FN Archimer Export Format
PT J
TI Reproduction of Spatio-Temporal Patterns of Major Mediterranean Phytoplankton Groups from Remote Sensing OC-CCI Data
BT 
AF NAVARRO, Gabriel
   ALMARAZ, Pablo
   CABALLERO, Isabel
   VAZQUEZ, Agueda
   HUERTAS, Isabel E.
AS 1:1;2:1;3:1;4:2;5:1;
FF 1:;2:;3:;4:;5:;
C1 CSIC, Inst Marine Sci Andalusia, Dept Ecol & Coastal Management, Puerto Real, Spain.
   Univ Cadiz, Higher Engn Sch, Dept Appl Phys, Puerto Real, Spain.
C2 CSIC, SPAIN
   UNIV CADIZ, SPAIN
IF 5.247
TC 8
UR https://archimer.ifremer.fr/doc/00589/70148/68133.pdf
   https://archimer.ifremer.fr/doc/00589/70148/68134.xlsx
LA English
DT Article
CR BOUSSOLE
DE ;PHYSAT-Med algorithm;OC-CCI database;phytoplankton functional types;Mediterranean Sea;wavelet analysis
AB During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT-Med, was developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows the detection from ocean color images of the dominant Mediterranean phytoplankton groups, namely nanoeukaryotes, Prochlorococcus. Synechococcus, diatoms, coccolithophorids, and Phaeocystis-like phytoplankton. Here, we present a new version of PHYSAT-Med applied to the Ocean Colour Climate Change Initiative (OC-CCI) database. The OC-CCI database consists of a multi-sensor, global ocean-color product that merges observations from four different sensors. This retuned version presents improvements with respect to the previous version, as it increases the temporal range (since 1998), decreases the cloud cover, improves the bias correction and a validation exercise was performed in the NW Mediterranean Sea. In particular, the PHYSAT-Med version has been used here to analyse the annual cycles of the major phytoplankton groups in the Mediterranean Sea. Wavelet analyses were used to explore the spatial variability in dominance both in the time and frequency domains in several Mediterranean sub-regions, such as the Alboran Sea, Ligurian Sea, Northern Adriatic Sea, and Levantine basin. Results extended the interpretation of previously detected patterns, indicating the dominance of Synechococcus-like vs. prochlorophytes throughout the year at the basin level, and the predominance of nanoeukaryotes during the winter months. The method successfully reproduced the diatom blooms normally detected in the basin during the spring season (March to April), especially in the Adriatic Sea. According to our results, the PHYSAT-Med OC-CCI algorithm represents a useful tool for the spatio-temporal monitoring of dominant phytoplankton groups in Mediterranean surface waters. The successful applications of other regional ocean color algorithms to the OC-CCI database will give rise to extended time series of phytoplankton functional types, with promising applications to the study of long-term oceanographic trends in a global change context. 
PY 2017
SO Frontiers In Marine Science
SN 2296-7745
PU Frontiers Media Sa
VL 4
IS 246
UT 000457690600244
DI 10.3389/fmars.2017.00246
ID 70148
ER

EF