Frontiers in Marine Science (Mar 2022)

Long-Term Monitoring of Diel and Seasonal Rhythm of Dentex dentex at an Artificial Reef

  • Marco Francescangeli,
  • Valerio Sbragaglia,
  • Joaquin del Rio Fernandez,
  • Enric Trullols,
  • Josefina Antonijuan,
  • Immaculada Massana,
  • Joana Prat,
  • Marc Nogueras Cervera,
  • Daniel Mihai Toma,
  • Jacopo Aguzzi,
  • Jacopo Aguzzi

DOI
https://doi.org/10.3389/fmars.2022.837216
Journal volume & issue
Vol. 9

Abstract

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Behavioral rhythms are a key aspect of species fitness, since optimize ecological activities of animals in response to a constantly changing environment. Cabled observatories enable researchers to collect long-term biological and environmental data in real-time, providing relevant information on coastal fishes’ ecological niches and their temporal regulation (i.e., phenology). In this framework, the platform OBSEA (an EMSO Testing-Site in the NW coastal Mediterranean) was used to monitor the 24-h and seasonal occurrence of an ecologically iconic (i.e., top-predator) coastal fish species, the common dentex (Dentex dentex). By coupling image acquisition with oceanographic and meteorological data collection at a high-frequency (30 min), we compiled 8-years’ time-series of fish counts, showing daytime peaks by waveform analysis. Peaks of occurrence followed the photophase limits as an indication of photoperiodic regulation of behavior. At the same time, we evidenced a seasonal trend of counts variations under the form of significant major and minor increases in August and May, respectively. A progressive multiannual trend of counts increase was also evidenced in agreement with the NW Mediterranean expansion of the species. In GLM and GAM modeling, counts not only showed significant correlation with solar irradiance but also with water temperature and wind speed, providing hints on the species reaction to projected climate change scenarios. Grouping behavior was reported mostly at daytime. Results were discussed assuming a possible link between count patterns and behavioral activity, which may influence video observations at different temporal scales.

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