Julia Sharapi, Gettysburg College

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Class Year:

2021

Mentor:

Sairah Malkin, Ph.D.
Location

Project Title:

Community Analysis of Chesapeake Bay Phytoplankton from 1991 to 2012: Towards Spatial and Temporal Distribution of Mixotrophs

Abstract:

Mixotrophic phytoplankton, capable of both photoautotrophy and heterotrophy, have recently been gaining scientific interest. The type of heterotrophy mixotrophs perform, either phagotrophy (in which species eat other species) or osmotrophy (uptake of nutrients from water), depend on the species type. Mixotrophs complicate the way scientists have historically understood marine trophic structure, as they increase the trophic transfer to higher trophic levels than what would be expected based on rigid autotrophic and heterotrophic feeding modes. Therefore, simplification and miscategorization of mixotrophs as strict autotrophs and heterotrophs neglects the significance these species have throughout the entire food web, which is relevant to policy makers and coastal communities, as well as for fisheries management. Despite being widespread, especially in estuarine ecosystems like the Chesapeake Bay, mixotrophs remain understudied and overlooked. We utilized the R package phyloseq and phytoplankton and water quality data from the Chesapeake Bay Monitoring program to analyze the spatial distribution of phytoplankton in the Chesapeake Bay and the spatiotemporal patterns associated with phytoplankton assemblages. We determined there was a significant difference between the sampling done at the MSU/PEARL lab in Maryland and the ODU/PEL lab in Virginia, which both contributed to the Chesapeake Bay phytoplankton dataset. We identified 121 mixotrophic taxa based on a literature review; this will ultimately also be incorporated into assessment of phytoplankton community composition. We observed that there is a clear salinity gradient across surface water samples, which implies it is a major driver of phytoplankton assemblages. Future work will build on this by incorporating other parameters, namely riverine flow rates and season. Understanding the major drivers of assemblages in the Chesapeake Bay in both surface waters and near pycnocline depths will inform a more comprehensive assessment and investigation of what environmental variables impact mixotroph abundance. This project also demonstrates the capacity for utilizing phyloseq as an efficient way to process and analyze phytoplankton data.

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