Chemical information is used in a variety of contexts including habitat recognition, foraging and predator avoidance, and a plethora of studies have shown that an individual's distinct chemical profile can mediate interactions with conspecifics. Interestingly, recent work has revealed that diet alone is sufficient to change the chemical profile of individuals, and with it, the way other individuals perceive and interact with them. Free amino acids are known to be utilised across species in a range of contexts, including during predator–prey and host–parasite interactions, and have been widely postulated to underpin diet‐mediated social interactions, especially in fish. However, so far no empirical evidence has been presented to support this suggestion. Using an established behavioural assay in three‐spined sticklebacks (Gasterosteus aculeatus), we aimed to assess association preferences in groups of fish fed experimental diets which differed by a single free amino acid. Our results demonstrate that free amino acids alone are sufficient to mediate interindividual association preferences, raising the possibility that such a mechanism may be widespread among aquatic animals.
Testing animals in groups can provide valuable data for investigating behavioural stress responses. However, conventional measures typically focus on the behaviour of individual animals or on dyadic interactions. Here, we aimed to determine metrics describing the behaviour of grouping animals that can reveal differences in stress responses. Using zebrafish (Danio rerio) as a model, we observed replicated shoals both immediately and 24 hours after exposure to a novel environment, as an assessment of temporal change in response to an acute stressor. We quantified various standard behavioural measures in combination with metrics describing group structure, including different proximity, social, and spatial metrics. Firstly, we showed a high collinearity between most of the analysed metrics, suggesting that they describe similar aspects of the group dynamics. After metric selection, we found that under acute stress shoals had significantly higher shoal densities, a lower variation in nearest neighbour distances and were in closer proximity to the walls compared to the same groups tested 24 hours later, indicating a reduction in acute stress over time. Thus, the use of group metrics could allow for the refinement of behavioural protocols carried out in a range of research areas, by providing sensitive and rich data in a more relevant social context.
Abstract-The automated analysis of interacting objects or people from video has many uses, including the recognition of activities, and identification of prototypical or unusual behaviors. Existing techniques generally use temporal sequences of quantifiable real-valued features, such as object position or orientation; however, more recently, qualitative representations have been proposed. In this paper we present a novel and robust qualitative method which can be used both for classification and clustering of pair-activities. We use Qualitative Trajectory Calculus (QT C) to represent the relative motion between two objects, and encodes their interactions as a trajectory of QT C states. A key element is a general and robust means of determining the sequence similarity, which we term Normalized Weighted Sequence Alignment; we show that this is an effective metric for both recognition and clustering problems. We have evaluated our method across three different datasets, and shown that it out-performs state of the art quantitative methods, achieving an error rate of no more than 4.1% for recognition, and cluster purities higher than 90%. Our motivation originates from an interest in automated analysis of animal behaviors, and we present a comprehensive video dataset of fish behaviors (Gasterosteus aculeatus), collected from lab-based experiments.
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