NSF Award Abstract:
The biological carbon pump in the ocean is an important process by which atmospheric carbon dioxide (CO2) is effectively transported from the surface ocean to the deep ocean, and thereby removing CO2 from the atmosphere. This transport occurs in a multi-step process. First, phytoplankton carry out photosynthesis in the surface, sunlit waters of the ocean, taking up atmospheric CO2 and fixing it into particulate organic carbon. A portion of the organic carbon contained in the phytoplankton is packaged into larger clusters (aggregates) that can sink to the deep ocean. The deeper these aggregates sink, the longer the carbon contained in them is removed from the atmosphere. The depth to which aggregates sink varies greatly over time and space and are difficult to predict. In general, larger aggregates sink more quickly, and thus more deeply, than smaller particles. Processes that promote aggregation to larger particles should enhance the biological pump, and processes that promote disaggregation (breakdown of particle clusters) and regeneration (decomposition) of the organic carbon should decrease the strength and efficiency of the biological pump. Particle aggregation and disaggregation rates are thus crucial to understanding the variability of the biological pump, but are very difficult to measure directly. This project will use chemical tracers and a modeling approach to quantify the rates of these important processes. The investigators will apply the approach to a variety of oceanic environments and provide the first large-scale effort to quantify these rates in the upper 500 meters of the ocean. As part of this project, they will interface with the CalTeach program, which is a University of California Science and Math Initiative to place university science, math, and engineering majors in K-12 classrooms. Many of these CalTeach interns go on to become K-12 science teachers in California. Two undergraduate students enrolled in the CalTeach program at the University of California, Santa Cruz (UCSC) will participate as laboratory assistants and develop a hands-on teaching module on the carbon cycle and biological pump for K-12 classrooms.
Scientists from the University of California at Santa Cruz and Woods Hole Oceanographic Institution propose to estimate the rates of particle aggregation and disaggregation in the mesopelagic zone through the inversion of observations of three chemical tracers, namely thorium (Th)-234, lithogenic particles, and particulate organic carbon (POC) distributed between small, suspended particles and large, sinking particles. The isotopes of Th have long been used to estimate rates of particle dynamics processes because of their known source function and particle-reactive behavior. Previous work has shown that lithogenic particles act as an inert, passive tracer of particle dynamics. The investigators will couple thorium and lithogenic particle measurements to measurements of POC to estimate particle aggregation and disaggregation rates from a wide range of oceanographic environments. Estimates of particle cycling rates deduced from the inversion of chemical tracer data provide a crucial quantitative constraint to which rates derived from other approaches can be compared. The main objective of this work is to estimate depth- varying (dis-) aggregation rates at each station of the EXPORTS and GEOTRACES cruises that are most consistent with the tracer data. This work will also produce depth-varying estimates of POC remineralization rates and particle sinking rates.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Lead Principal Investigator: Phoebe J. Lam
University of California-Santa Cruz (UCSC)
Principal Investigator: Olivier Marchal
Woods Hole Oceanographic Institution (WHOI)
Co-Principal Investigator: Jong-Mi Lee
University of California-Santa Cruz (UCSC)
Contact: Phoebe J. Lam
University of California-Santa Cruz (UCSC)
EXport Processes in the Ocean from Remote Sensing [EXPORTS]
DMP_Lam_Lee_Marchal_OCE-829614_1829790.pdf (80.10 KB)
12/07/2020