Yves Handrich

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 0.5 kg seabirds to 30 000 kg 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 1–2 m s−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.

Impact of Externally Attached Loggers on the Diving Behaviour of the King Penguin

The impact of relatively small externally attached time series recorders on some foraging parameters of seabirds was investigated during the austral summer of 1995 by monitoring the diving behaviour of 10 free‐ranging king penguins (Aptenodytes patagonicus) over one foraging trip. Time‐depth recorders were implanted in the abdominal cavities of the birds, and half of the animals also had dummy loggers attached on their backs. Although most of the diving behaviour was not significantly affected by the external loggers ( \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \usepackage[OT2,OT1]{fontenc} \newcommand\cyr{ \renewcommand\rmdefault{wncyr} \renewcommand\sfdefault{wncyss} \renewcommand\encodingdefault{OT2} \normalfont \selectfont} \DeclareTextFontCommand{\textcyr}{\cyr} \pagestyle{empty} \DeclareMathSizes{10}{9}{7}{6} \begin{document} \landscape

Feeding behaviour of free–ranging penguins determined by oesophageal temperature

P> 0.05

Is Penguin banding harmless

\end{document} ), the birds with externally attached loggers performed almost twice as many shallow dives, between 0 and 10 m depth, as the birds without external loggers. These shallow dives interrupted more frequently the deep‐diving sequences in the case of birds with external loggers (percentage of deep dives followed by deep dives: 46% for birds with implants only vs. 26% for birds with an external attachment). Finally, the distribution pattern of the postdive durations plotted against the hour of the day was more heterogeneous for the birds with an external package. In addition, these penguins had extended surfacing times between two deep dives compared to birds without external attachments ( \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \usepackage[OT2,OT1]{fontenc} \newcommand\cyr{ \renewcommand\rmdefault{wncyr} \renewcommand\sfdefault{wncyss} \renewcommand\encodingdefault{OT2} \normalfont \selectfont} \DeclareTextFontCommand{\textcyr}{\cyr} \pagestyle{empty} \DeclareMathSizes{10}{9}{7}{6} \begin{document} \landscape

A Nonlinear Filtering Approach for the Attitude and Dynamic Body Acceleration Estimation Based on Inertial and Magnetic Sensors: Bio-Logging Application

P< 0.0001

Measuring foraging activity in a deep-diving bird: comparing wiggles, oesophageal temperatures and beak-opening angles as proxies of feeding

\end{document} ). These results suggest the existence of an extra energy cost induced by externally attached loggers.