Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data

Regional relationships to estimate the main Phytoplankton Functional Types (PFTs) and Size Classes (PSCs) from satellite data are presented. Following the abundance-based approach and selecting the Total Chlorophyll a (TChla) as descriptor of the trophic status of the environment, empirical relation...

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Main Authors: Annalisa Di Cicco, Michela Sammartino, Salvatore Marullo, Rosalia Santoleri
Format: Article
Language:English
Published: Frontiers Media S.A. 2017-05-01
Series:Frontiers in Marine Science
Subjects:
Online Access:http://journal.frontiersin.org/article/10.3389/fmars.2017.00126/full
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spelling doaj-e84120d0164c4c2abc58879190627d0d2020-11-24T21:21:47ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452017-05-01410.3389/fmars.2017.00126254855Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite DataAnnalisa Di Cicco0Michela Sammartino1Salvatore Marullo2Salvatore Marullo3Rosalia Santoleri4Institute of Atmospheric Sciences and Climate, National Research Council (CNR)Rome, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council (CNR)Rome, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council (CNR)Rome, ItalyNational Agency for New Technologies, Energy and Sustainable Economic DevelopmentFrascati, ItalyInstitute of Atmospheric Sciences and Climate, National Research Council (CNR)Rome, ItalyRegional relationships to estimate the main Phytoplankton Functional Types (PFTs) and Size Classes (PSCs) from satellite data are presented. Following the abundance-based approach and selecting the Total Chlorophyll a (TChla) as descriptor of the trophic status of the environment, empirical relations between the TChla concentration and seven accessory pigments, marker for the main algal groups, have been developed for the Mediterranean Sea. Using only in-situ data acquired in this basin, firstly a previous regional diagnostic pigment analysis has been conducted to evaluate the specific pigment ratios featuring the phytoplankton assemblage that occurs in the Mediterranean Sea. Secondly, the new regional PFT and PSC algorithms have been calibrated and validated on the in-situ dataset. The statistical analysis showed a very good predictive power for all the new regional models. A quantitative comparison with global abundance-based models applied to our validation dataset showed that the regionalization improves the uncertainty and the spread of about one order of magnitude for all the classes (e.g., in the nano class, where the mean bias error improves from −0.056 to 0.001 mg m−3). These results highlighted that a regionalization for the PSC and PFT estimates are required, to take into account the peculiar bio-optical properties of the Mediterranean Sea. Finally, the new regional equations have been applied to the Mediterranean TChla satellite (1998–2015) time series to estimate annual and monthly PFT and PSC climatology. The analysis of the climatological maps, relative to the phytoplankton assemblage distribution patterns, reveals that all the three size classes reach their maxima in the higher nutrient areas, with absolute values >3 mg m−3 of TChla for micro-, and about 1.6 and 0.4 mg m−3 for nano- and pico-phytoplankton, respectively. Moreover, the nano component shows intermediate percentage values in the whole basin, ranging from 30 to 40% of the TChla in the western basin, up to 45% in the more productive areas. In terms of chlorophyll concentration, in the coastal areas we find the predominance of the Diatoms and Haptophytes, while in the ultra-oligotrophic waters Prokaryotes predominates on the other groups, constituting the principal component of the pico-phytoplankton.http://journal.frontiersin.org/article/10.3389/fmars.2017.00126/fullPFTsPSCsMediterranean Searegional algorithmsocean color
collection DOAJ
language English
format Article
sources DOAJ
author Annalisa Di Cicco
Michela Sammartino
Salvatore Marullo
Salvatore Marullo
Rosalia Santoleri
spellingShingle Annalisa Di Cicco
Michela Sammartino
Salvatore Marullo
Salvatore Marullo
Rosalia Santoleri
Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data
Frontiers in Marine Science
PFTs
PSCs
Mediterranean Sea
regional algorithms
ocean color
author_facet Annalisa Di Cicco
Michela Sammartino
Salvatore Marullo
Salvatore Marullo
Rosalia Santoleri
author_sort Annalisa Di Cicco
title Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data
title_short Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data
title_full Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data
title_fullStr Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data
title_full_unstemmed Regional Empirical Algorithms for an Improved Identification of Phytoplankton Functional Types and Size Classes in the Mediterranean Sea Using Satellite Data
title_sort regional empirical algorithms for an improved identification of phytoplankton functional types and size classes in the mediterranean sea using satellite data
publisher Frontiers Media S.A.
series Frontiers in Marine Science
issn 2296-7745
publishDate 2017-05-01
description Regional relationships to estimate the main Phytoplankton Functional Types (PFTs) and Size Classes (PSCs) from satellite data are presented. Following the abundance-based approach and selecting the Total Chlorophyll a (TChla) as descriptor of the trophic status of the environment, empirical relations between the TChla concentration and seven accessory pigments, marker for the main algal groups, have been developed for the Mediterranean Sea. Using only in-situ data acquired in this basin, firstly a previous regional diagnostic pigment analysis has been conducted to evaluate the specific pigment ratios featuring the phytoplankton assemblage that occurs in the Mediterranean Sea. Secondly, the new regional PFT and PSC algorithms have been calibrated and validated on the in-situ dataset. The statistical analysis showed a very good predictive power for all the new regional models. A quantitative comparison with global abundance-based models applied to our validation dataset showed that the regionalization improves the uncertainty and the spread of about one order of magnitude for all the classes (e.g., in the nano class, where the mean bias error improves from −0.056 to 0.001 mg m−3). These results highlighted that a regionalization for the PSC and PFT estimates are required, to take into account the peculiar bio-optical properties of the Mediterranean Sea. Finally, the new regional equations have been applied to the Mediterranean TChla satellite (1998–2015) time series to estimate annual and monthly PFT and PSC climatology. The analysis of the climatological maps, relative to the phytoplankton assemblage distribution patterns, reveals that all the three size classes reach their maxima in the higher nutrient areas, with absolute values >3 mg m−3 of TChla for micro-, and about 1.6 and 0.4 mg m−3 for nano- and pico-phytoplankton, respectively. Moreover, the nano component shows intermediate percentage values in the whole basin, ranging from 30 to 40% of the TChla in the western basin, up to 45% in the more productive areas. In terms of chlorophyll concentration, in the coastal areas we find the predominance of the Diatoms and Haptophytes, while in the ultra-oligotrophic waters Prokaryotes predominates on the other groups, constituting the principal component of the pico-phytoplankton.
topic PFTs
PSCs
Mediterranean Sea
regional algorithms
ocean color
url http://journal.frontiersin.org/article/10.3389/fmars.2017.00126/full
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