Defining dive bouts using a sequential differences analysis

Bout analysis searches for a bout-ending criterion (BEC) to determine whether successive events are part of the same bout. Methods widely used for finding the BEC are log-survivorship, log-frequency, and log-normal analyses. These analyses are based on the assumption that frequency distributions of event intervals can be described by two or three random distributions, and that the mean interval within a bout is common to all other bouts. Diving typically occurs in bouts. Since a dive bout is a sequence of complex behaviours in which the duration, depth, and interval between dives may all be adapted for optimal foraging, it is unreasonable to assume that the mean dive interval within a bout is common to all other dive bouts. Furthermore, one should not assume that dives might be split into bouts based only on dive interval without considering other characteristics, such as dive depth. Here we propose a new method, the sequential differences analysis, to find the BEC for dive bout analysis. This method has two features: (1) the frequency of differences in dive characteristics between two successive dives is used instead of the frequency of dive intervals, and (2) along with the dive interval, other characteristics are used to determine the BEC. Compared with the log-frequency analysis using dive intervals, the sequential differences analysis results in bouts with less variation (i.e. a smaller coefficient of variation) in dive characteristics, and a smaller number of dives within a bout. This suggests that our method splits dive sequences into bouts at a finer scale than the existing method. The sequential differences analysis is useful for dividing a sequence of complex behaviours with several characteristics into more meaningful bouts.