Movement and vocal behavior of free-ranging Norwegian killer whales (Orcinus orca)

Thesis (Ph. D.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Biology; and the Woods Hole Oceanographic Institution), 2008.Includes bibliographical references.Studying the social and cultural transmission of behavior among animals helps to identify patterns of interaction and information content flowing between individuals. Killer whales are likely to acquire traits culturally based on their population-specific feeding behaviors and group-distinctive vocal repertoires. I used digital tags to explore the contributions of individual Norwegian killer whales to group carousel feeding and the relationships between vocal and non-vocal activity. Periods of tail slapping to incapacitate herring during feeding were characterized by elevated movement variability, heightened vocal activity and call types containing additional orientation cues. Tail slaps produced by tagged animals were identified using a rapid pitch change and occurred primarily within 20m of the surface. Two simultaneously tagged animals maneuvered similarly when tail slapping within 60s of one another, indicating that the position and composition of the herring ball influenced their behavior. Two types of behavioral sequence preceding the tight circling of carousel feeding were apparent. First, the animals engaged in periods of directional swimming. They were silent in 2 of 3 instances, suggesting they may have located other foraging groups by eavesdropping. Second, tagged animals made broad horizontal loops as they dove in a manner consistent with corralling. All 4 of these occasions were accompanied by vocal activity, indicating that this and tail slapping may benefit from social communication. No significant relationship between the call types and the actual movement measurements was found. Killer whale vocalizations traditionally have been classified into discrete call types. Using human speech processing techniques, I considered that calls are alternatively comprised of shared segments that can be recombined to form the stereotyped and variable repertoire.(cont.) In a classification experiment, the characterization of calls using the whole call, a set of unshared segments, or a set of shared segments yielded equivalent performance. The shared segments required less information to parse the same vocalizations, suggesting a more parsimonious system of representation. This closer examination of the movements and vocalizations of Norwegian killer whales, combined with future work on ontogeny and transmission, will inform our understanding of whether and how culture plays a role in achieving population-specific behaviors in this species.by Ari Daniel Shapiro.Ph.D

The diving behaviour of mammal-eating killer whales (Orcinus orca): variations with ecological not physiological factors

Mammal-eating killer whales (Orcinus orca (L., 1758)) are a rare example of social predators that hunt together in groups of sexually dimorphic adults and juveniles with diverse physiological diving capacities. Day–night ecological differences should also affect diving as their prey show diel variation in activity and mammal-eating killer whales do not rely on echolocation for prey detection. Our objective was to explore the extent to which physiological aerobic capacities versus ecological factors shape the diving behaviour of this breath-hold diver. We used suction-cup-attached depth recorders (Dtags) to record 7608 dives of 11 animals in southeast Alaska. Analysis of dive sequences revealed a strong bout structure in both dive depth and duration. Day–night comparisons revealed reduced rates of deep dives, longer shallow dives, and shallower long-duration dives at night. In contrast, dive variables did not differ by age–sex class. Estimates of the aerobic dive limit (cADL) suggest that juveniles exceeded their cADL during as much as 15% of long dives, whereas adult males and females never exceeded their cADL. Mammal-eating killer whales in this area appear to employ a strategy of physiological compromise, with smaller group members diving nearer their physiological limits and large-bodied males scaling down their physiological performance

Comparing call-based versus subunit-based methods for categorizing Norwegian killer whale, Orcinus orca, vocalizations

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Animal Behaviour 81 (2011): 377-386, doi:10.1016/j.anbehav.2010.09.020.Students of animal communication face significant challenges when deciding how to categorise calls into subunits, calls, and call series. Here, we use algorithms designed to parse human speech to test different approaches for categorising calls of killer whales. Killer whale vocalisations have traditionally been categorised by humans into discrete call types. These calls often contain internal spectral shifts, periods of silence, and synchronously produced low and high frequency components, suggesting that they may be composed of subunits. We describe and compare three different approaches for modelling Norwegian killer whale calls. The first method considered the whole call as the basic unit of analysis. Inspired by human speech processing techniques, the second and third methods represented the calls in terms of subunits. Subunits may provide a more parsimonious approach to modelling the vocal stream since (1) there were fewer subunits than call types; (2) nearly 75% of all call types shared at least one subunit. We show that contour traces from stereotyped Norwegian killer whale calls yielded similar automatic classification performance using either whole calls or subunits. We also demonstrate that subunits derived from Norwegian stereotyped calls were detected in some Norwegian variable (non-stereotyped) calls as well as the stereotyped calls of other killer whale populations. Further work is required to test whether killer whales use subunits to generate and categorize their vocal repertoire.The undergraduate students were supported by the Massachusetts Institute of Technology Undergraduate Research Opportunities Program office and the Ocean Life Institute (OLI) at the Woods Hole Oceanographic Institution (WHOI). Field work was financed by the OLI, National Geographic Society and WWF Sweden. A. D. Shapiro was funded by a National Defense Science and Engineering Graduate Fellowship and the WHOI Academic Programs Office

