Time series analysis of biologging data: autocorrelation reveals periodicity of diving behaviour in macaroni penguins
The nature of how behaviour at one time step influences the next is of great interest to behavioural ecologists, but rarely used for comparisons between animals. Time depth recorders (TDR) and other archival tags have been widely used to infer patterns of diving and foraging. However, while we can extract variables that describe individual dives, how runs of dives may indicate behaviours and how one dive influences the next are not fully understood. Treating TDR data as time series, we examined patterns of autocorrelation to investigate structure in the timing of behaviour. We fitted an oscillating best-fit curve to the autocorrelation and used the parameters of this curve to investigate differences in foraging strategy of 129 macaroni penguins, Eudyptes chrysolophus, of both sexes. We found interannual differences in autocorrelation parameters as well as differences between reproductive stages. In contrast to other studies of macaroni penguin diving based on depth analysis, we found no differences between the sexes. We mimicked changes in the various parameters by simulation of dive profiles, and used these to infer biological meaning from the parameters. As this technique makes very few assumptions about how to identify a dive or cluster of dives, we suggest that it is a useful first characterization of diving or cyclical behaviour in a wide range of animals.