Dear colleagues, we are pleased to share our recent publication in Methods in Ecology and Evolution: Labriola, M. S., Pammer, P. O., Pedrazzi, G., Giacomini, G., Jona Lasinio, G., & Pace, D. S. (2025). A functional data analysis approach for modelling frequency‐modulated tonal sounds in animal communication. /Methods in Ecology and Evolution/, 00, 1-15. https://doi.org/10.1111/2041-210X.14446 ABSTRACT: * Frequency modulation (FM) is believed to play a major role in encoding information in tonal vocal communication. However, most studies aimed at investigating acoustic variability rely on the manual measurement of acoustic parameters, and the implementation of multivariate techniques, which represent only partially sound FM. Thus, innovative modelling approaches able to capture local FM dynamics are needed for tonal sounds modelling. These kinds of methodological developments in bioacoustics might be key for further understanding animal behaviour and ecology. * We propose the application of a functional data analysis (FDA) approach to model extracted FM patterns, which entails the transformation of acoustic signals into continuous functions. We describe a Raven-to-R FDA workflow for modelling tonal sounds and we highlight two of its potential applications for classification aims and FM analysis in relation to behavioural, social, and environmental factors. For illustrative purposes, the approach performance was tested on FM patterns (contours) of signature whistles emitted by bottlenose dolphins (/Tursiops truncatus/), to investigate their acoustic variability and potential information content. * Our results show that tonal sounds are inherently of functional nature and can be treated as such for FM analysis. We found that building the FDA sound curves using 25 B-spline basis functions was the most appropriate setting for the functionalisation of dolphin whistles. Our approach was able to accurately reconstruct the FM patterns of the modelled tonal sounds and even to capture their fine-scale modulations, with a precision of 80%. Functional clustering showed an accuracy up to 89% for short whistles. Estimated functional coefficients of the regression model suggested that different contextual factors have a significant effect on the FM patterns of SWs. * The adoption of an FDA approach appears to be quite promising for the study of frequency-modulated tonal sounds, both for classification aims and in-depth FM analysis. The limitations and advantages of the approach were discussed. We developed and tested a new methodology able to fill knowledge gaps in animal communication, and we anticipate it will lead to advances in the ethological and ecological understanding of wild animal populations. We would be happy to discuss further development with this community. Best, Maia, Petra, Giulia, Giancarlo, Giovanna and Daniela -- /MARIA SILVIA LABRIOLA PhD Student in Evolutionary Biology and Ecology Department of Biology - University of Rome Tor Vergata, Rome, Italy Mail: maria.silvia.labriola@uniroma2.it ORCID iD: https://orcid.org/0009-0007-2666-8673 ResearchGate: https://www.researchgate.net/profile/Maria-Silvia-Labriola Lab: https://www.recolab.org//