doi:10.1098/rspb.2006.0005

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. Keywords: accelerometer; power spectral density; dive; free-ranging; scaling; optimal INTRODUCTION In a Friday Evening Discourse given at the Royal Institution in 1949 Direct observations have often been used to record movements of flying animals MATERIAL AND METHODS We compared the stroke frequencies and swimming speeds of a range of animals in relation to their body sizes. Owing to morphological differences among species, body mass was used as an index of body size. Morphological measurements were used to estimate mass for adult Weddell seals , leatherback turtles and sperm whales Field experiments using accelerometers were conducted from tropical to Antarctic regions. Detailed protocols of the field experiments were already published for the sperm whale (French Guiana, South America, May 2001. Study protocols followed those of the above-mentioned published studies. We used acceleration data loggers (D2GT and PD2GT, Little Leonardo Ltd, Tokyo; Dtag, the Woods Hole Oceanographic Institution; We could detect the duration of each stroke cycle from the time-series data, but our goal was to determine the dominant stroke cycle frequency for each animal. The periodic properties of the acceleration signal allowed us to apply a Fourier Transform to determine the dominant frequency. Power spectral density (PSD) was calculated from the entire acceleration dataset of each animal, or a subsample during identified foraging or migration behaviour to determine the dominant stroke cycle frequency using a Fast Fourier Transformation with a computer program package, IGOR PRO (WaveMetric, Inc., Lake Oswego, OR, USA). For the sperm whale, the bottom phase of the dive was not used as it is typified by body rotations, which can occur at similar rates to the fluking action. Stroke frequency and body size of animals K. Sato et al. 473 Proc. R. Soc. B (2007) 3. RESULTS Seals move their rear flippers side-to-side and these movements are detected as fluctuations in lateral acceleration along the transverse axis of the body (Mirounga angustirostris; with R 2 Z0.99 (nZ17, p!0.0001). The 95% confidence interval for the exponent was from K0.28 to K0.30. In contrast, the mean propulsive swim speed (U ) among these species was independent of body mass in the log-log analysis (UZ1.88 m K0.05 , R 2 Z0.18, nZ17, pZ0.09). Sperm whales of more than 30 tons, 300 kg seals and 0.5 kg seabirds all swam at mean swim speeds around 1-2 m s K1 during transit between the sea surface and the foraging depths (table 1). DISCUSSION According to experimental measurements based on respirometers in water tunnels and the doubly labelled water technique, the optimum swim speed was proportional to mass 0.27 Stroke frequency and body size of animals K. Sato et al. 475 Proc. R. Soc. B K1 ). Why these free-ranging animals did not follow the theoretical and experimental predictions for optimal swimming speed is a question we cannot answer now. The constructal model The isometric model proposed by According to the present study, swim speed (U ) was independent of body size, therefore the frequency is expected to be proportional to area divided by mass (S/m), which is expected to be proportional to the length K1 or mass K1/3 . Results of the present study were obtained from morphologically diverse animals. Nonetheless, f is inversely proportional to m K0.29 , close to the predicted value of mass K1/3 , implying that diving specialists among seabirds and marine mammals have evolved similar proportions of propulsive muscles and muscle contraction rates during cruising travel. The scaling relationship was very strong among swimming specialists during contexts when they were predicted to swim efficiently. Moreover, interesting deviations from the regression line (see Japanese flounders Paralichthys olivaceus had lower stroke frequencies than other swimming specialists (open pink circle i

Episode 1: Overview of C-IMAGE

C-IMAGE PI Dr. Steven Murawski talks to David Levin about the research goals of our center and the importance of integration when tackling large scale impacts

Episode 1: Overview of C-IMAGE

C-IMAGE PI Dr. Steven Murawski talks to David Levin about the research goals of our center and the importance of integration when tackling large scale impacts

Stroke frequency, but not swimming speed, is related to body size in free-ranging seabirds, pinnipeds and cetaceans

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 0.5kg seabirds to 30000kg sperm whales using animal-borne accelerometers. Dominant stroke cycle frequencies of swimming specialist seabirds and marine mammals were proportional to mass−0.29 (R2=0.99, n=17 groups), while propulsive swimming speeds of 1–2ms−1 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