. 2001). Second, marine vertebrates have specific diets, and so it is presumably the abundance of key prey species that is most important to foraging success rather than simply elevated levels of overall plankton productivity.

Initial studies have suggested that leatherbacks target their foraging on the edges of warm eddies (Ferraroli et al. 2004). While this behavior certainly does occur on occasion, our overall results suggest a different picture of leatherback movements with the underlying pattern being that many individuals spend the majority of their time moving continuously around the Atlantic with only a proportion of individuals remaining in hotspots for extended periods. However, two of the nine turtles did show prolonged residence in one area, suggesting that sometimes turtles did not simply travel more or less continuously. Overall the movement pattern shown by an individual is probably driven by whether an abundant and long-term prey field is encountered or not. In the context of our results it should be noted that fundamental to the ecology of leatherback turtles (and indeed other species of marine turtle) is the fact females do not breed every year. Instead a nesting season is generally followed by an interval of several years before the next nesting season, with this “remigration interval” typically being 2–4 years (McDonald and Dutton 1996). In these “sabbatical” years away from the breeding grounds, leatherbacks might have a different pattern of movement and foraging success.

Hotspots where turtles remained for extended periods often had no discernable sea surface signature that would indicate a mesoscale feature. This pattern contrasts, for example, with selective foraging of albatrosses, loggerhead turtles, bluefin tuna, and basking sharks at frontal features (Sims and Quayle 1998, Polovina et al. 2000, Nel et al. 2001, Royer et al. 2004). Clearly the importance of mesoscale features varies across species, presumably because of some combination of their search abilities (e.g., speed of travel and sensory perception) as well as the spatial distribution of their prey. Further, while general associations between zooplankton and certain mesoscale oceanographic features have been noted, little is known about the factors driving the abundance and distribution of specific gelatinous zooplankton, primarily because of the problems of sampling these delicate organisms (Graham et al. 2001).

Conclusions

In summary we suggest that simple rules might be driving the movement of leatherbacks. Within a northerly and southerly range limit, individuals appear to have broad regional fidelity. They travel in fairly straight lines, continuously foraging as they travel, but taking advantage of patches of high prey abundance that they opportunistically encounter. Sometimes, but not always, these prey hotspots are reflected by mesoscale oceanographic features detected in remote sensed imagery. Dive depth is shaped by the prey distribution, and so diving behavior changes (e.g., depth and diel periodicity) as turtles travel. Prey patches are exploited, presumably until the benefit from staying in the patch drops below some threshold level. However, our results suggest that encounters with patches of high prey abundance, sufficient to make the turtle slow down and exploit the patch, are relatively rare, at least in their first year after nesting. Given the pressing concerns for the conservation status of the leatherback turtles, there is an urgent need for measures to be introduced to mitigate mortality in fisheries. Our results reiterate the wide-ranging movements of leatherbacks and their generally epipelagic diving, which corresponds with the wide-ranging deployment of epipelagic long-lines hooks throughout the Atlantic (Lewison et al. 2004). Importantly we show that while turtles occasionally slow down and show residence in specific areas, simply protecting turtles at these times from fishing induced mortality will be insufficient, because turtles spend long periods traveling between hotspots. Rather we suggest that the key to reducing bycatch is the modification of fishing gear across ocean basins (e.g., by changing hook types; Watson et al. 2005), so that turtles are not caught so often.

A description of turtle tracking and diving behavior (Ecological Archives E087-160-A1).

A figure showing the variation in diel dive index at different latitudes for nine turtles (Ecological Archives E087-160-A2).

A figure showing the total proportion of time spent diving to >10 m in each hour and the mean dive depth for three latitudinal bands (Ecological Archives E087-160-A3).

A figure showing the difference in diel diving behavior by turtle A during different sections of the track (Ecological Archives E087-160-A4).

A figure showing the daily speed of travel, mean duration of dives, the latitude, and the mean depth of dives for turtle C (Ecological Archives E087-160-A5).

A figure showing the daily speed of travel, mean duration of dives, the latitude, and the mean depth of dives for turtle I (Ecological Archives E087-160-A6).

A figure showing the track of turtle B, situated off the northeast coast of Brazil, overlaid onto images of sea surface temperature and chlorophyll concentration (Ecological Archives E087-160-A7).

A figure showing frequency distributions of the daily speed of travel for each turtle (Ecological Archives E087-160-A8).