Recent technological advances have permitted the collection of detailed animal location and ancillary biotelemetry data that facilitate inference about animal movement and associated behaviors. However, these rich sources of individual information, location, and biotelemetry data, are typically analyzed independently, with population‐level inferences remaining largely post hoc. We describe a hierarchical modeling approach, which is able to integrate location and ancillary biotelemetry (e.g., physiological or accelerometer) data from many individuals. We can thus obtain robust estimates of (1) population‐level movement parameters and (2) activity budgets for a set of behaviors among which animals transition as they respond to changes in their internal and external environment. Measurement error and missing data are easily accommodated using a state‐space formulation of the proposed hierarchical model. Using Bayesian analysis methods, we demonstrate our modeling approach with location and dive activity data from 17 harbor seals (Phoca vitulina) in the United Kingdom. Based jointly on movement and diving activity, we identified three distinct movement behavior states: resting, foraging, and transit, and estimated population‐level activity budgets to these three states. Because harbor seals are known to dive for both foraging and transit (but not usually for resting), we compared these results to a similar population‐level analysis utilizing only location data. We found that a large proportion of time steps were mischaracterized when behavior states were inferred from horizontal trajectory alone, with 33% of time steps exhibiting a majority of dive activity assigned to the resting state. Only 1% of these time steps were assigned to resting when inferred from both trajectory and dive activity data using our integrated modeling approach. There is mounting evidence of the potential perils of inferring animal behavior based on trajectory alone, but there fortunately now exist many flexible analytical techniques for extracting more out of the increasing wealth of information afforded by recent advances in biologging technology.

Summary: As part of global efforts to reduce dependence on carbon‐based energy sources there has been a rapid increase in the installation of renewable energy devices. The installation and operation of these devices can result in conflicts with wildlife. In the marine environment, mammals may avoid wind farms that are under construction or operating. Such avoidance may lead to more time spent travelling or displacement from key habitats. A paucity of data on at‐sea movements of marine mammals around wind farms limits our understanding of the nature of their potential impacts. Here, we present the results of a telemetry study on harbour sealsPhoca vitulinain The Wash, south‐east England, an area where wind farms are being constructed using impact pile driving. We investigated whether seals avoid wind farms during operation, construction in its entirety, or during piling activity. The study was carried out using historical telemetry data collected prior to any wind farm development and telemetry data collected in 2012 during the construction of one wind farm and the operation of another. Within an operational wind farm, there was a close‐to‐significant increase in seal usage compared to prior to wind farm development. However, the wind farm was at the edge of a large area of increased usage, so the presence of the wind farm was unlikely to be the cause. There was no significant displacement during construction as a whole. However, during piling, seal usage (abundance) was significantly reduced up to 25 km from the piling activity; within 25 km of the centre of the wind farm, there was a 19 to 83% (95% confidence intervals) decrease in usage compared to during breaks in piling, equating to a mean estimated displacement of 440 individuals. This amounts to significant displacement starting from predicted received levels of between 166 and 178 dB re 1 μPa_(p‐p). Displacement was limited to piling activity; within 2 h of cessation of pile driving, seals were distributed as per the non‐piling scenario. Synthesis and applications. Our spatial and temporal quantification of avoidance of wind farms by harbour seals is critical to reduce uncertainty and increase robustness in environmental impact assessments of future developments. Specifically, the results will allow policymakers to produce industry guidance on the likelihood of displacement of seals in response to pile driving; the relationship between sound levels and avoidance rates; and the duration of any avoidance, thus allowing far more accurate environmental assessments to be carried out during the consenting process. Further, our results can be used to inform mitigation strategies in terms of both the sound levels likely to cause displacement and what temporal patterns of piling would minimize the magnitude of the energetic impacts of displacement.

In the last thirty years, the emergence and progression of biologging technology has led to great advances in marine predator ecology. Large databases of location and dive observations from biologging devices have been compiled for an increasing number of diving predator species (such as pinnipeds, sea turtles, seabirds and cetaceans), enabling complex questions about animal activity budgets and habitat use to be addressed. Central to answering these questions is our ability to correctly identify and quantify the frequency of essential behaviours, such as foraging. Despite technological advances that have increased the quality and resolution of location and dive data, accurately interpreting behaviour from such data remains a challenge, and analytical methods are only beginning to unlock the full potential of existing datasets. This review evaluates both traditional and emerging methods and presents a starting platform of options for future studies of marine predator foraging ecology, particularly from location and two-dimensional (time-depth) dive data. We outline the different devices and data types available, discuss the limitations and advantages of commonly-used analytical techniques, and highlight key areas for future research. We focus our review on pinnipeds - one of the most studied taxa of marine predators - but offer insights that will be applicable to other air-breathing marine predator tracking studies. We highlight that traditionally-used methods for inferring foraging from location and dive data, such as first-passage time and dive shape analysis, have important caveats and limitations depending on the nature of the data and the research question. We suggest that more holistic statistical techniques, such as state-space models, which can synthesise multiple track, dive and environmental metrics whilst simultaneously accounting for measurement error, offer more robust alternatives. Finally, we identify a need for more research to elucidate the role of physical oceanography, device effects, study animal selection, and developmental stages in predator behaviour and data interpretation.

Investigation of marine mammal dive-by-dive blood distribution and oxygenation has been limited by a lack of noninvasive technology for use in freely diving animals. Here, we developed a noninvasive near-infrared spectroscopy (NIRS) device to measure relative changes in blood volume and haemoglobin oxygenation continuously in the blubber and brain of voluntarily diving harbour seals. Our results show that seals routinely exhibit preparatory peripheral vasoconstriction accompanied by increased cerebral blood volume approximately 15 s before submersion. These anticipatory adjustments confirm that blood redistribution in seals is under some degree of cognitive control that precedes the mammalian dive response. Seals also routinely increase cerebral oxygenation at a consistent time during each dive, despite a lack of access to ambient air. We suggest that this frequent and reproducible reoxygenation pattern, without access to ambient air, is underpinned by previously unrecognised changes in cerebral drainage. The ability to track blood volume and oxygenation in different tissues using NIRS will facilitate a more accurate understanding of physiological plasticity in diving animals in an increasingly disturbed and exploited environment.