Robots Explore plankton driven Fluxes in the marine twIlight zoNE
The scientific objective of REFINE is to understand and quantify the physical, biological and biogeochemical processes controlling the biological carbon pump, a key component of the oceanic CO2 sequestration. The oceanic twilight...
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Descripción del proyecto
The scientific objective of REFINE is to understand and quantify the physical, biological and biogeochemical processes controlling the biological carbon pump, a key component of the oceanic CO2 sequestration. The oceanic twilight zone (TZ), which is located between the depths of 100 and 1000 m and represents 20% of the ocean's volume, is where these processes occur. Yet the TZ is not properly sampled during most ship-based oceanographic cruises and, because of its depths, it escapes satellite remote sensing. Hence the TZ is one of the least known environments on Earth. The functioning of the TZ is highly dependent on the flux of matter and energy coming from the overlying well-lit euphotic zone (EZ). I have developed the REFINE ground-breaking, robotic-based approach to address the physical, biological and biogeochemical linkages between the EZ and the TZ, with special emphasis on the roles of phyto and zooplankton communities. I will implement REFINE through the following four main coordinated actions:
• Development of a new generation of multidisciplinary vertically profiling floats, uniquely able to robotically address phyto and zooplankton community composition.
• Achievement of ~3 years robotic-based process studies in five oceanic zones, representative of the diversity of biogeochemical conditions and responses to climate change in the global ocean, over a continuum of temporal scales ranging from diel to interannual.
• In-depth analysis of the unique REFINE dataset to perform carbon flux budgets within the TZ, and understand the physical and plankton-driven mechanisms involved in the EZ-TZ linkage and their impacts on the resulting fate of organic carbon and fluxes to ocean depths.
• Upscaling of regional processes to the global ocean through the use of artificial intelligence methods, in particular by taking advantage of multisource observations from REFINE robots and earth observation satellites.
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