No abstract

An ethogram is a catalogue of discrete behaviors typically employed by a species. Traditionally animal behavior has been recorded by observing study individuals directly. However, this approach is difficult, often impossible, in the case of behaviors which occur in remote areas and/or at great depth or altitude. The recent development of increasingly sophisticated, animal-borne data loggers, has started to overcome this problem. Accelerometers are particularly useful in this respect because they can record the dynamic motion of a body in e.g. flight, walking, or swimming. However, classifying behavior using body acceleration characteristics typically requires prior knowledge of the behavior of free-ranging animals. Here, we demonstrate an automated procedure to categorize behavior from body acceleration, together with the release of a user-friendly computer application, “Ethographer”. We evaluated its performance using longitudinal acceleration data collected from a foot-propelled diving seabird, the European shag, Phalacrocorax aristotelis. The time series data were converted into a spectrum by continuous wavelet transformation. Then, each second of the spectrum was categorized into one of 20 behavior groups by unsupervised cluster analysis, using k-means methods. The typical behaviors extracted were characterized by the periodicities of body acceleration. Each categorized behavior was assumed to correspond to when the bird was on land, in flight, on the sea surface, diving and so on. The behaviors classified by the procedures accorded well with those independently defined from depth profiles. Because our approach is performed by unsupervised computation of the data, it has the potential to detect previously unknown types of behavior and unknown sequences of some behaviors.

SUMMARYAquatic animals use a variety of strategies to reduce the energetic cost of locomotion. Efficient locomotion is particularly important for breath-holding divers because high levels of exercise may quickly deplete oxygen reserves,leading to the termination of a dive. We investigated the swimming behavior of eight adult Weddell seals, which are proficient divers, in McMurdo Sound,Antarctica. A newly developed data logger was attached to free-ranging females at their own breeding sites to record swimming speed, depth, two-dimensional accelerations (stroke frequency and body angle) and temperature. All seals conducted multiple deep dives (the mean dive depth range for each animal was 223.3±66.5–297.9±164.7 m). Prolonged gliding while descending was observed with thinner females (N=5 seals). But the fatter females (N=3 seals) exhibited only swim-and-glide swimming,characterized by intermittent stroking and fluctuating swim speed, throughout their descent and ascent. The body angles of four of the seals were restricted to less than 30° by the location of breathing holes in the ice and the slope of local bathymetric features. Of these four, the three fatter seals adopted the stroke-and-glide method while the other thinner seal descended with prolonged periods of gliding. Prolonged gliding seems to be a more efficient method for locomotion because the surface time between dives of gliding seals was significantly less than that of stroking animals, despite their same stroke frequencies.

It is obvious, at least qualitatively, that small animals move their locomotory apparatus faster than large animals: small insects move their wings invisibly fast, while large birds flap their wings slowly. However, quantitative observations have been difficult to obtain from free-ranging swimming animals. We surveyed the swimming behaviour of animals ranging from 0.5 kg seabirds to 30 000 kg sperm whales using animalborne accelerometers. Dominant stroke cycle frequencies of swimming specialist seabirds and marine mammals were proportional to mass K0.29 (R 2 Z0.99, nZ17 groups), while propulsive swimming speeds of 1-2 m s K1 were independent of body size. This scaling relationship, obtained from breath-hold divers expected to swim optimally to conserve oxygen, does not agree with recent theoretical predictions for optimal swimming. Seabirds that use their wings for both swimming and flying stroked at a lower frequency than other swimming specialists of the same size, suggesting a morphological trade-off with wing size and stroke frequency representing a compromise. In contrast, foot-propelled diving birds such as shags had similar stroke frequencies as other swimming specialists. These results suggest that muscle characteristics may constrain swimming during cruising travel, with convergence among diving specialists in the proportions and contraction rates of propulsive muscles.