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

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 ni...

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Published in:Ocean Science
Main Authors: G. Basterretxea, J. S. Font-Muñoz, I. Hernández-Carrasco, S. A. Sañudo-Wilhelmy
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2023
Subjects:
G
Online Access:https://doi.org/10.5194/os-19-973-2023
https://doaj.org/article/4231e8bb9f334f4cb96836ded22d790d
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spelling ftdoajarticles:oai:doaj.org/article:4231e8bb9f334f4cb96836ded22d790d 2023-07-30T04:07:03+02:00 Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis G. Basterretxea J. S. Font-Muñoz I. Hernández-Carrasco S. A. Sañudo-Wilhelmy 2023-07-01T00:00:00Z https://doi.org/10.5194/os-19-973-2023 https://doaj.org/article/4231e8bb9f334f4cb96836ded22d790d EN eng Copernicus Publications https://os.copernicus.org/articles/19/973/2023/os-19-973-2023.pdf https://doaj.org/toc/1812-0784 https://doaj.org/toc/1812-0792 doi:10.5194/os-19-973-2023 1812-0784 1812-0792 https://doaj.org/article/4231e8bb9f334f4cb96836ded22d790d Ocean Science, Vol 19, Pp 973-990 (2023) Geography. Anthropology. Recreation G Environmental sciences GE1-350 article 2023 ftdoajarticles https://doi.org/10.5194/os-19-973-2023 2023-07-09T00:34:21Z 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 NO 3 : Chl > 17 (mmol NO 3 mg Chl −1 ) is estimated to be a good indicator of the distribution limit of this unproductive biome that, on average, covers 92 × 10 6 km 2 ( ∼ 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 ( < 0.5 %). Our study finds that chlorophyll variations in HNLC regions respond to major climate variability signals such as the El Niño–Southern Oscillation (ENSO) and Meridional Overturning Circulation (MOC) at both short (2–4 years) and long (decadal) timescales. These results suggest global coupling in the functioning of distant biogeochemical regions. Article in Journal/Newspaper Southern Ocean Directory of Open Access Journals: DOAJ Articles Southern Ocean Ocean Science 19 4 973 990
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Geography. Anthropology. Recreation
G
Environmental sciences
GE1-350
spellingShingle Geography. Anthropology. Recreation
G
Environmental sciences
GE1-350
G. Basterretxea
J. S. Font-Muñoz
I. Hernández-Carrasco
S. A. Sañudo-Wilhelmy
Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
topic_facet Geography. Anthropology. Recreation
G
Environmental sciences
GE1-350
description 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 NO 3 : Chl > 17 (mmol NO 3 mg Chl −1 ) is estimated to be a good indicator of the distribution limit of this unproductive biome that, on average, covers 92 × 10 6 km 2 ( ∼ 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 ( < 0.5 %). Our study finds that chlorophyll variations in HNLC regions respond to major climate variability signals such as the El Niño–Southern Oscillation (ENSO) and Meridional Overturning Circulation (MOC) at both short (2–4 years) and long (decadal) timescales. These results suggest global coupling in the functioning of distant biogeochemical regions.
format Article in Journal/Newspaper
author G. Basterretxea
J. S. Font-Muñoz
I. Hernández-Carrasco
S. A. Sañudo-Wilhelmy
author_facet G. Basterretxea
J. S. Font-Muñoz
I. Hernández-Carrasco
S. A. Sañudo-Wilhelmy
author_sort G. Basterretxea
title Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
title_short Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
title_full Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
title_fullStr Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
title_full_unstemmed Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
title_sort global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis
publisher Copernicus Publications
publishDate 2023
url https://doi.org/10.5194/os-19-973-2023
https://doaj.org/article/4231e8bb9f334f4cb96836ded22d790d
geographic Southern Ocean
geographic_facet Southern Ocean
genre Southern Ocean
genre_facet Southern Ocean
op_source Ocean Science, Vol 19, Pp 973-990 (2023)
op_relation https://os.copernicus.org/articles/19/973/2023/os-19-973-2023.pdf
https://doaj.org/toc/1812-0784
https://doaj.org/toc/1812-0792
doi:10.5194/os-19-973-2023
1812-0784
1812-0792
https://doaj.org/article/4231e8bb9f334f4cb96836ded22d790d
op_doi https://doi.org/10.5194/os-19-973-2023
container_title Ocean Science
container_volume 19
container_issue 4
container_start_page 973
op_container_end_page 990
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