FN Archimer Export Format
PT J
TI Multi-model remote sensing assessment of primary production in the subtropical gyres
BT 
AF Regaudie-de-Gioux, Aurore
   Huete-Ortega, M.
   Sobrino, C.
   López-Sandoval, D.C.
   González, N.
   Fernández-Carrera, A.
   Vidal, M
   Marañón, E.
   Cermeño, P.
   Latasa, M.
   Agustí, S.
   Duarte, C.M.
AS 1:1;2:2,3;3:3;4:4;5:5;6:3;7:6;8:3;9:7;10:8;11:1,4;12:1,4;
FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;10:;11:;12:;
C1 Mediterranean Institute for Advanced Studies (IMEDEA), Calle Miquel Marques 21, 07190 Esporles, Spain
   Oroboros Instruments, Schöpfstraße 8, 6020 Innsbruck, Austria
   Departamento de Ecología y Biología Animal, Universidade de Vigo, 36310 Vigo, Spain
   King Abdullah University of Science and Technology (KAUST), Red Sea Research Center (RSRC), Thuwal 23955-6900, Saudi Arabia
   Area de Biodiversidad y Conservación, ESCET, Universidad Rey Juan Carlos, Tulipán s/n., Móstoles 28933, Madrid, Spain
   Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Universitat de Barcelona, Diagonal, 643, 08028 Barcelona, Spain
   Institute of Marine Sciences (ICM-CSIC), Passeig Marítim de la Barceloneta, 37–49, 08003 Barcelona, Spain
   Spanish Institute of Oceanography, Avda. Principe de Asturias 70bis, 33212 Gijón, Spain
C2 IMEDEA, SPAIN
   OROBOROS INSTRUMENTS, AUSTRIA
   UNIV VIGO, SPAIN
   UNIV KING ABDULLAH, SAUDI ARABIA
   UNIV REY JUAN CARLOS, SPAIN
   UNIV BARCELONA, SPAIN
   ICM CSIC, SPAIN
   IEO, SPAIN
IF 2.528
TC 10
UR https://archimer.ifremer.fr/doc/00487/59843/62992.pdf
LA English
DT Article
DE ;Primary production;Remote PP model;Skills;Subtropical gyre
AB The subtropical gyres occupy about 70% of the ocean surface. While primary production (PP) within these oligotrophic regions is relatively low, their extension makes their total contribution to ocean productivity significant. Monitoring marine pelagic primary production across broad spatial scales, particularly across the subtropical gyre regions, is challenging but essential to evaluate the oceanic carbon budget. PP in the ocean can be derived from remote sensing however in situ depth-integrated PP (IPPis) measurements required for validation are scarce from the subtropical gyres. In this study, we collected >120 IPPis measurements from both northern and southern subtropical gyres that we compared to commonly used primary productivity models (the Vertically Generalized Production Model, VGPM and six variants; the Eppley-Square-Root model, ESQRT; the Howard–Yoder–Ryan model, HYR; the model of MARRA, MARRA; and the Carbon-based Production Model, CbPM) to predict remote PP (PPr) in the subtropical regions and explored possibilities for improving PP prediction. Our results showed that satellite-derived PP (IPPsat) estimates obtained from the VGPM1, MARRA and ESQRT provided closer values to the IPPis (i.e., the difference between the mean of the IPPsat and IPPis was closer to 0; |Bias| ~ 0.09). Model performance varied due to differences in satellite predictions of in situ parameters such as chlorophyll a (chl-a) concentration or the optimal assimilation efficiency of the productivity profile (PBopt) in the subtropical region. In general, model performance was better for areas showing higher IPPis, highlighting the challenge of PP prediction in the most oligotrophic areas (i.e. PP < 300 mg C m−2 d−1). The use of in situ chl-a data, and PBopt as a function of sea surface temperature (SST) and the mixed layer depth (MLD) from gliders and floats in PPr models would improve their IPP predictions considerably in oligotrophic oceanic regions such as the subtropical gyres where MLD is relatively low (<60 m) and cloudiness may bias satellite input data. 
PY 2019
PD AUG
SO Journal Of Marine Systems
SN 0924-7963
PU Elsevier BV
VL 196
UT 000472689700008
BP 97
EP 106
DI 10.1016/j.jmarsys.2019.03.007
ID 59843
ER

EF