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Abstract/Summary
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<jats:p>Abstract. Between 2018 and 2022, four pearl farming Tuamotu atolls of French Polynesia were monitored with autonomous oceanographic instruments to measure the hydrodynamics of atoll lagoons and the ocean–lagoon water exchanges. These surveys were conducted within the framework of the ANR-funded MANA (Management of Atolls) project and its extensions to additional sites. The overarching goal was to improve knowledge on the processes influencing the spat collection of the pearl oyster Pinctada margaritifera, the oyster species used to produce black pearls. These data sets are also critical for the calibration and validation of 3D high spatial resolution hydrodynamic models used to study oyster larval dispersal within lagoons. The observational strategies focused on the characterization of ocean–lagoon exchanges through passes and hoa (i.e., shallow reef flats), lagoon circulation, incident waves breaking on the forereef, water elevation inside the lagoon as well as spatial temperature variability. Chronologically, the investigated atolls were first Raroia Atoll with 9 months of measurements between May 2018 and March 2019 during which the MALIS1 and MALIS2 cruises on-board the R/V ALIS took place. It was followed by a 4 month deployment in Takapoto Atoll (November 2021 to March 2022). In late April 2022, Apataki Atoll was instrumented until end of July, followed by Takaroa measurements between July and October 2022. Apataki (Leg2) and Takaroa Atoll were conjointly instrumented during the MALIS 3 oceanographic cruise. Altogether, those multi-atoll data bring a worldwide unique oceanographic atoll data set that is useful for addressing local pearl farming questions but potentially beneficial for other fundamental and applied investigations. Each data set was post-processed, quality controlled and converted into NetCDF format. Files are available in open source into dedicated repositories in the SEANOE marine data platform. Links (DOI) of individual data sets are provided in Table 2.
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Hinweis
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DeepGreen-ID: f823c09fefbf44eba2c63e320ba347c5 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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