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Revealing Chronotypes Across Aquatic Species Using Acoustic Telemetry

Authors: Martina Martorell‐Barceló; David Abecasis; Mourad Akaarir; Alexandre Alonso‐Fernández; Robert Arlinghaus; Eneko Aspillaga; Margarida Barcelo‐Serra; +21 Authors

Revealing Chronotypes Across Aquatic Species Using Acoustic Telemetry

Abstract

ABSTRACTAcoustic 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.

Countries
Netherlands, Spain, Portugal, Germany, Spain
Keywords

Hidden semi-markov models, Hidden semi-Markov models, hidden semi-Markov models, behavioural types repeatability, behavioural types, biotelemetry, Behavioural types, Repeatability, repeatability, Biotelemetry, circadian-related behaviours, Circadian-related behaviours

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
hybrid