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Livrables
Dr. Labarre will employ a comprehensive dissemination and communication strategy to ensure widespread sharing of research results and engage both the scientific community and the general public. Scientific dissemination will include publications in high-impact peer-reviewed journals and participation in international conferences to share findings and foster collaboration. In addition, collaboration with media teams at NPI and UiT, as well as involvement in iC3 and I-CRYME projects, will facilitate press releases and media coverage.
Data Collection and GenerationThe research project will focus on collecting and generating environmental data from the Kong Hakon VII Sea (KHS) region of the Southern Ocean, specifically targeting areas influenced by glacier discharge and various ice types, such as platelet ice, landfast ice, and pack ice. Ship-based surveys conducted onboard the SA and KPH vessels will facilitate sampling near KHS ice shelves at multiple water depths using Niskin bottles mounted on a rosette sampler equipped with a suite of sensors including a CTD (conductivity-temperature-depth), photosynthetically active radiation (PAR) sensors and biogeochemical sensors. Samples collected along the ice-ocean continuum will undergo analysis for flow cytometry and genomics, providing insights into the abundance and expression profiles of plankton communities.Data Organisation, long-term Storage and AccessThe environmental data collected and generated throughout the research will be long-term archived and accessible through the Norwegian Polar Data Centre (NPI) and the UiT DataverseNO server (https://site.uit.no/dataverseno/). Additionally, integration of these datasets into the Southern Ocean Observing System (SOOS) map (https://www.soosmap.aq/) will offer a comprehensive view of the Southern Ocean research landscape. All sequencing (genomics) data generated as part of this research will be archived with assigned accession numbers at the European Nucleotide Archive (ENA) (https://www.ebi.ac.uk/ena/). The data will be published following the FAIR Principles (Findable, Accessible, Interoperable and Reusable) and published with a Digital Object Identifier (DOI), a unique alphanumeric code that provides a permanent link to the published dataset to ensure easy access.
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