Biology subjects

Strandburg-Peshkin, A.

Publications and source records attributed to Strandburg-Peshkin, A..

3 recordsLinked to original sources

bioRxiv2023

Accelerometer-based predictions of behaviour elucidate factors affecting the daily activity patterns of spotted hyenas

Animal activity patterns are highly variable and influenced by internal and external factors, including social processes. Quantifying activity patterns in natural settings can be challenging, as it is difficult to monitor animals over long time periods. Here, we developed and validated a machine-learning based classifier to identify behavioural states from accelerometer data of wild spotted hyenas (Crocuta crocuta), social carnivores that live in large fission-fusion societies. By combining this classifier with continuous collar-based accelerometer data from five hyenas, we generated a complete record of activity patterns over more than one month. We used these continuous behavioural sequences to investigate how past activity, individual idiosyncrasies, and social synchronisation influence hyena activity patterns. We found that hyenas exhibit characteristic crepuscular-nocturnal daily activity patterns. Time spent active was independent of activity level on previous days, suggesting that hyenas do not show activity compensation. We also found limited evidence for an effect of individual identity on activity, and showed that pairs of hyenas who spent more time together synchronised their activity patterns. This study sheds light on the patterns and drivers of activity in spotted hyena societies, and also provides a useful tool for quantifying behavioural sequences from accelerometer data.

animal behavior and cognition↗

bioRxiv2021

A practical guide for generating unsupervised, spectrogram-based latent space representations of animal vocalizations

The manual detection, analysis, and classification of animal vocalizations in acoustic recordings is laborious and requires expert knowledge. Hence, there is a need for objective, generalizable methods that detect underlying patterns in these data, categorize sounds into distinct groups, and quantify similarities between them. Among all computational methods that have been proposed to accomplish this, neighborhood-based dimensionality reduction of spectrograms to produce a latent-space representation of calls stands out for its conceptual simplicity and effectiveness. Using a dataset of manually annotated meerkat (Suricata suricatta) vocalizations, we demonstrate how this method can be used to obtain meaningful latent space representations that reflect the established taxonomy of call types. We analyze strengths and weaknesses of the proposed approach, give recommendations for its usage and show application examples, such as the classification of ambiguous calls and the detection of mislabeled calls. All analyses are accompanied by example code to help researchers realize the potential of this method for the study of animal vocalizations.

animal behavior and cognition↗

bioRxiv2021

Daily ranging and den usage patterns structure fission-fusion dynamics and social associations in spotted hyenas

Environment structure often shapes social interactions. Spatial attractors that draw multiple individuals may play a particularly important role in dispersed groups, where individuals must first encounter one another to interact. We use GPS data recorded simultaneously from five spotted hyenas (Crocuta crocuta) within a single clan to investigate how communal dens and daily ranging patterns shape fission-fusion dynamics (subgroup splits and merges). We introduce a species-general framework for identifying and characterizing dyadic fission-fusion events and describe a taxonomy of ten possible configurations of these events. Applying this framework to the hyena data illuminates the spatiotemporal structure of social interactions within hyenas daily routines. The most common types of fission-fusion events involve close approaches between individuals, do not involve co-travel together, and occur at the communal den. Comparison to permutation-based reference models suggests that den usage structures broad-scale patterns of social encounters, but that other factors influence how those encounters unfold. We discuss the dual role of communal dens in hyenas as physical and social resources, and suggest that dens are an example of a general "social piggybacking" process whereby environmental attractors take on social importance as reliable places to encounter conspecifics, causing social and spatial processes to become fundamentally intertwined.

animal behavior and cognition↗