The goal of the project is to develop improved parameterization of phytoplankton food web structure and community composition/diversity in the GFDL Earth System Models. Improved parameterization is critical to understanding and predicting ecosystem changes associated with climate change. A multidisciplinary, collaborative project is proposed in which (i) the composition of phytoplankton communities in major ocean basins will be described on the basis of functional genes (i.e., related to essential functions in assimilation of carbon and nitrogen) using high throughput analytical methods (the Phyto-array); (ii) statistical methods will be employed to quantitatively evaluate assemblage patterns derived from the Phyto-array and their relationships to environmental factors; and (iii) these results will be used to inform the development and refinement of biogeochemical ocean models to forecast trends in the ecosystems over time in response to climate change. The present composition and spatial variability in phytoplankton assemblages will be documented, and the deduced relationships will be used to predict changes as they occur over the next decades in response to both ocean and local scale components of climate change. Better parameterization of diversity and ecosystem structure will lead to a more mechanistically robust characterization of phytoplankton ecology in the GFDL Earth System Models and, therefore, a more effective means of characterizing the response of ocean ecosystems to climate change over the coming centuries. The analytical methods can also be used to monitor phytoplankton community changes over time to continually calibrate and validate both biogeochemical models of carbon flux and satellite remote sensing based models of primary productivity.