Raw data concerning the carbonate system and the sensory behaviour of juvenile Dicentrarchus labrax in response to mechano-acoustic and visual cues under ocean warming and acidification
|Temporal extent||2020-09-18 -2020-12-18|
|Author(s)||Cohen-Rengifo Mishal1, Mazurais David1, Begout Marie-Laure2|
|Affiliation(s)||1 : IFREMER, PFOM-ARN, F-29280, Plouzané, France
2 : MARBEC, University of Montpellier, CNRS, IFREMER, IRD, 34250 Palavas-les-Flots, Franc
|Keyword(s)||raw data, carbonate system parameters, physico-chemical parameters, sensory ecology, escape response, predator-prey, vision, mechano-audition, ocean warming, ocean acidification|
This data set is linked to a study that sought to investigate whether a mid-term 92-days exposure to warming and/or acidification alters the visual or mechano-acoustic sensory channels of the European sea bass Dicentrarchus labrax when it comes to detect and avoid simulated avian predator cues. Juveniles, aged between 283 to 316 days post hatching, were challenged in separate behavioural trials to assess their reaction facing either a shadow (visual cue) or a falling object (mechano-acoustic cue). These cues were intended to mimic an overflying bird or a bird swoop attack, respectively.
To follow the best practices of ocean acidification, the 1st and 2nd tabs show daily measurements of temperature and pH (in NIST scale). The 3rd tab shows weekly measurements of temperature and pH (in NIST and total scale), salinity, oxygen and total alkalinity that were used to calculate the carbonate system parameters, which is also shown in the 3rd tab.
Total body length (in cm, from the nose tip to end of caudal fin) was measured in a sample of 74 alive individuals upon arrival (4th tab) or in 379 dead individuals once the behavioural tests were ended (5th tab).
Abbreviations for the kinematic behavioural variables evaluated during the behavioural tests are available in the 6th tab. Data set for both the visual behavioural tests (7th tab) and the mechano-acoustic behavioural tests (8th tab) were used to run the linear mixed-effects models.
|Acknowledgements||This project was co-funded by the Ifremer Institute and the Regional Council of Brittany (Région Bretagne; postdoc SAD n°1540, IMPACIBL). The authors are thankful to the whole ARN laboratory, to the IFREMER members Philippe Miner, Pierrick Le Souchou, Xavier Cousin, Cyril Noël, Aurélien Lledo, Jean-Pierre Lafontaine, and to the intern Laura Buchet.|