Search for: All records

Knowledge of how animals respond to weather and changes in their physical environment is increasingly important given the higher frequency of extreme weather recorded in recent years and its forecasted increase globally 1,2. Even species considered to be highly adapted to extremes of weather, as albatrosses are to strong winds 3–5, may be disadvantaged by shifts in those extremes. Tracked albatrosses were shown recently to avoid storms and the strongest associated winds 6. The drivers of this response are so far unknown, though we hypothesise that turbulent storm conditions restrict foraging success, possibly by reducing the detectability or accessibility of food, and albatrosses divert towards more profitable conditions where possible. We tested the impact of physical environment - wind speed, rainfall, water clarity, and time of day - on feeding activity and success of two species of albatrosses with contrasting foraging strategies. We tracked 33 wandering and 48 black-browed albatrosses from Bird Island (South Georgia) with GPS and immersion loggers, and 19 and 7 individuals respectively with stomach-temperature loggers to record ingestions, providing an in-depth picture of foraging behaviour. Reduced foraging profitability (probability of prey capture and overall mass) was associated with stormy conditions, specifically strong winds and heavy rain in surface-seizing wandering albatrosses, and probability of prey capture was reduced in strong winds in black-browed albatrosses. We show that even highly wind-adapted species may frequently encounter conditions that make foraging difficult, giving context to storm avoidance in albatrosses. 

ABSTRACT Estimates of movement costs are essential for understanding energetic and life-history trade-offs. Although overall dynamic body acceleration (ODBA) derived from accelerometer data is widely used as a proxy for energy expenditure (EE) in free-ranging animals, its utility has not been tested in species that predominately use body rotations or exploit environmental energy for movement. We tested a suite of sensor-derived movement metrics as proxies for EE in two species of albatrosses, which routinely use dynamic soaring to extract energy from the wind to reduce movement costs. Birds were fitted with a combined heart-rate, accelerometer, magnetometer and GPS logger, and relationships between movement metrics and heart rate-derived V̇O2, an indirect measure of EE, were analyzed during different flight and activity modes. When birds were exclusively soaring, a metric derived from angular velocity on the yaw axis provided a useful proxy of EE. Thus, body rotations involved in dynamic soaring have clear energetic costs, albeit considerably lower than those of the muscle contractions required for flapping flight. We found that ODBA was not a useful proxy for EE in albatrosses when birds were exclusively soaring. As albatrosses spend much of their foraging trips soaring, ODBA alone was a poor predictor of EE in albatrosses. Despite the lower percentage of time flapping, the number of flaps was a useful metric when comparing EE across foraging trips. Our findings highlight that alternative metrics, beyond ODBA, may be required to estimate energy expenditure from inertial sensors in animals whose movements involve extensive body rotations. 

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. 

Southern Ocean ecosystems are globally important. Processes in the Antarctic atmosphere, cryosphere, and the Southern Ocean directly influence global atmospheric and oceanic systems. Southern Ocean biogeochemistry has also been shown to have global importance. In contrast, ocean ecological processes are often seen as largely separate from the rest of the global system. In this paper, we consider the degree of ecological connectivity at different trophic levels, linking Southern Ocean ecosystems with the global ocean, and their importance not only for the regional ecosystem but also the wider Earth system. We also consider the human system connections, including the role of Southern Ocean ecosystems in supporting society, culture, and economy in many nations, influencing public and political views and hence policy. Rather than Southern Ocean ecosystems being defined by barriers at particular oceanic fronts, ecological changes are gradual due to cross-front exchanges involving oceanographic processes and organism movement. Millions of seabirds and hundreds of thousands of cetaceans move north out of polar waters in the austral autumn interacting in food webs across the Southern Hemisphere, and a few species cross the equator. A number of species migrate into the east and west ocean-basin boundary current and continental shelf regions of the major southern continents. Human travel in and out of the Southern Ocean region includes fisheries, tourism, and scientific vessels in all ocean sectors. These operations arise from many nations, particularly in the Northern Hemisphere, and are important in local communities as well as national economic, scientific, and political activities. As a result of the extensive connectivity, future changes in Southern Ocean ecosystems will have consequences throughout the Earth system, affecting ecosystem services with socio-economic impacts throughout the world. The high level of connectivity also means that changes and policy decisions in marine ecosystems outside the Southern Ocean have consequences for ecosystems south of the Antarctic Polar Front. Knowledge of Southern Ocean ecosystems and their global connectivity is critical for interpreting current change, projecting future change impacts, and identifying integrated strategies for conserving and managing both the Southern Ocean and the broader Earth system.