Modeling the speciation and biogeochemistry of iron at the Bermuda Atlantic Time‐series Study site

Abstract

By means of numerical modeling, we analyze the cycling of iron between its various physical (dissolved, colloidal, particulate) and chemical (redox state and organic complexation) forms in the upper mixed layer. With our proposed model it is possible to obtain a first quantitative assessment of how this cycling influences iron uptake by phytoplankton and its loss via particle export. The model is forced with observed dust deposition rates, mixed layer depths, and solar radiation at the site of the Bermuda Atlantic Time‐series Study (BATS). It contains an objectively optimized ecosystem model which yields results close to the observational data from BATS that has been used for the data‐assimilation procedure. It is shown that the mixed layer cycle strongly influences the cycling of iron between its various forms. This is mainly due to the light dependency of photoreductive processes, and to the seasonality of primary production. The daily photochemical cycle is driven mainly by the production of superoxide, and its amplitude depends on the concentration and speciation of dissolved copper. Model results are almost insensitive to the dominant form of dissolved iron within dust deposition, and also to the form of iron that is taken up directly during algal growth. In our model solutions, the role of the colloidal pumping mechanism depends strongly on assumptions on the colloid aggregation and photoreduction rate.