PROGNOSTIC MODELLING OF IRON-BINDING LIGANDS IN A GLOBAL BIOGEOCHEMICAL MODEL AND ITS EFFECT ON IRON DISTRIBUTION

Complexation with organic ligands controls the solubility of iron in the surface ocean; together with particle adsorption it thus determines the bioavailability and residence time of dust-deposited iron. Assumptions on ligand abundance are therefore critical for biogeochemical models that include iron. A number of processes are known that contribute to the production or breakdown of ligands, but that rate measurements of these processes are still uncertain.

Instead of fixing organic ligands to an observed mean concentration, a mechanistic description of ligand dynamics has been implemented in a global 3D biogeochemical model (REcoM). Two classes of ligands are considered in the model: strong and weak ligands, with different biogenic sources, photochemical reactivity and microbial degradation rates.

Modelled ligand and iron distribution are compared with global databases of ligand and iron measurements. Considering two ligands, the model shows significantly improved representation of iron distribution by contrast with model output with constant ligand concentration, particularly in the Atlantic and Indian Ocean. Prognostic modelling of iron-binding ligands strengthens biological controls on iron solubility which could enhance the predictive power of models under changing environmental conditions.