Jessica Luo

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March 21, 2022 11:30 am - 12:30 pm

Modeling marine plankton using a trait-based approach: benefits and limitations.  Jessica Luo received her B.A. and M.S. from Stanford University in 2007, and her Ph.D. in Marine Biology and Fisheries from the University of Miami in 2015. Dr. Luo completed her postdoctoral training at the National Center for Atmospheric Research (NCAR) in Boulder, CO, before moving to Princeton, NJ in 2019 to join the research staff at the NOAA Geophysical Fluid Dynamics Laboratory.

Marine plankton are incredibly speciose ocean ‘drifters’ that sit at base of the marine food chain, producing half of the global net primary productivity. They also serve as the primary contributors to the ocean biological pump, a collection of processes that transport carbon and nutrients from the surface oceans to depth, and are projected to shift substantially due to climate change. Efforts at modeling marine ecosystems and biogeochemistry on a global scale have either focused on very simplistic representations of plankton or complex, size-spectrum models with O(100) size classes of plankton, yet intermediate solutions for IPCC-class models have proved to be elusive. Here I discuss two trait-based modeling approaches for marine plankton communities. First, I present a trait-based model with full biogeochemistry, using size as the “master trait,” enabled for the Community Earth System Model (CESM). Secondly, I show that using size-independent traits in the GFDL-COBALT model can enable the representation of a critical but under-sampled group of zooplankton that have an outsize impact on the biological pump. Finally, I discuss ways to combine an emerging set of plankton observational tools with modeling to create improved global maps of plankton ecological traits.

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    Dr Alana Ayasse is a research scientist at Carbon Mapper and the University of Arizona. She earned her BA in Geography and Environmental Studies from UCLA and her PhD in Geography from UCSB. Her research focuses on improving remote sensing techniques to map methane and carbon dioxide plumes, understanding the role of satellites in a global carbon monitoring system, and using remote sensing data to further understand trends in carbon emissions.

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