Viki Mancoridis ’23
Drivers of Variability in Exploited Marine Fish Populations
The purpose of this project was to predict the survival rates of Atlantic cod through models that consider climate trends and market pressure. I parsed online databases and implemented various estimation techniques to compile data on the biological, geospatial, environmental and economic attributes of cod stocks. I fed relevant data into a hierarchical linear mixed model that calculated the fit of classic discrete population models to my data. I compared fits of two competing population models: One that considered the impact of sea surface temperatures on stock survival rates, and one that did not. Correlation rates were higher when climate trends were considered. Next, I modeled the economic impacts of cod price flexibility. I found that various cod-stock prices were inelastic, while others were elastic. This is critical information for fisheries’ managers, who must react to resource depletion responsibly. The most interesting part of my work was learning about oceanic sciences, which was entirely new to me. The project also gave me proficiency in using Python and Stan software for research purposes, and taught me how to manage a GitLab repository. In the future, I will keep an eye out for other computational biology opportunities!
Food Systems, Water And Human Health
Sarmiento Group, Program in Atmospheric and Oceanic Sciences, Princeton University
Jorge Sarmiento, George J. Magee Professor of Geoscience and Geological Engineering, Emeritus, Professor of Geosciences, Emeritus; Fernando González Taboada, Associate Research Scholar, Atmospheric and Oceanic Sciences