Articles | Volume 14, issue 18
Biogeosciences, 14, 4125–4159, 2017
https://doi.org/10.5194/bg-14-4125-2017
Biogeosciences, 14, 4125–4159, 2017
https://doi.org/10.5194/bg-14-4125-2017

Research article 21 Sep 2017

Research article | 21 Sep 2017

Inverse-model estimates of the ocean's coupled phosphorus, silicon, and iron cycles

Benoît Pasquier and Mark Holzer

Data sets

World Ocean Database 2013, NOAA Atlas NESDIS 72 Boyer, T.P., J. I. Antonov, O. K. Baranova, C. Coleman, H. E. Garcia, A. Grodsky, D. R. Johnson, R. A. Locarnini, A. V. Mishonov, T.D. O'Brien, C.R. Paver, J.R. Reagan, D. Seidov, I. V. Smolyar, and M. M. Zweng https://doi.org/10.7289/V5NZ85MT

The GEOTRACES Intermediate Data Product 2014 Mawji, E., et al. https://doi.org/10.1016/j.marchem.2015.04.005

Size-partitioned phytoplankton carbon concentrations retrieved from ocean color data, links to data in NetCDF format Kostadinov, Tihomir S; Milutinovic, Svetlana; Marinov, Irina; Cabré, Anna https://doi.org/10.1594/PANGAEA.859005

Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group https://doi.org/10.5067/AQUA/MODIS_OC.2014.0

Download
Short summary
We construct a model of the ocean's coupled phosphorus, silicon, and iron cycles and optimize its biogeochemical parameters. State estimates for widely differing iron sources are consistent with observations because of compensation between sources and sinks. Export production and the patterns of export supported by each iron source type (aeolian, sedimentary, hydrothermal) are well constrained. The fraction of export supported by each iron type varies systematically with its fractional source.
Altmetrics
Final-revised paper
Preprint