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Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean

Abstract

In the relatively unproductive waters of the tropical ocean, islands can enhance phytoplankton biomass and create hotspots of productivity and biodiversity that sustain upper trophic levels, including fish that are crucial to the survival of islands’ inhabitants. This phenomenon, termed the island mass effect 66 years ago, has been widely described. However, most studies focused on individual islands, and very few documented phytoplankton community composition. Consequently, basin-scale impacts on phytoplankton biomass, primary production and biodiversity remain largely unknown. Here we systematically identify enriched waters near islands from satellite chlorophyll concentrations (a proxy for phytoplankton biomass) to analyse the island mass effect for all tropical Pacific islands on a climatological basis. We find enrichments near 99% of islands, impacting 3% of the tropical Pacific Ocean. We quantify local and basin-scale increases in chlorophyll and primary production by contrasting island-enriched waters with nearby waters. We also reveal a significant impact on phytoplankton community structure and biodiversity that is identifiable in anomalies in the ocean colour signal. Our results suggest that, in addition to strong local biogeochemical impacts, islands may have even stronger and farther-reaching ecological impacts.

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Fig. 1: Maps of IME detection in the tropical Pacific.
Fig. 2: Maps of island impacts on PHYSAT phenoclasses.
Fig. 3: Island impacts on phytoplankton community structure as depicted by PHYSAT phenoclasses.

Data availability

The main outputs of this study, including the island database, IME and REF masks and IME impacts on Chl, primary production and PHYSAT, are available as a dataset hosted on Zenodo65. The PHYSAT climatology calculated for this paper is available there as well. PHYSAT is now being processed by ACRI (https://www.acri-st.fr/) and PHYSAT data will soon be publicly available from their website. Other data that support the findings of this study are available in various public repositories: https://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMH1chlamday.html (MODIS Chl), http://orca.science.oregonstate.edu/2160.by.4320.monthly.hdf.vgpm.m.chl.m.sst.php (MODIS primary production), https://www.ngdc.noaa.gov/mgg/shorelines/gshhs.html (GSHHG coastline), https://www.gebco.net/data_and_products/gridded_bathymetry_data/ (GEBCO bathymetry). The island database from Nunn et al.52 is available as Additional file 1 at https://doi.org/10.1186/s40562-016-0041-8.

Code availability

The IME detection algorithm, along with datasets and example code to reproduce Fig. 1, Extended Data Fig. 1 and parts of Table 1, is available at https://github.com/messiem/toolbox_IME_detection and the corresponding release is available via Zenodo66.

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Acknowledgements

M.M. was funded by the European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement SAPPHIRE no. 746530, and by the David and Lucile Packard Foundation. The project leading to this publication has received funding from European FEDER Fund under project no. 1166-39417 (M.M., A.P. and A.D.). We thank A.-H. Rêve-Lamarche and D. Dessailly for their help with extracting and using the PHYSAT outputs, and E. Pape for useful comments and text edits.

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Authors and Affiliations

Authors

Contributions

M.M. conceived and designed the study, with input from A.P., A.D. and S.A. M.M. developed the IME algorithm with feedback from A.P. and A.D., performed the data analyses and led the interpretation and writing. S.A. provided the PHYSAT outputs. A.P., A.D., E.M. and S.A. provided substantial input on the text, and contributed to discussions that shaped the study and the manuscript.

Corresponding author

Correspondence to Monique Messié.

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Nature Geoscience thanks Jamison Gove and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Kyle Frischkorn and Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Example maps of IME and reference (REF) region detection.

Two contrasting months are shown for the Fiji/Tonga region: a) August (small IMEs but higher climatological enrichment across the region), and b) December (strong IMEs, with IMEs from the Fiji and Tonga island groups merging). Reference regions (blue) exclude IME regions from any island.

Extended Data Fig. 2 IME maps for different climatological months.

For each month, IME regions are contoured in different shades of red depending on Chl increase near islands relative to a reference region (similar to Fig. 1).

Extended Data Fig. 3 PHYSAT phenoclass richness vs Chl across IME and REF regions.

Phenoclass richness was normalized to 100 data points, and only regions with at least 100 PHYSAT data points were included.

Extended Data Fig. 4 Example of random permutation used to remove the Chl signal on the phenoclass richness increase observed in IME regions.

Top panel: identical to Fig. 3b left panels (that is, including all IME and REF regions); both Chl (left) and phenoclass richness (right) are significantly higher in IME than in REF regions (Mann-Whitney U-test). Bottom panel: example of a random permutation where 2/3 of the IME and REF regions were retained such that the Chl distributions do not significantly differ anymore. In this permutation, phenoclass richness remains significantly higher within the IME subset (right) even though Chl is (non-significantly) lower (left).

Extended Data Table 1 Additional metrics for IME impacts in the tropical Pacific (see Table 1)

Supplementary information

Supplementary Information

Supplementary Figs. 1–3 and Tables 1 and 2.

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Messié, M., Petrenko, A., Doglioli, A.M. et al. Basin-scale biogeochemical and ecological impacts of islands in the tropical Pacific Ocean. Nat. Geosci. 15, 469–474 (2022). https://doi.org/10.1038/s41561-022-00957-8

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