Degree Name

Department

Biology

College

Life Sciences

Defense Date

2025-12-03

Publication Date

2025-12-15

First Faculty Advisor

Steven Peck

First Faculty Reader

Steven Leavitt

Honors Coordinator

Jerald Johnson

Keywords

Ecology, Urban Ecology, Soundscape, Acoustic Ecology, Biophony, Machine Learning

Abstract

This thesis examines the application of soundscape ecology principles to urban settings. Soundscape ecology is the study of the entire sonic makeup of a community, composed of biophony (biological sound), geophony (environmental sound), and anthrophony (human-generated sound). By examining the changes in and qualities of the soundscape, researchers can gain information about the biological makeup and ecological quality of an area, and the temporal and spatial distribution of resident species. Recent technological advances in recording equipment and machine learning methods are making soundscape ecology an increasingly relevant and practical tool.

Applying soundscape ecology methods to urban ecosystems introduces unique challenges, such as overcoming the influence of strong anthropogenic noise, and ensuring the accuracy of soundscape metrics for each area of study. This thesis explores possible solutions to these challenges, and provides future directions for urban soundscape ecology research.