One Year In - Madeline’s Year Working the Cuyahoga River Restoration Project

In January, I began my master’s with the QCE Lab and at the University of Missouri. My research aims to better understand how native species respond to habitat fragmentation and subsequent improvement efforts. My study takes place along the Cuyahoga River, with a focus on the potential ecological effects of the Gorge Dam and the anticipated outcomes once it’s removed.

This past spring, I spent time in Northeast Ohio, on the river tracking and tagging fish, and collecting side-scan sonar images for future habitat selection analyses. Monitoring these individuals has given me insights into their movements and behavior before dam removal, establishing a baseline for understanding how populations might respond to future changes.

A highlight of this summer was presenting my research at the Annual American Fisheries Society conference in San Antonio, at the Black Bass Symposium. I presented “Assessing Smallmouth Bass Movement in the Cuyahoga River Prior to Dam Removal,” a wonderful opportunity to share findings, gather feedback, and connect my work to broader conservation efforts.

I’m currently developing colonization models to predict which species from neighboring watersheds are most likely to recolonize and establish in reconnected habitats. I’m focusing on the Brecksville Dam removal (2020) and exploring potential outcomes once the Gorge Dam is removed. These models aim to reveal patterns of  species-specific movement and recolonization probabilities following a major habitat improvement strategy.

Looking ahead, I’m excited to continue refining models, expanding the dataset, and collaborating with other researchers. My goal is to contribute meaningful insights that inform management of our dynamic river ecosystems. This journey has been challenging, rewarding, and full of learning experiences, and I’m eager to see where the rest of my master’s work leads.

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Side-Scan Sonar Imagery for Invasive Carp Population Modeling

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Cuyahoga River Tagging