The goal of many biogeochemists is to determine how the relationships between physical, chemical, and biological oceanography will lead to feedbacks between the earth's oceans and climate. One tool that biogeochemists use is the three-dimensional coupled physical-biological model. These models typically include a physical model with horizontal resolution that may vary from <1 km to >400 km depending on the objective, scale, and computational power of the project. Embedded within the physical model will be a (relatively) simple mathematical construct representing the chemical and ecological processes which the modeler believes are pertinent to the particular question being addressed. At their most basic level these models describe the transfer functions linking biological and chemical standing stocks (state variables). Such biogeochemical models have been used for purposes as diverse as assessing the effects of fronts on plankton communities and predicting changes in carbon sequestration rates under different climate change scenarios.

 

Modern biogeochemical models deal with many issues, the most fundamental of which is our still nascent understanding of the role of biota in biogeochemical cycles. While the physical equations of state are relatively well known, biological oceanographers do not yet agree on something as fundamental as which plankton functional groups are necessary to include. In fact, the importance of including different plankton functional groups may be intrinsically tied to the processes addressed by the model and dependent upon the geographical regions assessed. Furthermore, parameterization of plankton models is largely ad hoc. Unfortunately, the limited data that we have to parameterize such important processes as phytoplankton nutrient uptake kinetics comes from laboratory studies that not only are done in conditions that vary greatly from those experienced in situ, but also involve only a single species (typically only a single strain), while biogeochemical models invariably aggregate multiple species (and genera, families, etc.) into a single plankton functional group.

Nevertheless three-dimensional biogeochemical models have great utility, because there are many biophysical interactions that are difficult to elucidate from cruise or satellite data. For instance, I created a model of diatom-diazotroph assemblages (DDA) in the Amazon River Plume (which we embedded in a physical model of the Tropical Atlantic constructed by Victoria Coles) to address the role of top-down and bottom-up forcing on DDA, using simulated Lagrangian floats. While it would be possible (though difficult) to simultaneously measure DDA growth rates, nutrient uptake kinetics, and losses to grazers in the field, such experiments would never have shown us another critical factor in determining whether or not DDA would bloom. Our model suggested that physical retention in the mesohaline region was a critical prerequisite for DDA bloom formation. This unanticipated model result can now be framed as a testable hypothesis to assess on subsequent cruises in the region: DDA net growth rates in their ideal habitat niche are only slightly greater than one, hence bloom formation requires a stable niche for significant duration.