Abstract
Marine plankton form complex communities of interacting organisms at the base of the food web, which sustain oceanic biogeochemical cycles and help regulate climate. Although global surveys are starting to reveal ecological drivers underlying planktonic community structure and predicted climate change responses, it is unclear how community-scale species interactions will be affected by climate change. Here, we leveraged $\textit{Tara}$ Oceans sampling to infer a global ocean cross-domain plankton co-occurrence network-the community interactome-and used niche modeling to assess its vulnerabilities to environmental change. Globally, this revealed a plankton interactome self-organized latitudinally into marine biomes (Trades, Westerlies, Polar) and more connected poleward. Integrated niche modeling revealed biome-specific community interactome responses to environmental change and forecasted the most affected lineages for each community. These results provide baseline approaches to assess community structure and organismal interactions under climate scenarios while identifying plausible plankton bioindicators for ocean monitoring of climate change.
Original language | English (US) |
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Pages (from-to) | eabg1921 |
Journal | Science advances |
Volume | 7 |
Issue number | 35 |
DOIs | |
State | Published - Aug 28 2021 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2021-09-16Acknowledgements: Tara Oceans (which includes both the Tara Oceans and Tara Oceans Polar Circle expeditions) would not exist without the leadership of the Tara Ocean Foundation and the continuous support of 23 institutes (http://oceans.taraexpeditions.org). Funding: We further thank the commitment of the following sponsors: CNRS (in particular Groupement de Recherche GDR3280 and the Research Federation for the study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans-GOSEE), European Molecular Biology Laboratory (EMBL), Genoscope/CEA, the French Ministry of Research, the French Government “Investissements d’Avenir” programmes OCEANOMICS (ANR-11-BTBR-0008), FRANCE GENOMIQUE (ANR-10-INBS-09-08), MEMO LIFE (ANR-10-LABX-54), PSL* Research University (ANR-11-IDEX-0001-02), ETH and the Helmut Horten Foundation, MEXT/JSPS/KAKENHI (projects 16H06429, 16K21723, 16H06437, and 18H02279), the Spanish Ministry of Economy and Competitiveness (project MAGGY—CTM2017-87736-R), ERC Advanced Award Diatomic (grant agreement 835067 to CB), the CNRS MITI through the interdisciplinary program Modélisation du Vivant (GOBITMAP grant to SC), and the H2020 European Commission project AtlantECO (award number 862923). We also thank the support and commitment of Agnès b. and Etienne Bourgois, the Prince Albert II de Monaco Foundation, the Veolia Foundation, Region Bretagne, Lorient Agglomeration, Serge Ferrari, World Courier, and KAUST. The global sampling effort was enabled by countless scientists and crew who sampled aboard the Tara from 2009 to 2013, and we thank MERCATOR-CORIOLIS and ACRI-ST for providing daily satellite data during the expedition. E.D. is supported by the RFI ATLANSTIC2020 grant (PROBIOSTIC grant to DE). M.Bu. received financial support from the French Facility for Global Environment (FFEM) as part of the “Ocean Plankton, Climate and Development” project. P.C.J. was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP (PhD grant 2017/26786-1). H.S. is supported by a Brazilian Research Council (CNPq) productivity grant (process 309514/2017-7) and FAPESP (grant 2014/14139-3). We are also grateful to the countries who graciously granted sampling permissions. Computational support was provided by the bioinformatics core facility of Nantes (BiRD, Biogenouest), University of Nantes, France. The authors declare that all data reported here are fully and freely available from the date of publication, with no restrictions, and that all of the analyses, publications, and ownership of data are free from legal entanglement or restriction by the various nations whose waters the Tara Oceans expeditions sampled in. This article is contribution number 120 of Tara Oceans. Additional funding from the Natural Sciences and Engineering Council (NSERC) Canada Discovery program is gratefully acknowledged. Author contributions: S.C. designed the study. S.C., E.D., M.B., D.V., and N.H. performed the experiments. S.C., E.D., M.B., D.V., and N.H. analyzed the data. S.C., E.D., and D.V. performed the simulations. S.C., E.D., and D.E. wrote the paper, with input from M.B.S. and C.B., as well as all authors. Competing interests: The authors declare that they have no competing interests. Data and materials availability: Data described here are available at the EBI under the project identifiers PRJEB402 and PRJEB7988 and at PANGAEA (96). All data (raw abundance matrices and interactome graphML files) needed to evaluate the conclusions of the paper are available in the Supplementary Materials. A web server for exploring and searching the global ocean interactome is available at https://saas.ls2n.fr/Tara-Oceans-interactome/
This publication acknowledges KAUST support, but has no KAUST affiliated authors.