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Abstract Background Inertial measurement units (IMUs) with high-resolution sensors such as accelerometers are now used extensively to study fine-scale behavior in a wide range of marine and terrestrial animals. Robust and practical methods are required for the computationally-demanding analysis of the resulting large datasets, particularly for automating classification routines that construct behavioral time series and time-activity budgets. Magnetometers are used increasingly to study behavior, but it is not clear how these sensors contribute to the accuracy of behavioral classification methods. Development of effective  classification methodology is key to understanding energetic and life-history implications of foraging and other behaviors. Methods We deployed accelerometers and magnetometers on four species of free-ranging albatrosses and evaluated the ability of unsupervised hidden Markov models (HMMs) to identify three major modalities in their behavior: ‘flapping flight’, ‘soaring flight’, and ‘on-water’. The relative contribution of each sensor to classification accuracy was measured by comparing HMM-inferred states with expert classifications identified from stereotypic patterns observed in sensor data. Results HMMs provided a flexible and easily interpretable means of classifying behavior from sensor data. Model accuracy was high overall (92%), but varied across behavioral states (87.6, 93.1 and 91.7% for ‘flapping flight’, ‘soaring flight’ and ‘on-water’, respectively). Models built on accelerometer data alone were as accurate as those that also included magnetometer data; however, the latter were useful for investigating slow and periodic behaviors such as dynamic soaring at a fine scale. Conclusions The use of IMUs in behavioral studies produces large data sets, necessitating the development of computationally-efficient methods to automate behavioral classification in order to synthesize and interpret underlying patterns. HMMs provide an accessible and robust framework for analyzing complex IMU datasets and comparing behavioral variation among taxa across habitats, time and space. 

Little is known about the effects of large-scale breeding range expansions on the ecology of top marine predators. We examined the effects of a recent range expansion on the breeding and foraging ecology of Laysan albatrosses ( Phoebastria immutabilis ). Laysan albatrosses expanded from historical breeding colonies in the Central Pacific Ocean to the Eastern Pacific Ocean around central Baja California, Mexico, leading to a 4,000-km shift from colonies located adjacent to the productive transition zone in the Central Pacific to colonies embedded within the eastern boundary current upwelling system of the Eastern Pacific California Current. We use electronic tagging and remote sensing data to examine the consequences of this range expansion on at-sea distribution, habitat use, foraging habitat characteristics, and foraging behavior at sea by comparing birds from historic and nascent colonies. We found the expansion resulted in distinct at-sea segregation and differential access to novel oceanographic habitats. Birds from the new Eastern Pacific colony on Guadalupe Island, Mexico have reduced ranges, foraging trip lengths and durations, and spend more time on the water compared to birds breeding in the Central Pacific on Tern Island, United States. Impacts of the range expansion to the post-breeding season were less pronounced where birds maintained some at-sea segregation but utilized similar habitat and environmental variables. These differences have likely benefited the Eastern Pacific colony which has significantly greater reproductive output and population growth rates. Laysan albatrosses have the plasticity to adapt to distinctly different oceanographic habitats and also provide insight on the potential consequences of range shifts to marine organisms.