A new direction for differentiating animal activity based on measuring angular velocity about the yaw axis

by Richard M. Gunner, Rory P. Wilson, Mark D. Holton, Rebecca Scott, Phil Hopkins, Carlos M. Duarte
Research article Year: 2020 ISSN: 2045-7758 DOI: 10.1002/ece3.6515


Gunner, R. M., Wilson, R. P., Holton, M. D., Scott, R., Hopkins, P., & Duarte, C. M. (2020). A new direction for differentiating animal activity based on measuring angular velocity about the yaw axis. Ecology and evolution10(14), 7872-7886.


  1. The use of animal-attached data loggers to quantify animal movement has increased in popularity and application in recent years. High-resolution tri-axial acceleration and magnetometry measurements have been fundamental in elucidating fine-scale animal movements, providing information on posture, traveling speed, energy expenditure, and associated behavioral patterns. Heading is a key variable obtained from the tandem use of magnetometers and accelerometers, although few field investigations have explored fine-scale changes in heading to elucidate differences in animal activity (beyond the notable exceptions of dead-reckoning).
  2. This paper provides an overview of the value and use of animal heading and a prime derivative, angular velocity about the yaw axis, as an important element for assessing activity extent with potential to allude to behaviors, using “free-ranging” Loggerhead turtles (Caretta caretta) as a model species.
  3. We also demonstrate the value of yaw rotation for assessing activity extent, which varies over the time scales considered and show that various scales of body rotation, particularly rate of change of yaw, can help resolve differences between fine-scale behavior-specific movements. For example, oscillating yaw movements about a central point of the body's arc implies bouts of foraging, while unusual circling behavior, indicative of conspecific interactions, could be identified from complete revolutions of the longitudinal axis.
  4. We believe this approach should help identification of behaviors and “space-state” approaches to enhance our interpretation of behavior-based movements, particularly in scenarios where acceleration metrics have limited value, such as for slow-moving animals.