Identifying the foraging habitat of marine predators is vital to understanding the ecology of these species and for their management and conservation. Foraging habitat for many marine predators is dynamic, and this poses a serious challenge for understanding how oceanographic features may shape the ecology of these animals. To help resolve this issue, we present a switching state-space model (SSSM) for discerning different movement behaviours hidden within error-prone satellite telemetry data. Along with modelling the movement dynamics, the SSSM estimates the probability that an animal is in a particular discrete behavioural mode, such as transiting or foraging. Using Argos satellite telemetry for leatherback sea turtles, we show that the SSSM readily identifies distinct classes of movement behaviour from the noisy data. Moreover, patterns in simultaneously collected diving data, to which the model is blind, match well with behavioural mode estimates. By combining behavioural mode estimates from the model with the diving data, we show that while transiting, leatherbacks make longer, deeper dives; and while foraging, they encounter cooler waters that range from 13 to 22°C. These differences are consistent among the turtles studied and within the same turtle in different years. This modelling approach can enhance standard kernel density estimators for identifying habitat use by incorporating behavioural information into the estimation procedure. Ultimately, we can build predictive models of habitat use by incorporating environmental data and diving behaviour directly into the SSSM framework.

Incidental capture in fisheries threatens many marine vertebrates, however, conservation cannot be effective without identifying major sources of mortality. For the critically endangered leatherback turtle (Dermochelys coriacea), a reliance on fisheries observer data and an absence of behavioural data sets corresponding to a large and diverse sample of animals have focused conservation efforts on a very limited part of the species marine habitat. Using the largest satellite telemetry data set for Atlantic leatherbacks, morphometrics from foraging animals and entanglement records, we show annual return migrations to key feeding areas by males, females and juveniles, and demonstrate the importance of northern latitudes to leatherbacks. We show that leatherbacks are vulnerable to entanglement in northern coastal and shelf waters, where turtle-fishery interactions represent a greater threat to this species than previously recognized. Unless conservation efforts expand to coastal and shelf areas, present efforts alone will not be sufficient to save the species.

Leatherback sea turtles, Dermochelys coriacea, undertake broad oceanic movements. While satellite telemetry has been used to investigate the post-nesting behaviour of female turtles tagged on tropical nesting beaches, long-term behavioural patterns of turtles of different sexes and sizes have not been described. Here we investigate behaviour for 25 subadult and adult male and female turtles satellite-tagged in temperate waters off Nova Scotia, Canada. Although sex and reproductive condition contributed to variation in migratory patterns, the migratory cycle of all turtles included movement between temperate and tropical waters. Marked changes in rates of travel, and diving and surfacing behaviour, accompanied southward movement away from northern foraging areas. As turtles approached higher latitudes the following spring and summer, they assumed behaviours consistent with regular foraging activity and eventually settled in coastal areas off Canada and the northeastern USA. Behavioural patterns corresponding to various phases of the migratory cycle were consistent across multiple animals and were repeated within individuals that completed return movements to northern waters. We consider the potential biological significance of these patterns, including how turtle behaviour relates to predator avoidance, thermoregulation and prey distribution.

Summary1. Biological and statistical complexity are features common to most ecological data that hinder our ability to extract meaningful patterns using conventional tools. Recent work on implementing modern statistical methods for analysis of such ecological data has focused primarily on population dynamics but other types of data, such as animal movement pathways obtained from satellite telemetry, can also benefit from the application of modern statistical tools. 2. We develop a robust hierarchical state-space approach for analysis of multiple satellite telemetry pathways obtained via the Argos system. State-space models are time-series methods that allow unobserved states and biological parameters to be estimated from data observed with error. We show that the approach can reveal important patterns in complex, noisy data where conventional methods cannot. 3. Using the largest Atlantic satellite telemetry data set for critically endangered leatherback turtles, we show that the diel pattern in travel rates of these turtles changes over different phases of their migratory cycle. While foraging in northern waters the turtles show similar travel rates during day and night, but on their southward migration to tropical waters travel rates are markedly faster during the day. These patterns are generally consistent with diving data, and may be related to changes in foraging behaviour. Interestingly, individuals that migrate southward to breed generally show higher daytime travel rates than individuals that migrate southward in a non-breeding year. 4. Our approach is extremely flexible and can be applied to many ecological analyses that use complex, sequential data.

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