Towards an optimal design for ecosystem-level ocean observatories

Abstract

Four operational factors, together with high development cost, currently limit the use of ocean observatories in ecological and fisheries applications: 1) limited spatial coverage, 2) limited integration of multiple types of technologies, 3) limitations in the experimental design for in situ studies, and 4) potential unpredicted bias in monitoring outcomes due to the infrastructure's presence and functioning footprint. To address these limitations, we propose a novel concept of a standardised 'ecosystem observatory module' structure composed of a central node and three tethered satellite pods together with permanent mobile platforms. The module would be designed with a rigid spatial configuration to optimise overlap among multiple observation technologies, each providing 360° coverage of a cylindrical or hemi-spherical volume around the module, including permanent stereo video cameras, acoustic imaging sonar cameras, horizontal multibeam echosounders, and a passive acoustic array. The incorporation of multiple integrated observation technologies would enable unprecedented quantification of macrofaunal composition, abundance, and density surrounding the module, as well as the ability to track the movements of individual fishes and macroinvertebrates. Such a standardised modular design would allow for the hierarchical spatial connection of observatory modules into local module clusters and larger geographic module networks providing synoptic data within and across linked ecosystems suitable for fisheries and ecosystem-level monitoring on multiple scales.

Burrow emergence rhythms of Nephrops norvegicus by UWTV and surveying biases

“…In addition, different stand-alone or cabled observatories, holding several seabed and water column sensors for environmental monitoring (e.g. the OBSEA or SmartBay; respectively, https ://www.obsea .es and https ://www.smart bay.ie/), could be used to picture burrow emergence modulation (for an insight on monitoring network geometry and characteristics see 65,66 ). The different observational points could be synchronously used to account for the control of oceanographic and ecological drivers on the burrowing behavior of the species 67 .…”

Global Deep-Sea Biodiversity Research Trends Highlighted by Science Mapping Approach

“…The quantification of large-sized components (macro-and megafauna), which was usually approached with traditional tools (e.g., dredging and trawling), now occurs through different fixed-cabled and mobile platforms equipped with a wide variety of imaging devices, which allow seascape characterization approaches (Danovaro et al, 2020a). In fact, imaging-based classification of species and the counting of individuals as well as the computing of different biological variables (e.g., size class frequencies, surface densities, and biomass) and life-trait labeling (e.g., predator-prey relationships, scavenging, and bioturbation) allow the calculation of more complex ecological indicators (Rountree et al, 2019;Aguzzi et al, 2020).…”

“…This influences our perception of biodiversity and derived information on species interactions (to establish food web architectures) (Aguzzi and Company, 2010). More sound data will be obtained with multisensory cabled and docked mobile platforms in a highfrequency, prolonged, and remote fashion (Aguzzi et al, 2019;Rountree et al, 2019).…”

“…Some of this debate is centered on species endemicity and rarity, which may be a better metric than species richness for assessing the role of biodiversity in ecosystem functioning (Sigwart et al, 2019;Danovaro et al, 2020a). Unfortunately, these indices cannot be accurately calculated or interpreted due to several constraints, including the sampling tools and the exploration/monitoring technologies utilized (Aguzzi et al, 2019;Rountree et al, 2019). In contrast, a better metric for marine biodiversity evaluation could be based on the measurement of cryptic (genetic) diversity rather than "species" diversity, as these factors are not necessarily correlated (Costello and Chaudhary, 2017).…”

The unexploited potential of listening to deep‐sea fish

“…Some of these studies suffered from self‐generated noise coming from inboard instrumentation which compromised the possibility of recording low‐amplitude sounds, including fish calls. Therefore, a fundamental requirement for a successful PAM of deep‐sea fish is a type of deployment which minimizes self‐noise (Rountree et al., 2020; Rountree & Juanes, 2010; Wall et al., 2014). This is the case of static acoustic monitoring (SAM; Bolgan et al., 2020; Carriço et al., 2019; Carriço et al, in press; Cato, 1978; McCauley & Cato, 2016; Wall et al., 2013) and of gliders (Bolgan et al., 2020; Wall et al., 2013, 2017).…”