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Chronotypes-Personality behavioural syndromes in wild marine fish [dataset]

Authors :
Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
European Commission
Federal Ministry of Education and Research (Germany)
Martorell Barceló, Martina [mmartorell@imedea.uib-csic.es]
Martorell Barceló, Martina
Signaroli, Marco
Barceló-Serra, Margarida
Lana, Arancha
Aspillaga, Eneko
Garau, Amalia
Arlinghaus, Robert
Alós, Josep
Ministerio de Ciencia e Innovación (España)
Agencia Estatal de Investigación (España)
European Commission
Federal Ministry of Education and Research (Germany)
Martorell Barceló, Martina [mmartorell@imedea.uib-csic.es]
Martorell Barceló, Martina
Signaroli, Marco
Barceló-Serra, Margarida
Lana, Arancha
Aspillaga, Eneko
Garau, Amalia
Arlinghaus, Robert
Alós, Josep
Publication Year :
2023

Abstract

This dataset encompasses all necessary data required to replicate the study, `Chronotypes-Personality behavioural syndromes in wild fish’. The data were obtained through standardised behavioural tests conducted under laboratory conditions on 63 Pearly Razorfish (Xyrichtys novacula) individuals between April and July of 2019. Over a week, the fish were maintained in isolated aquariums to test their behaviours, including exploration, activity, boldness, and aggression, conducted daily. A Raspberry Pi system, equipped with the YOLOv5 deep-learning automatic tracking algorithm, was used to record these tests and calculate the fish's minute-by-minute position, providing essential data for evaluating exploration and activity. This system also stored videos to retrospectively obtain boldness and aggression data. Each test included only those individuals with at least two measurements. After the laboratory period, the fish were tagged with acoustic tags and returned to the sea to measure their chronotypes; only individuals with at least seven consecutive days of data were considered. The chronotype data, obtained from a previous study, are represented here through the previously derived scores. These laboratory-based experimental data were analysed using R software. In the exploration context, positional data were translated into total active time (TimeOut), minimum distance to the toy (MinDistance), and time spent near the toy (TimeToy). For activity, the data were converted into total active time (TimeOut), total distance covered (Distance), areas (CoreArea and Area), and direction angles (MeanAngle and KappaAngle). A Principal Component Analysis (PCA) was conducted to obtain the scores for exploration, activity, and aggressiveness. Upon acquiring these scores, trait repeatability was computed using a Linear Mixed-Effects Model, fitting the experimental day (Day), the total length of the individual (Size), and the internal condition (Condition) as fixed factors, and the i

Details

Database :
OAIster
Notes :
https://www.geonames.org/2514239/mallorca.html, name=Mallorca; lat=39.6078; long=3.01197, start=2019-04; end=2019-07, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1395196458
Document Type :
Electronic Resource