Robust rhythm reporting will advance ecological and evolutionary research

Hersh, T. A., Ravignani, A., & Burchardt, L. (2023). Robust rhythm reporting will advance ecological and evolutionary research. Methods in Ecology and Evolution, 14(6), 1398-1407. doi:10.1111/2041-210X.14118.

Rhythmicity in the millisecond to second range is a fundamental building block of communication and coordinated movement. But how widespread are rhythmic capacities across species, and how did they evolve under different environmental pressures? Comparative research is necessary to answer these questions but has been hindered by limited crosstalk and comparability among results from different study species.
Most acoustics studies do not explicitly focus on characterising or quantifying rhythm, but many are just a few scrapes away from contributing to and advancing the field of comparative rhythm research. Here, we present an eight-level rhythm reporting framework which details actionable steps researchers can take to report rhythm-relevant metrics. Levels fall into two categories: metric reporting and data sharing. Metric reporting levels include defining rhythm-relevant metrics, providing point estimates of temporal interval variability, reporting interval distributions, and conducting rhythm analyses. Data sharing levels are: sharing audio recordings, sharing interval durations, sharing sound element start and end times, and sharing audio recordings with sound element start/end times.
Using sounds recorded from a sperm whale as a case study, we demonstrate how each reporting framework level can be implemented on real data. We also highlight existing best practice examples from recent research spanning multiple species. We clearly detail how engagement with our framework can be tailored case-by-case based on how much time and effort researchers are willing to contribute. Finally, we illustrate how reporting at any of the suggested levels will help advance comparative rhythm research.
This framework will actively facilitate a comparative approach to acoustic rhythms while also promoting cooperation and data sustainability. By quantifying and reporting rhythm metrics more consistently and broadly, new avenues of inquiry and several long-standing, big picture research questions become more tractable. These lines of research can inform not only about the behavioural ecology of animals but also about the evolution of rhythm-relevant phenomena and the behavioural neuroscience of rhythm production and perception. Rhythm is clearly an emergent feature of life; adopting our framework, researchers from different fields and with different study species can help understand why.
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