As a doctoral student at Columbia University and Lamont-Doherty Earth Observatory, Ruth developed novel machine learning methods to quantify songbird vocal activity and estimate when birds arrive at their Arctic breeding grounds based on over a thousand hours of acoustic recordings. Her results, published in Science Advances, demonstrate the potential for automated biodiversity sensors to contribute to ecological research by efficiently extracting information from large and highly complex data streams. She also leveraged cutting-edge GPS tracking devices to investigate how behavioral responses to environmental conditions contribute to long term shifts in migration timing of North America’s most recognizable songbird, the American. This work, published in Environmental Research Letters and reported in Newsweek, overcame previous technological challenges and represents a breakthrough in using individuals’ behavior to explain shifts in avian migration timing. As a Postdoctoral Associate at BGC, her work takes a global perspective on biodiversity by developing quantitative indicators to assess progress toward targets developed by the Convention on Biological Diversity. She developed metrics to assess trends in the coverage and sampling effectiveness of spatiotemporal biodiversity data within a flexible framework, which can quickly integrate information on tens of thousands of species. This enables a detailed understanding of how best to improve our collective knowledge and safeguard biodiversity for future generations.
Ruth Y. Oliver, Peter J. Mahoney, Eliezer Gurarie, Nicole Krikun, Brian Weeks, Mark Hebblewhite, Glen Liston, Natalie Boelman (2020) Behavioral response to spring snow conditions contribute to long-term shift in migration phenology in American robins, Environmental Research Letters.
Ruth Y. Oliver, Daniel P. W. Ellis, Helen E. Chmura, Jesse S. Krasue, Jonathan H. Pérez, Shannan K. Sweet, Laura Gough, John C. Wingfield, Natalie T. Boelman (2018) Eavesdropping on the Arctic: Automated bioacoustics reveal dynamics in songbird breeding phenology, Science Advances, 4, eaaq1084.