Objective
Remineralisation of the particulate matter that sinks from the surface to the deep ocean is a crucial component of the biological carbon pump, because it ultimately influences the Earth’s climate. Due to the difficulties to observe this process, however, little is known about the variability of mesopelagic (~200-1000 m) remineralisation. REOPTIMIZE aims to improve knowledge of mesopelagic remineralisation by exploiting – for the first time – time-series of optical proxies of particle size and oxygen consumption collected by autonomous robotic platforms (i.e. Bio-Argo floats). These new estimates of remineralisation, acquired at unprecedented spatial and temporal resolution, will improve our knowledge of the biological carbon pump and ultimately reduce uncertainties in current and future estimates of the ocean carbon budget.
REOPTIMIZE will combine models and field measurements. Field data from the Atlantic Meridional Transect cruises will be firstly exploited to extend current relationships between optical proxies and particle size from the ocean surface to the mesopelagic zone. Then, spectral light backscattering data acquired by a fleet of Bio-Argo floats in under-sampled oceanic areas will be converted to size-revolved carbon biomasses. These biomass estimates will then be combined with simultaneous oxygen consumption rates and analysed, by means of simple models of particle dynamics, to derive particle disaggregation rates in the mesopelagic. These inter-disciplinary and innovative activities will establish a two-way exchange of knowledge between the Researcher’s and the host institution and to enhance their European and international network of collaborators. Outcomes of REOPTIMIZE will have an impact on the European strategy for global ocean observations.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencesdatabases
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticsautonomous robots
- natural sciencesphysical sciencesoptics
- agricultural sciencesagricultural biotechnologybiomass
- natural sciencesearth and related environmental sciencesgeochemistrybiogeochemistry
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Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
PL1 3DH Plymouth
United Kingdom
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.