Modeling the Speciation and Biogeochemistry of Iron at the Bermuda Atlantic Time-series Study Site

By means of numerical modeling we analyze the cycling of iron between itsvarious 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 quantitativeassessment of how this cycling influences iron uptake byphytoplankton and its loss via particle export. Themodel is forced with observed dust deposition rates, mixed layer depths, andsolar radiation at the site of the Bermuda Atlantic Timeseries Study(BATS). It contains an objectively optimized ecosystem model whichyields results close to the observational data from BATS that has beenused for the data-assimilation procedure.It is shown that the mixed layer cycle strongly influences the cyclingof iron between its various forms. This is mainly due to the lightdependency of photoreductive processes, and to the seasonality ofprimary production. The daily photochemical cycle is driven mainly bythe production of superoxide and its amplitude depends on theconcentration and speciation of dissolved copper.Model results are almost insensitive to the dominant form of dissolvediron within dust deposition, and also to the form of iron that istaken up directly during algal growth.In our model solutions, the role of the colloidal pumping mechanismdepends strongly on assumptions on the colloid aggregation andphotoreduction rate