Biology subjects

Renaud-Goud, P.

Publications and source records attributed to Renaud-Goud, P..

3 recordsLinked to original sources

bioRxiv2025

Acoustic markers of negative arousal in lambs: evidence from behavioural and eye thermal profiles

Vocalizations are known indicators of emotional arousal in animals, but validation using simultaneously collected physiological and behavioural measures remains limited to a few species. This study investigated sheep vocal expression of negative emotional arousal using stress-related behaviours and eye temperature as non-invasive arousal indicators. To this aim, twenty lambs underwent a short-term isolation test with two phases aimed at eliciting different levels of arousal in response to separation from conspecifics: partial isolation, where lambs maintained visual, acoustic and tactile contact with conspecifics through a fence, and full isolation (complete separation). During full isolation, lambs expressed higher bodily activation--spending more time running, jumping, and changing state behaviours--and produced more open-mouthed bleats (321 vs 27) than in partial isolation, validating higher arousal. Eye temperature also increased from partial to full isolation (however only in small lambs and not large ones). Calls emitted in full isolation were characterised by higher frequencies, were less tonal (more chaos) and had shorter durations. When combining behavioural and physiological assessment of arousal and testing their impact on the spectro-temporal structure of vocalizations, we found that bodily activation, but not eye peak temperature, impacted on the frequency distribution and tonality of the calls. Call duration increased with eye temperature, but only in lambs expressing high bodily activation, while the mean of the second formant increased with eye temperature in smaller but not larger lambs. Overall, lamb vocalizations indicate arousal and are correlated with bodily activation, while co-variations with physiological measures depended on behaviour and individual traits. HighlightsO_LIAnimal calls indicate emotional arousal, but few species have validated measures C_LIO_LILamb calls became higher in frequency, less tonal and shorter with negative arousal C_LIO_LICalls indicated emotional arousal and were correlated with bodily activation C_LIO_LIChanges in calls with eye temperature depended on behaviour and individual traits C_LI

animal behavior and cognition↗

bioRxiv2025

Socio-acoustic co-selection? Vocal encoding of sociability prevails over emotions in sheep bleats

Vocalisations of animals are good indicators of their emotions. Temperament is known to influence the regulation and expression of emotions. However, how animal temperament affects their vocalisations and particularly their vocal expressions of emotions remains largely unexplored. Sociability is often measured as the behavioural reactivity to social separation and is a temperament trait intrinsically linked to emotional reactivity. Most social species respond to this challenging situation using contact calls. Here, we investigated whether the acoustic structure of these calls reflect sociability, emotions or both. Among 152 recorded female lambs, 42 belonged to two diverging sheep lines selected for high or low sociability. High bleats were recorded both in isolation (social challenge, all lambs) then before receiving a food treat (non-social challenge, selected lambs) to investigate the link between vocalisations, emotions and heritable sociability. The acoustic features of isolation bleats differed between lines, but it was not the case for pre-food treat bleats. Surprisingly, the genetic selection index and social behaviour explained better the structure of isolation bleats than the arousal. Last, encoding of individuality in isolation bleats was impaired by the genetic selection. Our findings show that selecting for sociable animals affects vocal signatures in calls produced during a social challenge, leading us to hypothesize a socio-acoustic co-selection.

animal behavior and cognition↗

bioRxiv2023

SoundChunk: A free open-source and user oriented R package for acoustic data management, sound detection and extraction

In a standard bioacoustic experiment setting, after data collection and before data analysis lies a time-consuming process that consists in extracting and labeling sounds of interest (chunks) from usually long recording files, collected through spreading PAM (Passive Acoustic Monitoring) for instance, and storing them in a structured and exploitable way based on both the meta-data of the initial recordings and the label data. SoundChunk is a user-oriented package in R that aims at providing tools for any R user so that they can go efficiently and comfortably through this process. Usually, the tasks include detecting, labeling, and extracting sound from audio files. With the recent advance of Machine Learning, especially Convolutional Neural Networks, some of these tasks are integrated in the ML framework; however, the learning phase relies on labeled chunks that need to be created. Three types of data are involved in the process: (i) WAVE files, whether they come from the initial recordings or are generated by chunk extraction, (ii) meta-data describing the conditions in which the initial WAVE files were recorded, (iii) label track files, whether they are automatically generated or manually input, that contain timed information about audio files. SoundChunk provides utilities to sanely manipulate each of these three categories and combine them into easy-to-use chunks along with their meta-data. We expose functionalities that: (i) clean and restructure label tracks that are readable by softwares like Audacity, (ii) chop long recordings into small fixed-size slices, (iii) detect chunks both interactively (so that robust detection settings can be found on a subset of the recordings) and automatically (so that the detection is applied across all recordings), (iii) dispatch chunks into structured folder(s), according to their meta-data. MaintainersThe team is open for suggestions and contributions. Contact: soundchunknfeat@proton.me (currently: ASV, PRG). UsersThis document is available as a vignette once the package is loaded an may be used on a set of example data (Villain and Renaud-Goud 2023).

bioinformatics↗