FN Archimer Export Format
PT J
TI Global Retrieval of Diatom Abundance Based on Phytoplankton Pigments and Satellite Data
BT 
AF SOPPA, Mariana A.
   HIRATA, Takafumi
   SILVA, Brenner
   DINTER, Tilman
   PEEKEN, Ilka
   WIEGMANN, Sonja
   BRACHER, Astrid
AS 1:1;2:2,3;3:4;4:1,5;5:1,6;6:1;7:1,5;
FF 1:;2:;3:;4:;5:;6:;7:;
C1 Helmholtz Ctr Polar & Marine Res, Alfred Wegener Inst, D-27570 Bremerhaven, Germany.
   Hokkaido Univ, Fac Environm Earth Sci, Kita Ku, Sapporo, Hokkaido 0600810, Japan.
   Japan Sci & Technol Agcy, CREST, Kita Ku, Sapporo, Hokkaido 0600810, Japan.
   Univ Marburg, Lab Climatol & Remote Sensing, D-35037 Marburg, Germany.
   Univ Bremen, Inst Environm Phys, D-28359 Bremen, Germany.
   MARUM Ctr Marine Environm Sci, D-28359 Bremen, Germany.
C2 INST A WEGENER, GERMANY
   UNIV HOKKAIDO, JAPAN
   JAPAN SCI TECH, JAPAN
   UNIV MARBURG, GERMANY
   UNIV BREMEN, GERMANY
   MARUM CTR MARINE ENVIRONM SCI, GERMANY
IN DOAJ
IF 3.18
TC 38
UR https://archimer.ifremer.fr/doc/00290/40075/39289.pdf
   https://archimer.ifremer.fr/doc/00290/40075/39290.pdf
LA English
DT Article
CR MD 145 / KEOPS
   MD 166 / BONUS-GOODHOPE
   MD 188 / KEOPS 2
   VT /  KEOPS 2006
   VT 125 / KEOPS2_MOOR
   VT 86 / KEOPS
BO Marion Dufresne
DE ;ocean colour;phytoplankton functional types;diatom;remote sensing;chlorophyll-a
AB Diatoms are the major marine primary producers on the global scale and, recently, several methods have been developed to retrieve their abundance or dominance from satellite remote sensing data. In this work, we highlight the importance of the Southern Ocean (SO) in developing a global algorithm for diatom using an Abundance Based Approach (ABA). A large global in situ data set of phytoplankton pigments was compiled, particularly with more samples collected in the SO. We revised the ABA to take account of the information on the penetration depth (Z(pd)) and to improve the relationship between diatoms and total chlorophyll-a (TChla). The results showed that there is a distinct relationship between diatoms and TChla in the SO, and a new global model (ABA(Zpd)) improved the estimation of diatoms abundance by 28% in the SO compared with the original ABA model. In addition, we developed a regional model for the SO which further improved the retrieval of diatoms by 17% compared with the global ABA(Zpd) model. As a result, we found that diatom may be more abundant in the SO than previously thought. Linear trend analysis of diatom abundance using the regional model for the SO showed that there are statistically significant trends, both increasing and decreasing, in diatom abundance over the past eleven years in the region.
PY 2014
PD OCT
SO Remote Sensing
SN 2072-4292
PU Mdpi Ag
VL 6
IS 10
UT 000344458000042
BP 10089
EP 10106
DI 10.3390/rs61010089
ID 40075
ER

EF