FN Archimer Export Format
PT J
TI Global estimates of marine gross primary production based on machine‐learning upscaling of field observations
BT 
AF Huang, Yibin
   Nicholson, David
   Huang, Bangquin
   Cassar, Nicolas
AS 1:1,2,3;2:4;3:2,3;4:1,5;
FF 1:;2:;3:;4:;
C1 Division of Earth and Ocean Sciences, Nicholas School of the Environment, Duke University, Durham, USA
   State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
   Fujian Provincial Key Laboratory of Coastal Ecology and Environmental Studies, Xiamen University, Xiamen, China
   Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, Massachusetts, USA
   Laboratoire des Sciences de l'Environnement Marin (LEMAR), UMR, UBO/CNRS/IRD/IFREMER, Institut Universitaire Européen de la Mer (IUEM), 6539 Brest, France
C2 UNIV DUKE, USA
   UNIV XIAMEN, CHINA
   UNIV XIAMEN, CHINA
   WHOI, USA
   UBO, FRANCE
UM LEMAR
IN WOS Cotutelle UMR
   copubli-int-hors-europe
   copubli-sud
IF 6.5
TC 19
UR https://archimer.ifremer.fr/doc/00668/77995/80215.pdf
LA English
DT Article
AB Approximately half of global primary production occurs in the oceans. While the large‐scale variability in net primary production (NPP) has been extensively studied, ocean gross primary production (GPP) has thus far received less attention. In this study, we derived two satellite‐based GPP models by training machine‐learning algorithm (Random Forest) with light‐dark bottle incubations (GPPLD) and the triple isotopes of dissolved oxygen (GPP17Δ). The two algorithms predict global GPPs of 9.2 ± 1.3 * 1015 and 15.1 ± 1.05 * 1015 mol O2 yr‐1 for GPPLD and GPP17Δ, respectively. The projected GPP distributions in agreement with our understanding of the mechanisms regulating primary production. Global GPP17Δ was higher than GPPLD by an average factor of 1.6 which varied meridionally. The discrepancy between GPP17Δ and GPPLD simulations can be partly explained by the known biases of each methodology. After accounting for some of these biases, the GPP17Δ and GPPLD converge to 9.5∼12.6 *1015 mol O2 yr‐1, equivalent to 103∼150 Pg C yr‐1. Our results suggest that global oceanic GPP is 1.5‐2.2 fold larger than oceanic NPP and comparable to GPP on land. 
PY 2021
PD MAR
SO Global Biogeochemical Cycles
SN 0886-6236
PU American Geophysical Union
VL 35
IS 3
UT 000635221000009
DI 10.1029/2020GB006718
ID 77995
ER

EF