High-tech networks of robotic platforms for the monitoring of deep-sea crustacean populations

The Crustacean Society Mid-Year Meeting (TSC 2019), 26-30 May 2019, Hong Kong.-- 1 pageOur perception of deep-sea megafaunal benthic and pelagic biodiversity depends upon the development of remote and high-frequency monitoring technologies, capable of autonomous operation and during long-term deployments. In fact, deep-sea megafauna displays large inertial, internal-tidal and even diel synchronized spatial displacements, which affect biodiversity estimations usually based on temporally scattered sampling methodologies (e.g., ship-time dependent). To address this problem, underwater observatories (cabled, or in delay-mode), autonomous underwater vehicles (AUVs), which include fast improving seafloor robots (crawlers), are being assembled into highly interconnected monitoring networks that can be used for data collection via high-bandwidth telecommunications. A time-coordinated optoacoustic (i.e., HD, laser scattering and multi-beam) imaging and passive acoustic characterization (i.e., for animal soundscapes) is being implemented to deliver time-series of counted individuals (as proxy of populations¿ rhythmic benthopelagic, nektobenthic and endobenthic movements), to be linked with the surrounding habitat forcing (i.e., via a concomitant acquisition of different oceanographic, chemical, and geological data). This multi-parametric monitoring is revealing important life traits for deep-sea species including crustaceans: it allows the scaling of behavioral states of individuals up to changes in perceived species composition (e.g., richness), their relative abundances (e.g., evenness), as well as predator-prey relationships (e.g., food web structure), with a reduced ecological footprint compared to more invasive deep-sea monitoring methods (e.g. trawling). Examples of such monitoring for crustaceans will be presented and discussedThe present work was supported by the following projects: ARIM (MartTERA ERA-Net Cofound); RESBIO (TEC2017-87861-R; Ministerio de Ciencia, Innovación y Universidades); MERCES (Grant Agreement N. 689518), and IDEM (Grant Agreement N. 11.0661/2017/750680/SUB/ENV.C2