D. Michael Scantlebury

TL;DR: Overall, DBA seems to be a substantive proxy for movement-based power but consideration of other movement-related metrics, such as the Static Body Acceleration and the rate of change of body pitch and roll, may enable researchers to refine movement- based metabolic costs, particularly in animals where movement is not characterized by marked changes in body acceleration.

TL;DR: Framework4 is an all-encompassing software suite which operates on smart sensor data to determine the 4 key elements considered pivotal for movement analysis from such tags; animal trajectory, behaviour, energy expenditure and quantification of the environment in which the animal moves.

TL;DR: The importance of behaviours which reduce locomotor costs when traversing new, energetically challenging environments, and demonstrate that these behaviours are utilised by pumas in the wild are illustrated.

TL;DR: Overall behaviour recognition using this new approach was better than most other methods due to its ability to deal with behavioural variation and the speed with which the task was completed because extraneous data are avoided in the process.

TL;DR: This work proposes that the intricacies of movement paths, and particularly turns, reflect decisions made by animals so that turn points are particularly relevant to behavioural ecologists, and introduces a fast, accurate algorithm for inferring turning‐points in high‐resolution data.