Revealing Chronotypes Across Aquatic Species Using Acoustic Telemetry

Abstract

Acoustic telemetry offers valuable opportunities to investigate individual variability in circadian‐related and other behaviours and how environmental cues shape these patterns in wild fish populations. However, this potential has not yet been fully exploited. We conducted a meta‐analysis on 44 datasets from 34 distinct marine and freshwater species and different types of data (acoustic detections, depth, acceleration and positioning). Our aim was to explore the potential of acoustic telemetry in identifying chronotypes as consistent among‐individual differences in circadian‐related behaviours. First, we applied hidden semi‐Markov models to classify individual time series into active and rest states. Subsequently, we computed two classical circadian‐related behavioural traits: awakening time (as the activity onset) and rest onset (as the activity offset). Subsequently, we identified distinct phenotypes by decomposing behavioural variation into within‐ and among‐individual components based on repeatability scores. We found evidence of distinct chronotypes in 17 species, with average repeatability scores of 0.52 for awakening time and 0.43 for rest onset, revealing that chronotypes are common in aquatic species. Our findings highlight that both the data type, particularly acceleration sensors, and the number of detections are effective tools for exploring chronotypes. Our study proposes a novel approach to characterising daily activity patterns in aquatic species, predominantly in fishes, and provides guidelines for investigating chronotypes across diverse taxa. We emphasise the promise of biotelemetry and advanced statistical models for improving our understanding of the behaviour of aquatic species and highlight the value of synthesising across large data sets collected in networks of biotelemetryprojects.

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