Collecting reliable, real-time data on the migratory patterns of birds can help foster more effective conservation practices, and – when correlated with other data – provide insight into important environmental phenomena. Scientists at CLO currently rely on information from weather surveillance radar, as well as reporting data from over 400,000 active birdwatchers, one of the largest and longest-standing citizen science networks in existence. However, there are important gaps in this information since radar imaging cannot differentiate between species, and most birds migrate at night, unobserved by citizen scientists. The combination of acoustic sensing and machine listening in this project addresses these shortcomings, providing valuable species-specific data that can help biologists complete the bird migration puzzle.