Massive data about European shags
Using cluster analysis to extract behavioral patterns from massive amounts of accelerometer measurements finally brings big data to humble ethology.
An ethogram is a catalogue of discrete behaviors typically employed by a species. Traditionally animal behavior has been recorded by observing study individuals directly. However, this approach is difficult, often impossible, in the case of behaviors which occur in remote areas and/or at great depth or altitude. The recent development of increasingly sophisticated, animal-borne data loggers, has started to overcome this problem.
The typical behaviors extracted were characterized by the periodicities of body acceleration. Each categorized behavior was assumed to correspond to when the bird was on land, in flight, on the sea surface, diving and so on. The behaviors classified by the procedures accorded well with those independently defined from depth profiles. Because our approach is performed by unsupervised computation of the data, it has the potential to detect previously unknown types of behavior and unknown sequences of some behaviors.
I think this approach could work even for animals that are easily accessible. Activity levels could be recorded with accelerometers while traditional observation could be used to more broadly classify the current behavior (is the animal grooming or eating?, running away from or towards the fight?) This might also help marshall evidence about species-specific behavioral repertoires.
Sakamoto et al. Can ethograms be automatically generated using body acceleration data from free-ranging birds?PLoS One 4(4): e5379. doi:10.1371/journal.pone.0005379
