RII Track-4: NSF: Toward Tracking Organic Carbon Cycling in a Changing Arctic Ocean using Optical Properties and Numerical Modelling

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Phytoplankton, which form the base of marine food webs, are responding to the associated higher light availability and fresher surface water in the Arctic. Their spring bloom is occurring earlier due to early sea ice melt, and they have recently tended to show a fall bloom. This suggests that the phytoplankton are acclimating to a “new Arctic”. The goal of this project is to improve the understanding of phytoplankton-originating organic carbon cycling through a collaboration with scientists at the Scripps Institution of Oceanography (SIO) in San Diego, California. The opportunity to collaborate with two leading scientists in the field of optical oceanography at SIO will positively impact and potentially transform the PI’s research career trajectory. These benefits will also enhance the research capacity of the PI’s home institution.The goal of the project is to 1) investigate phytoplankton changes in response to environmental variables, 2) track vertical export of phytoplankton-originating organic carbon, and 3) predict the impact of phytoplankton changes on zooplankton abundance. The investigator will analyze several comprehensive datasets acquired on five field campaigns to the Arctic between 2010 and the fall of 2021. The data include inherent and apparent optical properties, phytoplankton pigments and community composition, and a full suite of physical and chemical measurements. Samples obtained from the most recent campaign will be shipped to SIO for analysis using a customized optical instrument and technique developed by two leading experts in the field of Optical Oceanography at SIO. The phytoplankton community composition will be derived from the measured phytoplankton absorption spectra. The vertical export of organic carbon will be estimated using an innovative approach based on profiles of particle backscattering. Together with the data from spring and summer campaigns in previous years, the fall data will be used to parameterize a numerical model of the seasonal succession of phytoplankton and zooplankton. The primary outputs will be publications and presentations for both scientific and public audiences. Expected outcomes will consist of training in the state-of-the-art optical measurement and modelling techniques and mentoring of a post-doc in the integration of the knowledge into a numerical model.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.