Multiparametric monitoring of fish activity rhythms in an Atlantic coastal cabled observatory
Introduction
The exploration of the benthic oceanic realms is rapidly changing, thanks to advances in imaging and sensor (i.e. oceanographic and geochemical) technologies, installed on cabled observatories (e.g. Widder et al., 2005; Schoening et al., 2012; Vardaro et al., 2013; Osterloff et al., 2016; De Leo et al., 2018). The image and contemporary environmental data collection these platforms provide, provide ecologists with high-value ecological data which experimentally approximate species Hutchinson niche (Aguzzi et al., 2020). In fact, for each species in each frame, the number of individuals can be directly related with concomitant environmental characteristics, which define the “eco-field” of those individuals (Farina and Belgrano, 2004). When multivariate time series analysis approaches are used on those bio- and environmental data sets, new indications of species life traits can be derived.
A potential of this monitoring approach is the temporal fluctuations in counted individuals can be considered as a proxy of variations in local abundance. Individuals within a population responds to habitat cycles in photophase and tides, consequently modulating their behavioural activity. In the case of fishes which show high motility, changes in behavioural swimming rate directly influence video-counting levels (e.g. Condal et al., 2012; Aguzzi et al., 2010, Aguzzi et al., 2012, Aguzzi et al., 2015a; Chauvet et al., 2018; Rountree et al., 2020). At the same time, recurring synchronous increments in counts for different species can be linked to their trophic status, deriving information on interspecific relationships and thus allowing the food-web architecture to be depicted (Aguzzi et al., 2020). Finally, when this highly integrated biological and environmental monitoring is executed over consecutive years, it can, in principle, also provide clues on the overall performance of benthic ecosystems' productivity (e.g. Thomsen et al., 2017), being derived information of relevance for management policies (Danovaro et al., 2017).
Time-lapse image and coupled multiparametric video monitoring could also be used to explore communities' response to stochastic environmental events e.g. seismic activity or meteorology (e.g. Aguzzi et al., 2012; Matabos et al., 2014). To date, the response of animal behaviour to those effects is still poorly characterized. The analyses of the soundscape (i.e. the sounds in an environment from geophysical, oceanographic or biological source, including maritime activities) (Pijanowski et al., 2011) could provide an additional layer of information since its quality might condition fish behaviour (e.g. predators' presence; Rountree et al., 2006; Slabbekoorn et al., 2010; Wall et al., 2014). Moreover, the simple passive acoustic recognition of fish vocalizations could complement traditional survey methods (Staaterman et al., 2017), allowing species traceability beyond imaging methods (Rountree et al., 2020).
Time-lapse multiparametric synchronous video, oceanographic and sound monitoring by cabled observatories may provide a roadmap to deliver ancillary behavioural information, to explain the temporal variability in catches of commercial species. As per image spotting probability, activity rhythms influence species availability to fishing at all depths of the continental margin and in the deep sea (Aguzzi and Company, 2010; Aguzzi et al., 2015b). In the case of fish, important ancillary data could be produced by cabled observatory video-monitoring, by adding new behavioural observations for capture management models (e.g. Follana-Berná et al., 2019; Rountree et al., 2020). In fact, the comparison of video and trawl data has an established research record using movable lander assets (Priede and Merrett, 1996; Bailey et al., 2007) and an important advancement has been recently conducted with Baited Remote Underwater Video Systems (e.g. BRUVS; Bicknell et al., 2016; Langlois et al., 2018).
To the best of our knowledge, there are no previous studies on the behaviour of coastal Atlantic fish communities by cabled observatories, combining time-lapse imagery with concomitant oceanographic monitoring including sound. Therefore, the modulatory effect on the behaviour of coastal fishes (and resulting species composition) of combined tidal and day-night cycles in a variable soundscape, is still poorly known. Here, we used such a multiparametric video and environmental monitoring approach to track several fish species of commercial value in Galway Bay. Species activity rhythms response (in terms of video-capture availability) was evaluated into an area where behavioural modulation must occur upon tidal and light mixed regimes, and potentially, upon a non-previously quantified environmental noise.
Section snippets
The study area and the platform
Galway Bay (Galway, Ireland) is a large semidiurnal tidal bay, protected from the open Atlantic Ocean by the Aran Islands (Fig. 1). The dynamics within the bay are mainly influenced by the Atlantic flows toward the bay and by wind driven currents, but freshwater discharges, primarily from the River Corrib, are also significant. The general direction of water coincided with the tidal current direction, i.e. into Galway Bay, on the flooding tide (O'Donncha et al., 2015). In this area, the
Faunal general remarks
A total of 747 videos were viable for faunal inspection, with the remaining 21 unusable due to high turbidity or lighting malfunction. In that imaging material, we detected several fish species, a majority of which are of commercial relevance (Table 1 and Fig. 2): Clupea harengus, Trachurus trachurus, Trisopterus minutus, T. luscus, Gadus morhua, Pollachius pollachius, Melanogrammus aeglefinus, Merlangius merlangus, Ctenolabrus rupestris, Labrus bergylta, Chelidonichthys lucerna and Zeus faber.
Discussion
In this study, we characterized behavioural rhythms of species in a coastal fish community, by high-frequency video and environmental multiparametric monitoring in Galway Bay. Despite the marked semi-diurnal tidal regime of the coastal area, most of the fishes showed marked day-night and not hydrodynamic driven visual count patterns. Those behavioural results are framed in a strongly tidal context. Tidal current direction is from the Atlantic Ocean toward Galway Bay, on the flooding tide (
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
Dr. J. Aguzzi and J. del Rio are members of the CSIC-UPC Associated Unit “Tecnoterra”, managing the OBSEA platform, an EMSO testing-site. This work was developed within the framework of the Projects ADVANCE (H2020 INFRAIA-2014-2015 grant agreement 654410, Jerico-Next TNA), RESBIO (TEC2017-87861-R) and ARIM (Autonomous Robotic sea-floor Infrastructure for benthopelagic Monitoring; MarTERA ERA-Net Cofound).
The SmartBay cabled observatory was funded by Science Foundation Ireland (SFI) as part of
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