Predicting global distributions of eukaryotic plankton communities from satellite data

Kaneko Hiroto, Endo Hisashi, Henry Nicolas, Berney Cédric, Mahe Frédéric, Poulain Julie, Labadie Karine, Beluche Odette, El Hourany Roy, Acinas Silvia G., Babin Marcel, Bork Peer, Bowler Chris, Cochrane Guy, de Vargas Colomban, Gorsky Gabriel, Guidi Lionel, Grimsley Nigel, Hingamp Pascal, Iudicone Daniele, Jaillon Olivier, Kandels Stefanie, Karsenti Eric, Not Fabrice, Poulton Nicole, Pesant Stéphane, Sardet Christian, Speich Sabrina, Stemmann Lars, Sullivan Matthew B., Sunagawa Shinichi, Chaffron Samuel, Wincker Patrick, Nakamura Ryosuke, Karp-Boss Lee, Boss Emmanuel, Bowler Chris, de Vargas Colomban, Tomii Kentaro, Ogata Hiroshi Y.. 2023. Predicting global distributions of eukaryotic plankton communities from satellite data. ISME Communications, 3 (1), 9 p.

Url - jeu de données - Entrepôt autre : https://www.genome.jp/ftp/db/community/tara/Satellite/ / Url - autres données associées : https://github.com/hirotokaneko/plankton-from-satellite

Résumé : Satellite remote sensing is a powerful tool to monitor the global dynamics of marine plankton. Previous research has focused on developing models to predict the size or taxonomic groups of phytoplankton. Here, we present an approach to identify community types from a global plankton network that includes phytoplankton and heterotrophic protists and to predict their biogeography using global satellite observations. Six plankton community types were identified from a co-occurrence network inferred using a novel rDNA 18 S V4 planetary-scale eukaryotic metabarcoding dataset. Machine learning techniques were then applied to construct a model that predicted these community types from satellite data. The model showed an overall 67% accuracy in the prediction of the community types. The prediction using 17 satellite-derived parameters showed better performance than that using only temperature and/or the concentration of chlorophyll a. The constructed model predicted the global spatiotemporal distribution of community types over 19 years. The predicted distributions exhibited strong seasonal changes in community types in the subarctic–subtropical boundary regions, which were consistent with previous field observations. The model also identified the long-term trends in the distribution of community types, which suggested responses to ocean warming.

Mots-clés Agrovoc : plankton surveys [EN], distribution des populations, plancton, Observation satellitaire, modélisation, zooplancton, technique de prévision, télédétection

Classification Agris : U30 - Méthodes de recherche
M40 - Écologie aquatique
L60 - Taxonomie et géographie animales

Champ stratégique Cirad : CTS 1 (2019-) - Biodiversité

Agences de financement européennes : European Research Council

Agences de financement hors UE : Kyoto University, Agence Nationale de la Recherche

Programme de financement européen : H2020

Projets sur financement : (FRA) Organisation et montée en puissance d'une Infrastructure Nationale de Génomique, (EU) Untangling eco-evolutionary impacts on diatom genomes over timescales relevant to current climate change

Auteurs et affiliations

• Kaneko Hiroto, Kyoto University (JPN)
• Endo Hisashi, Kyoto University (JPN)
• Henry Nicolas, Université Paris-Sorbonne (FRA)
• Berney Cédric, Université Paris-Sorbonne (FRA)
• Mahe Frédéric, CIRAD-BIOS-UMR PHIM (FRA) ORCID: 0000-0002-2808-0984
• Poulain Julie, CEA (FRA)
• Labadie Karine, CEA (FRA)
• Beluche Odette, CEA (FRA)
• El Hourany Roy, ULCO (FRA)
• Acinas Silvia G., Institut de Ciències del Mar (ESP)
• Babin Marcel, Université Laval (CAN)
• Bork Peer, Max Delbrück Centre for Molecular Medicine (DEU)
• Bowler Chris, IBENS (FRA)
• Cochrane Guy, EMBL (DEU)
• de Vargas Colomban, Université Paris-Sorbonne (FRA)
• Gorsky Gabriel, Sorbonne université (FRA)
• Guidi Lionel, Sorbonne université (FRA)
• Grimsley Nigel, CNRS (FRA)
• Hingamp Pascal, Université Aix-Marseille (FRA)
• Iudicone Daniele, Stazione Zoologica Anton Dohrn (ITA)
• Jaillon Olivier, CEA (FRA)
• Kandels Stefanie, EMBL (DEU)
• Karsenti Eric, EMBL (DEU)
• Not Fabrice, CNRS (FRA)
• Poulton Nicole, Bigelow Laboratory for Ocean Sciences (USA)
• Pesant Stéphane, EMBL (DEU)
• Sardet Christian, Sorbonne université (FRA)
• Speich Sabrina, UBO (FRA)
• Stemmann Lars, Sorbonne université (FRA)
• Sullivan Matthew B., Ohio State University (USA)
• Sunagawa Shinichi, Ohio State University (USA)
• Chaffron Samuel, Université de Nantes (FRA)
• Wincker Patrick, CEA (FRA)
• Nakamura Ryosuke, National Institute of Advanced Industrial Science and Technology (JPN)
• Karp-Boss Lee, Université du Maine (FRA)
• Boss Emmanuel, University of Maine (USA)
• Bowler Chris, IBENS (FRA)
• de Vargas Colomban, Université Paris-Sorbonne (FRA)
• Tomii Kentaro, National Institute of Advanced Industrial Science and Technology (JPN) - auteur correspondant
• Ogata Hiroshi Y., Kyoto University (JPN) - auteur correspondant

Source : Cirad-Agritrop (https://agritrop.cirad.fr/609606/)

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