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Carbon Cycle & Ecosystems

Community structure, the taxonomic and functional composition of pelagic plankton communities, has an important bearing on global rates of net primary production, the export of carbon from the euphotic zone and the biogeochemical cycling of carbon and associated nutrients. New capabilities have recently been developed to assess phytoplankton community structure and carbon cycling from satellite ocean color observations and in intermediate complexity ecosystem models. Validation of these novel approaches and their further development is limited by scarcity of field observations over the variety of biogeochemical provinces of the global ocean. Since 2003, we have been studying the distribution and dynamics of colored dissolved organic matter (CDOM) in the global ocean "piggybacking" on hydrographic sections of the CO2/CLIVAR Repeat Hydrography Project. With NASA support, we have collected radiometric profiles, particle and CDOM absorption spectra, and phytoplankton pigment data. Our major science achievement to date is a new understanding of the relative roles of biogeochemical sources and sinks vs. ventilation on subsurface CDOM distributions. This work also has provided considerable validation data in poorly sampled areas of the ocean. Here, we propose to continue this effort on upcoming CO2/CLIVAR sections in the Arabian Sea, South Atlantic, Southern Ocean, and North Atlantic, and to enhance the program by adding a flow-through system that will also measure surface inherent optical properties (IOPs) such as spectral absorption, backscattering and particle size spectra. Our field effort will be closely coupled to our ongoing collaborative efforts in developing new ocean color products useful for assessing global productivity and carbon cycling. The combination of field and satellite data analyses will enable us to understand the controls on plankton community structure allowing an understanding of the processes by which phytoplankton community structure affects open ocean IOPs and how one can best assess community structure characteristics from IOPs.

Project PI: Norman Nelson/ University of California, Santa Barbara

Email: norm@icess.ucsb.edu

http://www.icess.ucsb.edu/~norm/

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Started: Aug 10, 2010

Last Activity: Dec 16, 2010

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