Biology subjects

Manser, M. B.

Publications and source records attributed to Manser, M. B..

4 recordsLinked to original sources

bioRxiv2026

Decomposing alarm-calling behaviour to investigate context-dependent threat discrimination and response escalation in a social mongoose

Prey can adjust their behaviour to perceived predation risk, which may induce non-consumptive fitness effects. However, quantifying perceived risk in field studies remains challenging as anti-predator behaviours often integrate multiple processes such as encounter probability and detection capacity. Partitioning prey responses into sub-processes may therefore provide novel insights on predation risk perception. To this end, we decomposed meerkat alarm-calling behaviour into threat discrimination, and response escalation. Using 23 years of data from a wild population in the Kalahari, we evaluated the context-dependence of both components in relation to landscape features, and group composition. We defined threat discrimination as the probability to emit an alarm call at predators (eagles) relative to non-predators (vultures) and response escalation as the strength and intensity of the ensuing collective reaction. We found that discrimination varied with habitat and vegetation productivity. Furthermore, larger groups and the presence of pups increased meerkat threat discrimination, but only during the dry season. Response escalation varied with habitat and group size, but pup presence only increased reaction strength. The contrasting context-dependence among the two alarm-calling components support decomposing compound behaviours rather than quantifying perceived risk from a single behaviour. Thus, we recommend future studies to use this approach, when possible, to improve inference on prey perception and responses to risk.

animal behavior and cognition↗

bioRxiv2024

Spatial position relative to group members affects weight gain in meerkats (Suricata suricatta)

Social animals often face a trade-off between the costs of foraging competition among group members and the benefits of protection from predators offered by group living. The spatial position of an individual in relation to the other group members during foraging can mediate the effects of this trade-off as individuals at the front or edge may have better access to food resources, but also higher predation risk than individuals near the centre of the group. Using meerkats (Suricata suricatta) as a model species, we investigated the effect of individual spatial position within a group on foraging success. We determined the spatial position of individuals in a meerkat group by fitting the animals with high-resolution GPS loggers. As a proxy of foraging success, we used meerkats individual body weight differences between the start and the end of daily data collection over foraging periods (3 hours). We found significant individual differences in meerkats spatial positions within the group. In addition, age-dependent differences in spatial position became obvious, with younger individuals spending more time in the centre of the group and less time in the front. However, younger individuals who spent more time on the side of the group relative to older individuals had higher daily weight gain, indicating more successful foraging. In older individuals, we found that the dominant females tended to spend more time towards the front of the group, but gained less weight in this location, contrary to the predicted association between front edge of the group and better access to food resources. Our results suggest that the relationship between weight gain and spatial position is highly nuanced and likely dependent on more than just trade-offs between foraging success and predation risk. HighlightsO_LISpatial position relative to other group members during foraging was a highly repeatable trait for individual meerkats, though time spent near the front of the group was more strongly influenced by individual traits (age, sex, and social rank) C_LIO_LIYounger meerkats spent less time in the front and more time in the centre of the group relative to older meerkats, but had the highest foraging success towards the sides of the group C_LIO_LIDominant female meerkats spent more time near the front of the group, but had reduced foraging success in this position C_LIO_LIMeerkats may trade-off more than just foraging success and predation risk when making decisions about where to position themselves relative to other group members C_LI

animal behavior and cognition↗

bioRxiv2024

Same data, different results? Evaluating machine learning approaches for individual identification in animal vocalisations

Automated acoustic analysis is increasingly used in behavioural ecology, and determining caller identity is a key element for many investigations. However, variability in feature extraction and classification methods limits the comparability of results across species and studies, constraining conclusions we can draw about the ecology and evolution of the groups under study. We investigated the impact of using different feature extraction (spectro-temporal measurements, linear and Mel-frequency cepstral coefficients, as well as highly comparative time-series analysis) and classification methods (discriminant function analysis, neural networks, random forests, and support vector machines) on the consistency of caller identity classification accuracy across 16 mammalian datasets. We found that Mel-frequency cepstral coefficients and random forests yield consistently reliable results across datasets, facilitating a standardised approach across species that generates directly comparable data. These findings remained consistent across vocalisation sample sizes and number of individuals considered. We offer guidelines for processing and analysing mammalian vocalisations, fostering greater comparability, and advancing our understanding of the evolutionary significance of acoustic communication in diverse mammalian species.

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↗