Abstract. 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 populationlevel 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.

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Investigation of activity budgets in relation to seasonal, intrinsic (age, sex) and extrinsic (time of day, spatial) covariates enables an understanding of how such covariates shape behavioural strategies. However, conducting such investigations in the wild is challenging, because of the required large sample size of individuals across the annual cycle, and difficulties in categorising behavioural states and analysing the resulting individual‐referenced and serially correlated data. In this study, from telemetry tags deployed on 63 grey seals Halichoerus grypus and 126 harbour seals Phoca vitulina we used behavioural data, and movement data within a Bayesian state–space model (SSM), to define population‐level activity budgets around Britain. Using generalised estimating equations (GEEs) we then examined how time spent in four states (resting on land (hauled out), resting at sea, foraging and travelling) was influenced by seasonal, intrinsic and extrinsic covariates. We present and discuss the following key findings. 1) We found no evidence that regional variation in foraging effort was linked to regional population trajectories in harbour seals. 2) Grey seals demonstrated sex‐specific seasonal differences in their activity budgets, independent from those related to reproductive costs. 3) In these sympatric species there was evidence of temporal separation in time hauled out, but not in time foraging. 4) In both species, time spent resting at sea was separated into inshore (associated with tidal haul out availability) and offshore areas. Time spent resting at sea and on land was interchangeable to some extent, suggesting a degree of overlap in their functionality. This may result in a relaxation of the constraints associated with a central place foraging strategy. More generally, we demonstrate how a large dataset, incorporating differing tag parameters, can be analysed to define activity budgets and subsequently address important ecological questions.

International audienceSpecies distribution maps can provide important information to focus conservation efforts and enable spatial management of human activities. Two sympatric marine predators, grey seals Halichoerus grypus and harbour seals Phoca vitulina, have overlapping ranges on land and at sea but contrasting population dynamics around Britain: whilst grey seals have generally increased, harbour seals have shown significant regional declines. We analysed 2 decades of at-sea movement data and terrestrial count data from these species to produce high resolution, broad-scale maps of distribution and associated uncertainty to inform conservation and management. Our results showed that grey seals use offshore areas connected to their haul-out sites by prominent corridors, and harbour seals primarily stay within 50 km of the coastline. Both species show fine-scale offshore spatial segregation off the east coast of Britain and broad-scale partitioning off western Scotland. These results illustrate that, for broad-scale marine spatial planning, the conservation needs of harbour seals (primarily inshore, the exception being selected offshore usage areas) are different from those of grey seals (up to 100 km offshore and corridors connecting these areas to haul-out sites). More generally, our results illustrate the importance of detailed knowledge of marine predator distributions to inform marine spatial planning; for instance, spatial prioritisation is not necessarily the most effective spatial planning strategy even when conserving species with similar taxonomy

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 seals Phoca vitulina in 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.

1. Grey seals (Halichoerus grypus) were the first mammals to be protected by an Act of Parliament in the UK and are currently protected under UK, Scottish, and EU conservation legislation. Reporting requirements under each of these statutes requires accurate and timely population estimates. Monitoring is principally conducted by aerial surveys of the breeding colonies; these are used to produce estimates of annual pup production. Translating these data to estimates of adult population size requires information about demographic parameters such as fecundity and sex ratio.2. An age-structured population dynamics model is presented, which includes density dependence in pup survival, with separate carrying capacities in each of the four breeding regions considered (North Sea, Inner Hebrides, Outer Hebrides, and Orkney). This model is embedded within a Bayesian state-space modelling framework, allowing the population model to be linked to available data and the use of informative prior distributions on demographic parameters. A computerintensive fitting algorithm is presented based on particle filtering methods. 3. The model is fitted to region-level pup production estimates from 1984 to 2010 and an independent estimate of adult population size, derived from aerial surveys of hauled-out seals in 2008. The fitted model is used to estimate total population size from 1984 to 2010. 4. The population in the North Sea region has increased at a near-constant rate; growth in the other three regions began to slow in the mid-1990s and these populations appear to have reached carrying capacity. The total population size of seals aged 1 year or older in 2010 was estimated to be 116 100 (95% CI 98 400-138 600), an increase of <1% on the previous year. 5. The modelling and fitting methods are widely applicable to other wildlife populations where diverse sources of information are available and inference is required for the underlying population dynamics.

Summary1. With ambitious renewable energy targets, pile driving associated with offshore wind farm construction will become widespread in the marine environment. Many proposed wind farms overlap with the distribution of seals, and sound from pile driving has the potential to cause auditory damage. 2. We report on a behavioural study during the construction of a wind farm using data from GPS/GSM tags on 24 harbour seals Phoca vitulina L. Pile driving data and acoustic propagation models, together with seal movement and dive data, allowed the prediction of auditory damage in each seal. 3. Growth and recovery functions for auditory damage were combined to predict temporary auditory threshold shifts in each seal. Further, M-weighted cumulative sound exposure levels [cSELs(M pw )] were calculated and compared to permanent auditory threshold shift exposure criteria for pinnipeds in water exposed to pulsed sounds. 4. The closest distance of each seal to pile driving varied from 4Á7 to 40Á5 km, and predicted maximum cSELs(M pw ) ranged from 170Á7 to 195Á3 dB re 1lPa 2 -s for individual seals. Comparison to exposure criteria suggests that half of the seals exceeded estimated permanent auditory damage thresholds. 5. Prediction of auditory damage in marine mammals is a rapidly evolving field and has a number of key uncertainties associated with it. These include how sound propagates in shallow water environments and the effects of pulsed sounds on seal hearing; as such, our predictions should be viewed in this context. 6. Policy implications. We predicted that half of the tagged seals received sound levels from pile driving that exceeded auditory damage thresholds for pinnipeds. These results have implications for offshore industry and will be important for policymakers developing guidance for pile driving. Developing engineering solutions to reduce sound levels at source or methods to deter animals from damage risk zones, or changing temporal patterns of piling could potentially reduce auditory damage risk. Future work should focus on validating these predictions by collecting auditory threshold information pre-and post-exposure to pile driving. Ultimately, information on population-level impacts of exposure to pile driving is required to ensure that offshore industry is developed in an environmentally sustainable manner.

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.Electronic supplementary materialThe online version of this article (doi:10.1186/s40462-016-0090-9) contains supplementary material, which is available to authorized users.