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Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis

Gotzon Basterretxea; Joan S. Font-Muñoz; Ismael Hernández-Carrasco; Sergio A. Sañudo-Wilhelmy
Ocean Science · Vol. 19, Issue 4 · pp. 973-990 · 2023

Abstract

We examine 20 years of monthly global ocean color data and modeling outputs of nutrients using self-organizing map (SOM) analysis to identify characteristic spatial and temporal patterns of high-nutrient low-chlorophyll (HNLC) regions and their association with different climate modes. The global nitrate-to-chlorophyll ratio threshold of NO3 : Chl > 17 (mmol NO3 mg Chl−1) is estimated to be a good indicator of the distribution limit of this unproductive biome that, on average, covers 92 × 106 km2 (∼ 25 % of the ocean). The trends in satellite-derived surface chlorophyll (0.6 ± 0.4 % yr−1 to 2 ± 0.4 % yr−1) suggest that HNLC regions in polar and subpolar areas have experienced an increase in phytoplankton biomass over the last decades, but much of this variation, particularly in the Southern Ocean, is produced by a climate-driven transition in 2009–2010. Indeed, since 2010, the extent of the HNLC zones has decreased at the poles (up to 8 %) and slightly increased at the Equator (

Bibliographic Information

JournalOcean Science
PublisherCopernicus Publications / European Geosciences Union
Publication Date2023-07-06
Publication Year2023
Volume19
Issue4
Pages973-990
Document TypeJournal Article
Print ISSN1812-0784
eISSN1812-0792
DOI10.5194/os-19-973-2023
SubjectOceanography; physical oceanography; chemical oceanography; biogeochemistry; ocean modelling

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NARA Access CoverageOA / free full text
Journal Homepagehttps://www.ocean-science.net/
Publisher PageOpen Publisher Page
This article is openly available from the publisher.