Constraining Global Marine Iron Sources and Ligand‐Mediated Scavenging Fluxes With GEOTRACES Dissolved Iron Measurements in an Ocean Biogeochemical Model. Issue 8 (9th August 2021)

• Record Type: Journal Article
• Authors: Somes, Christopher J.; Dale, Andrew W.; Wallmann, Klaus; Scholz, Florian; Yao, Wanxuan; Oschlies, Andreas; Muglia, Juan; Schmittner, Andreas; Achterberg, Eric P.
• Is Part Of: Global biogeochemical cycles. Volume 35:Issue 8(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-08-09
• Subjects: ocean -- iron -- model -- residence time -- scavenging -- ligand; Biogeochemical cycles -- Periodicals; Electronic journals; 577.1405
• DOI: 10.1029/2021GB006948
• Languages: English
• ISSNs: 0886-6236

Abstract

Abstract: Iron is a key micronutrient controlling phytoplankton growth in vast regions of the global ocean. Despite its importance, uncertainties remain high regarding external iron source fluxes and internal cycling on a global scale. In this study, we used a global dissolved iron data set, including GEOTRACES measurements, to constrain source and scavenging fluxes in the marine iron component of a global ocean biogeochemical model. Our model simulations tested three key uncertainties: source inputs of atmospheric soluble iron deposition (varying from 1.4 to 3.4 Gmol/yr), reductive sedimentary iron release (14–117 Gmol/yr), and compared a variable ligand parameterization to a constant distribution. In each simulation, scavenging rates were tuned to reproduce the observed global mean iron inventory for consistency. The variable ligand parameterization improved the global model‐data misfit the most, suggesting that heterotrophic bacteria are an important source of ligands to the ocean. Model simulations containing high source fluxes of atmospheric soluble iron deposition (3.4 Gmol/yr) and reductive sedimentary iron release (114 Gmol/yr) further improved the model most notably in the surface ocean. High scavenging rates were then required to maintain the iron inventory resulting in relatively short surface and global ocean residence times of 0.83 and 7.5 years, respectively. The model simulates a tight spatial coupling between source inputs and scavenging rates, which may be too strong due to underrepresented ligands near source inputs, contributing to large uncertainties when constraining individual fluxes with dissolved iron concentrations. Model biases remain high and are discussed to help improve global marine iron cycle models. Key Points: Global marine iron model tests varying levels of atmospheric deposition, sedimentary release, ligand distributions, and scavenging rates Simulations that best reproduce observations include variable ligands and high rates of atmospheric deposition and sedimentary release Simulations with high iron sources require high scavenging rates resulting in short residence times