Modeling Climate & Economic Risk in Alaska’s Salmon Industry

Alaska supplies roughly 80 percent of North America’s wild-caught salmon, making the industry both an ecological cornerstone and a major economic driver for the state. This poster examined how climate change and economic pressures are reshaping that industry, asking whether rising ocean temperatures, sea level change, and ocean acidification are measurably affecting salmon populations and catch outcomes.

Presented at the 2025 SPARK! (Showcase of Projects, Art, Research, and Knowledge) Graduate Poster Exhibition, this research was developed by Evan Adams, a Master of Science student in Data Science at Rutgers University–Camden. Using environmental data, population metrics, and economic indicators, the project explored the sustainability of Alaska’s salmon industry in an era of accelerating climate disruption. The abstract appears below.

Graduate Poster Exhibition at SPARK!

The Graduate Poster Exhibition celebrates the research and creative work of the graduate community, showcasing everything from prose and code to original research and artistic expression. As part of SPARK! (Showcase of Projects, Art, Research, and Knowledge), a reimagining of Research Week, the exhibition highlights the depth, range, and impact of graduate scholarship and invites the campus community to engage with ideas taking shape across disciplines.

Mastering Data: The Data Science Program

The Master of Science in Data Science at Rutgers University–Camden is an interdisciplinary program that equips students with skills in data analysis, machine learning, and statistical modeling. The curriculum integrates tools from mathematics, computer science, public policy, and prevention science, emphasizing practical applications across various industries. Core courses include Foundations of Data Science, Statistical Methods for Data Science, Data Visualization, and Applied Data Mining and Machine Learning. Students also engage in a thesis or capstone project, applying their knowledge to real-world problems.

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