Crossing latitudes--long-distance tracking of an apex predator

Abstract

Tiger sharks (Galeocerdo cuvier) are apex predators occurring in most tropical and warm temperate marine ecosystems, but we know relatively little of their patterns of residency and movement over large spatial and temporal scales. We deployed satellite tags on eleven tiger sharks off the north-western coast of Western Australia and used the Brownian Bridge kernel method to calculate home ranges and analyse movement behaviour. One individual recorded one of the largest geographical ranges of movement ever reported for the species, travelling over 4000 km during 517 days of monitoring. Tags on the remainder of the sharks reported for shorter periods (7-191 days). Most of these sharks had restricted movements and long-term (30-188 days) residency in coastal waters in the vicinity of the area where they were tagged. Core home range areas of sharks varied greatly from 1166.9 to 634,944 km2. Tiger sharks spent most of their time in water temperatures between 23°-26°C but experienced temperatures ranging from 6°C to 33°C. One shark displayed seasonal movements among three distinct home range cores spread along most of the coast of Western Australia and generalized linear models showed that this individual had different patterns of temperature and depth occupancy in each region of the coast, with the highest probability of residency occurring in the shallowest areas of the coast with water temperatures above 23°C. These results suggest that tiger sharks can migrate over very large distances and across latitudes ranging from tropical to the cool temperate waters. Such extensive long-term movements may be a key element influencing the connectivity of populations within and among ocean basins.

Fig 1. Movement patterns of tiger sharks in Western Australia.

Maps show location uplinks of 8 tiger sharks. Triangles indicate tagging location and grey polygons indicate Commonwealth Marine Reserves.

Fig 2. Home range of tiger sharks.

The utilisation distribution calculated using the Brownian Bridge kernel method. Black line represents the 50% Brownian Bridge home range distribution.

Fig 3. Time spent in each temperature bin.

Plots show the percentage of time spent within the specified temperature bins for each tiger shark (ID number in the top right hand corner of each plot).

Fig 4. Latitudinal variation of temperature profiles for Shark 5.

Percentage of time spent in each temperature bin at each region of Western Australia for Shark 5.

Fig 5. Time spent in each depth bin.

Percentage of time spent in each depth bin for two tiger sharks tagged with SPLASH tags.

Fig 6. Vertical profiles of water temperature.

Plots show temperature profiles recorded by Argo floats of the north (17.6°S 117.6°E) and south (35.78°S 119.5°E) sections of the WA coast. Vertical lines represent the minimum temperature reported by the shark’s satellite transmitter and horizontal lines represent the estimated diving depth.

Fig 7. Generalised linear model for Shark 5.

Generalised linear model (GLM) predicted probabilities (solid line) of a shark being in a 25% utilisation distribution in relation to (a) water depth, (b) water temperature in the north and (c) in the south. Dotted lines show the standard error.