Abstract: Longitudinal behavioral data generally contains a significant amount of structure. In this work, we identify the structure inherent in daily behavior with models that can accurately analyze, predict, and cluster multimodal data from individuals and communities within the social network of a population. We represent this behavioral structure by the principal components of the complete behavioral dataset, a set of characteristic vectors we have termed eigenbehaviors. In our model, an individual’s behavior over a specific day can be approximated by a weighted sum of his or her primary eigenbehaviors. When these weights are calculated halfway through a day, they can be used to predict the day’s remaining behaviors with 79% accuracy for our test subjects. Additionally, we demonstrate the potential for this dimensionality reduction technique to infer community affiliations within the subjects’ social network by clustering individuals into a behavior space spanned by a set of their aggregate eigenbehaviors. These behavior spaces make it possible to determine the behavioral similarity between both individuals and groups, enabling 96% classification accuracy of community affiliations within the population-level social network. Additionally, the distance between individuals in the behavior space can be used as an estimate for relational ties such as friendship, suggesting strong behavioral homophily amongst the subjects. This approach capitalizes on the large amount of rich data previously captured during the Reality Mining study from mobile phones continuously logging location, proximate phones, and communication of 100 subjects at MIT over the course of 9 months. As wearable sensors continue to generate these types of rich, longitudinal datasets, dimensionality reduction techniques such as eigenbehaviors will play an increasingly important role in behavioral research.

Abstract: Mobbing signals advertise the location of a stalking predator to all prey in an area and recruit them into the inspection aggregation. Such behavior usually causes the predator to move to another area. However, mobbing calls could be eavesdropped by other predators. Because the predation cost of mobbing calls is poorly known, we investigated whether the vocalizations of the mobbing pied flycatcher, Ficedula hypoleuca, a small hole nesting passerine, increase the risk of nest predation. We used mobbing calls of pied flycatchers to examine if they could lure predators such as the marten, Martes martes. This predator usually hunts by night and may locate its mobbing prey while resting nearby during the day. Within each of 56 experimental plots, from the top of one nest-box we played back mobbing sounds of pied flycatchers, whereas blank tapes were played from the top of another nest-box. The trials with mobbing calls were carried out before sunset. We put pieces of recently abandoned nests of pied flycatchers and a quail, Coturnix coturnix, egg into each of the nest-boxes. Nest-boxes with playbacks of mobbing calls were depredated by martens significantly more than were nest-boxes with blank tapes. The results of the present study indicate that repeated conspicuous mobbing calls may carry a significant cost for birds during the breeding season.

Abstract: Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis.

Abstract: One of the most prominent behavioural features of many forest primates are the loud calls given by the adult males. Early observational studies repeatedly postulated that these calls function in intragroup spacing or intergroup avoidance. More recent field experiments with Diana monkeys (Cercopithecus diana) of Taï Forest, Ivory Coast, have clearly shown that loud male calls function as predator alarm calls because calls reliably (1) label different predator classes and (2) convey semantic information about the predator type present. Here, I test the alarm call hypothesis another primate, the Campbell's monkey (C. campbelli). Like Diana monkeys, male Campbell's monkeys produce conspicuous loud calls to crowned hawk eagles (Stephanoaetus coronatus) and leopards (Panthera pardus), two of their main predators. Playback experiments showed that monkeys responded to the predator category represented by the different playback stimuli, regardless of whether they consisted of (1) vocalisations of the actual predators (crowned hawk eagle shrieks or leopard growls), (2) alarm calls to crowned hawk eagles or leopards given by other male Campbell's monkeys or (3) alarm calls to crowned hawk eagles or leopards given by sympatric male Diana monkeys. These experiments provide further evidence that non-human primates have evolved the cognitive capacity to produce and respond to referential labels for external events.

Abstract: Position preferences of well-fed and food-deprived juvenile roach were investigated in schools of 2 and 4 fish in the laboratory. Food-deprived fish appeared significantly more often in the front position than their well-fed conspecifics. For fish at the same hunger level, individuals at the front of the school had the highest feeding rate. These results represent the first evidence for a relationship between the nutritional state of individual fish and their positions in a school and suggest a functional advantage of the preference.