Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates

Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to...

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Published in:Biogeosciences
Main Authors: M. Ardyna, M. Babin, M. Gosselin, E. Devred, S. Bélanger, A. Matsuoka, J.-É. Tremblay
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2013
Subjects:
Online Access:https://doi.org/10.5194/bg-10-4383-2013
https://doaj.org/article/cc8aa2a15f2e457aa2ce68bb5653c62c
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spelling ftdoajarticles:oai:doaj.org/article:cc8aa2a15f2e457aa2ce68bb5653c62c 2023-05-15T14:40:08+02:00 Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates M. Ardyna M. Babin M. Gosselin E. Devred S. Bélanger A. Matsuoka J.-É. Tremblay 2013-06-01T00:00:00Z https://doi.org/10.5194/bg-10-4383-2013 https://doaj.org/article/cc8aa2a15f2e457aa2ce68bb5653c62c EN eng Copernicus Publications http://www.biogeosciences.net/10/4383/2013/bg-10-4383-2013.pdf https://doaj.org/toc/1726-4170 https://doaj.org/toc/1726-4189 doi:10.5194/bg-10-4383-2013 1726-4170 1726-4189 https://doaj.org/article/cc8aa2a15f2e457aa2ce68bb5653c62c Biogeosciences, Vol 10, Iss 6, Pp 4383-4404 (2013) Ecology QH540-549.5 Life QH501-531 Geology QE1-996.5 article 2013 ftdoajarticles https://doi.org/10.5194/bg-10-4383-2013 2022-12-30T21:55:17Z Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to primary production (PP) are often observed. These are neither detected by ocean color sensors nor accounted for in the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e., 5206 stations) and develop an empirical model to estimate vertical chlorophyll a (Chl a ) according to (1) the shelf–offshore gradient delimited by the 50 m isobath, (2) seasonal variability along pre-bloom, post-bloom, and winter periods, and (3) regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface Chl a concentration (Chl a surf 0.7–30 mg m −3 ) throughout the open water period, the Chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when Chl a surf is low (0–0.5 mg m −3 ). By applying our empirical model to annual Chl a surf time series, instead of the conventional method assuming vertically homogenous Chl a , we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in Chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e., pre-bloom, post-bloom > 0.7 mg m −3 , and the winter period) somehow compensate for the underestimates found when SCMs are deep (i.e., post-bloom < 0.5 mg m −3 ). SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail. Article in Journal/Newspaper Arctic Arctic Ocean Phytoplankton Directory of Open Access Journals: DOAJ Articles Arctic Arctic Ocean Biogeosciences 10 6 4383 4404
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
spellingShingle Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
M. Ardyna
M. Babin
M. Gosselin
E. Devred
S. Bélanger
A. Matsuoka
J.-É. Tremblay
Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
topic_facet Ecology
QH540-549.5
Life
QH501-531
Geology
QE1-996.5
description Predicting water-column phytoplankton biomass from near-surface measurements is a common approach in biological oceanography, particularly since the advent of satellite remote sensing of ocean color (OC). In the Arctic Ocean, deep subsurface chlorophyll maxima (SCMs) that significantly contribute to primary production (PP) are often observed. These are neither detected by ocean color sensors nor accounted for in the primary production models applied to the Arctic Ocean. Here, we assemble a large database of pan-Arctic observations (i.e., 5206 stations) and develop an empirical model to estimate vertical chlorophyll a (Chl a ) according to (1) the shelf–offshore gradient delimited by the 50 m isobath, (2) seasonal variability along pre-bloom, post-bloom, and winter periods, and (3) regional differences across ten sub-Arctic and Arctic seas. Our detailed analysis of the dataset shows that, for the pre-bloom and winter periods, as well as for high surface Chl a concentration (Chl a surf 0.7–30 mg m −3 ) throughout the open water period, the Chl a maximum is mainly located at or near the surface. Deep SCMs occur chiefly during the post-bloom period when Chl a surf is low (0–0.5 mg m −3 ). By applying our empirical model to annual Chl a surf time series, instead of the conventional method assuming vertically homogenous Chl a , we produce novel pan-Arctic PP estimates and associated uncertainties. Our results show that vertical variations in Chl a have a limited impact on annual depth-integrated PP. Small overestimates found when SCMs are shallow (i.e., pre-bloom, post-bloom > 0.7 mg m −3 , and the winter period) somehow compensate for the underestimates found when SCMs are deep (i.e., post-bloom < 0.5 mg m −3 ). SCMs are, however, important seasonal features with a substantial impact on depth-integrated PP estimates, especially when surface nitrate is exhausted in the Arctic Ocean and where highly stratified and oligotrophic conditions prevail.
format Article in Journal/Newspaper
author M. Ardyna
M. Babin
M. Gosselin
E. Devred
S. Bélanger
A. Matsuoka
J.-É. Tremblay
author_facet M. Ardyna
M. Babin
M. Gosselin
E. Devred
S. Bélanger
A. Matsuoka
J.-É. Tremblay
author_sort M. Ardyna
title Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
title_short Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
title_full Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
title_fullStr Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
title_full_unstemmed Parameterization of vertical chlorophyll a in the Arctic Ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
title_sort parameterization of vertical chlorophyll a in the arctic ocean: impact of the subsurface chlorophyll maximum on regional, seasonal, and annual primary production estimates
publisher Copernicus Publications
publishDate 2013
url https://doi.org/10.5194/bg-10-4383-2013
https://doaj.org/article/cc8aa2a15f2e457aa2ce68bb5653c62c
geographic Arctic
Arctic Ocean
geographic_facet Arctic
Arctic Ocean
genre Arctic
Arctic Ocean
Phytoplankton
genre_facet Arctic
Arctic Ocean
Phytoplankton
op_source Biogeosciences, Vol 10, Iss 6, Pp 4383-4404 (2013)
op_relation http://www.biogeosciences.net/10/4383/2013/bg-10-4383-2013.pdf
https://doaj.org/toc/1726-4170
https://doaj.org/toc/1726-4189
doi:10.5194/bg-10-4383-2013
1726-4170
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op_doi https://doi.org/10.5194/bg-10-4383-2013
container_title Biogeosciences
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container_issue 6
container_start_page 4383
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