Every year, billions of birds undertake seasonal migrations, traveling vast distances across North America. These movements require physical adaptations and reflect fine-tuned responses to ecological signals such as resource availability and optimal timing for reproduction. Avian migration has substantial implications for human well-being, including ecosystem service provision, impacts on food security, and the potential to spread pathogens. However, despite the relevance of large-scale seasonal avian movement, relatively few studies have explicitly sought to understand how changes in migratory patterns emerge from ecological principles and these studies remain difficult due to several challenges. First, migration data across species are often sparse or inconsistent, and existing approaches frequently overlook behavioral plasticity and context-dependent responses. Second, these limitations stem in part from the fact that migration occurs across broad time and spatial scales, making direct field observations difficult to obtain. To overcome these challenges, this project integrates a trait-based framework with high-resolution, species-specific acoustic data to advance understanding of the mechanisms driving variation in migration timing across the United States. The project is designed to benefit students in southern Texas and will focus on providing training in avian ecology, biostatistics, and computer programming. Students will receive research training through a new Course-Based Undergraduate Research Experience on Signal Processing in Avian Ecology along with immersive workshops on bioacoustics. These courses are designed as an integral component of the research project, where students will directly contribute to both data collection and analysis. This research addresses a fundamental question in ecology: How do species’ functional traits determine responses to environmental variability and affect adaptation and survival? Avian migration, a large-scale, time-