An Automated Pipeline for Image Processing and Data Treatment to Track Activity Rhythms of Paragorgia arborea in Relation to Hydrographic Conditions

Abstract

Imaging technologies are being deployed on cabled observatory networks worldwide. They allow for the monitoring of the biological activity of deep-sea organisms on temporal scales that were never attained before. In this paper, we customized Convolutional Neural Network image processing to track behavioral activities in an iconic conservation deep-sea species—the bubblegum coral Paragorgia arborea—in response to ambient oceanographic conditions at the Lofoten-Vesterålen observatory. Images and concomitant oceanographic data were taken hourly from February to June 2018. We considered coral activity in terms of bloated, semi-bloated and non-bloated surfaces, as proxy for polyp filtering, retraction and transient activity, respectively. A test accuracy of 90.47% was obtained. Chronobiology-oriented statistics and advanced Artificial Neural Network (ANN) multivariate regression modeling proved that a daily coral filtering rhythm occurs within one major dusk phase, being independent from tides. Polyp activity, in particular extrusion, increased from March to June, and was able to cope with an increase in chlorophyll concentration, indicating the existence of seasonality. Our study shows that it is possible to establish a model for the development of automated pipelines that are able to extract biological information from times series of images. These are helpful to obtain multidisciplinary information from cabled observatory infrastructures.

Framing Cutting-Edge Integrative Deep-Sea Biodiversity Monitoring via Environmental DNA and Optoacoustic Augmented Infrastructures

“…The step forward to efficiently augment the in situ deep-sea ecological monitoring capability of cabled observatories and their docked platforms envisions the ability to collect genetic and imaging data in situ and process the information in real time using automated pipelines (e.g., Osterloff et al, 2016Osterloff et al, , 2019Lopez-Vasquez et al, 2020;Zuazo et al, 2020). These developments rely on the establishment of AI algorithms for taxonomic assignment as well as dedicated reference DNA sequence databases.…”

Integrating Diel Vertical Migrations of Bioluminescent Deep Scattering Layers Into Monitoring Programs

“…Various fixed and mobile platforms (i.e., benthic crawler) of the NEPTUNE Cabled Observatory operated by Ocean Networks Canada 1 have been used for similar studies, with faunal behavior in a range of aphotic depths being connected to the local tidal regimes and to periodic fluctuations of oceanographic and atmospheric conditions (e.g., Doya et al, 2014;Matabos et al, 1 www.oceannetworks.ca 2014; Chatzievangelou et al, 2016;Lelièvre et al, 2017). Daynight and tidal-related rhythms have been recently found at the Lofoten-Vesterålen (LoVe) deep-sea observatory in Norway for sessile and motile megafauna such as the bubblegum coral (Paragorgia arborea; Zuazo et al, 2020), a deep, coldwater coral (Lophelia pertusa; Osterloff et al, 2019), shrimps (Osterloff et al, 2016), rockfish (Sebastes sp. ; described in Aguzzi et al, 2020b but not formally analyzed yet by chronobiological statistics), and other fauna (Purser, 2015).…”

Autonomous Surface and Underwater Vehicles as Effective Ecosystem Monitoring and Research Platforms in the Arctic—The Glider Project

“…The increased primary production enhances biological activity from the seabed and across the entire water column. The increase in chlorophyll concentration prompts polyp activity in corals [23] and is followed by the ascension to the surface of the overwintering copepod Calanus finmarchicus, the most abundant zooplankton in the region. C. finmarchicus feeds on the phytoplankton production and reproduces during spring and summer [19,39,40].…”

“…Building this knowledge requires additional and persistent data collection that cannot rely solely on sampling by traditional vessels due to practical and economic reasons. Currently, autonomous continuous long-term in situ monitoring programs exist for the LoVe region thanks to an underwater observatory system that employs crawler and stationary platforms to study ecological processes in the deep sea (https://love.equinor.com/) (accessed on 7 October 2021) [12,[22][23][24][25]. The deep sea, however, is a highly dynamic environment where benthic ecosystems are interconnected with the water column and the surface through the exchange of energy, mass, or nutrients [26][27][28].…”