A key question about the iron cycle is how much export is supported by the different iron sources (aeolian, sedimentary, and hydrothermal). Previous studies shut down a given source to quantify its importance, but this approach cannot quantify the source’s contribution to export in the unperturbed state because of the system’s nonlinearities. Moreover, such studies used forward models that were not objectively data constrained.
Here, we estimate the ocean’s steady-state coupled phosphorus, silicon, and iron cycles using a new inverse model embedded in a data-assimilated circulation. The model features the redissolution of scavenged iron, a subgrid topography parameterization, and three phytoplankton functional classes. Phytoplankton concentrations are represented implicitly in the formulation of nutrient uptake. Efficient numerics allow us to optimize biogeochemical parameters against observations. Because iron sources are uncertain, largely due to poorly constrained scavenging, we generate a family of state estimates for a wide range of source strengths. All states have similar fidelity to the observations.
From our state estimates, we quantify the relative contribution of each iron source to export production. This is done non-invasively by labelling each iron type with a suitable passive tracer. We find that the phosphorus and opal exports are well constrained at 8.1±0.3 Tmol P yr-1 and 171.±3. Tmol Si yr-1. The exports supported by each iron type have well constrained patterns. Sedimentary iron supports export primarily in shelf and upwelling regions, while hydrothermal iron supports export mostly in the Southern Ocean. Per source-injected molecule, aeolian iron supports 3.1±0.8 times more phosphorus export and 2.0±0.5 times more opal export than the other iron types. Conversely, per injected molecule, sedimentary and hydrothermal iron support 2.3±0.6 and 4.±2. times less phosphorus export, and 1.9±0.5 and 2.±1. times less opal export than the other iron types.