Tracking of marine animals has increased exponentially in the past decade, and the resulting data could lead to an in-depth understanding of the causes and consequences of movement in the ocean. However, most common marine tracking systems are associated with large measurement errors. Accounting for these errors requires the use of hierarchical models, which are often difficult to fit to data. Using 3 case studies, we demonstrate that Template Model Builder (TMB), a new R package, is an accurate, efficient and flexible framework for modelling movement data. First, to demonstrate that TMB is as accurate but 30 times faster than bsam, a popular R package used to apply state-space models to Argos data, we modelled polar bear Ursus maritimus Argos data and compared the locations estimated by the models to GPS locations of these same bears. Second, to demonstrate how TMB's gain in efficiency and frequentist framework facilitate model comparison, we developed models with different error structures and compared them to find the most effective model for light-based geolocations of rhinoceros auklets Cerorhinca monocerata. Finally, to maximize efficiency through TMB's use of the Laplace approximation of the marginal likelihood, we modelled behavioural changes with continuous rather than discrete states. This new model directly accounts for the irregular sampling intervals characteristic of Fastloc-GPS data of grey seals Halichoerus grypus. Using real and simulated data, we show that TMB is a fast and powerful tool for modelling marine movement data. We discuss how TMB's potential reaches beyond marine movement studies.

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We tested the hypothesis that segregation in wintering areas is associated with population differentiation in a sentinel North Pacific seabird, the rhinoceros auklet (Cerorhinca monocerata). We collected tissue samples for genetic analyses on five breeding colonies in the western Pacific Ocean (Japan) and on 13 colonies in the eastern Pacific Ocean (California to Alaska), and deployed light-level geolocator tags on 12 eastern Pacific colonies to delineate wintering areas. Geolocator tags were deployed previously on one colony in Japan. There was strong genetic differentiation between populations in the eastern vs. western Pacific Ocean, likely due to two factors. First, glaciation over the North Pacific in the late Pleistocene might have forced a southward range shift that historically isolated the eastern and western populations. And second, deep-ocean habitat along the northern continental shelf appears to act as a barrier to movement; abundant on both sides of the North Pacific, the rhinoceros auklet is virtually absent as a breeder in the Aleutian Islands and Bering Sea, and no tagged birds crossed the North Pacific in the non-breeding season. While genetic differentiation was strongest between the eastern vs. western Pacific, there was also extensive differentiation within both regional groups. In pairwise comparisons among the eastern Pacific colonies, the standardized measure of genetic differentiation (FꞌST) was negatively correlated with the extent of spatial overlap in wintering areas. That result supports the hypothesis that segregation in the non-breeding season is linked to genetic structure. Philopatry and a neritic foraging habit probably also contribute to the structuring. Widely distributed, vulnerable to anthropogenic stressors, and exhibiting extensive genetic structure, the rhinoceros auklet is fully indicative of the scope of the conservation challenges posed by seabirds.

Opportunist gulls use anthropogenic food subsidies, which can bolster populations, but negatively influence sensitive local ecosystems and areas of human settlement. In the eastern Gulf of Maine, Canada, breeding herring gulls Larus argentatus have access to resources from aquaculture, fisheries and mink farms, but the relative influence of industry on local gull populations is unknown. Our objectives were to 1) assess use of natural and anthropogenic habitats by herring gulls from multiple colonies, 2) evaluate variation among colonies in use of distinct resource types within these habitats and 3) highlight areas of high gull:industry interaction. Using GPS devices on 39 gulls from four colonies, we identified visitation behaviour (slow, localized movements) and assigned visits to nine resource types. To evaluate the spatial distribution of visits, we created a use intensity index, reflecting both fidelity (i.e. repeated visits) and time spent in specific areas. All four anthropogenic resource types were heavily used (56 ± 11% of visiting time across colonies), notably, fish plants and mink farms. Despite large distances among three colonies, birds overlapped at particular distant, inland mink farms. In contrast, birds from close colonies overlapped in visitation to specific nearby resources (e.g. fish plants and human settlement), and otherwise diverged in distribution and use of offshore and coastal areas. Birds from three colonies also made frequent, long visits to uninhabited islands. Industry is clearly influencing the behaviour of breeding gulls in the eastern Gulf of Maine, Canada, where birds are travelling great distances or spending large proportions of time interacting with anthropogenic resources, while otherwise paying lengthy visits to nearby coastal islands. Studies have shown that concentrations of gulls can have harmful direct and indirect ecological and societal impacts. Our findings have implications for the management and regulation of industry to mitigate detrimental effects on local ecosystems and humans.