External Speaker Series: Justin Kitzes on Automated Acoustics Surveys for Understanding and Predicting Biodiversity at Scale

All dates for this event occur in the past.

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Abstract: The availability of accurate, large-scale, long-term data on species diversity and abundance form a critical foundation for understanding, predicting, and ultimately prevent biodiversity loss. In this talk, I will discuss new developments in the field of bioacoustics that are allowing ecologists to gather and analyze data on terrestrial wildlife at increasingly large spatiotemporal scales. First, I will describe our approach to combining inexpensive field sensors, machine learning, and statistical models for surveying songbirds, frogs, and other taxa in the field. Second, I will describe how we have used this framework to draw new insights across the fields of natural history, conservation, and ecology.

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Speaker Bio: Justin Kitzes is an Assistant Professor of Biological Sciences at the University of Pittsburgh. His research broadly examines how species are distributed across complex landscapes, and how human impacts drive these distributions, with a particular focus on the ecology and conservation of rare and hard-to-detect species. To better study these species, his work relies heavily on techniques from terrestrial bioacoustics, specifically automated acoustic field recorders and machine learning models for sound detection and classification. His lab both develops methods and tools to enable bioacoustics research and applies these methods to answer questions spanning natural history, conservation, and ecology. Dr. Kitzes received his Ph.D. from the University of California, Berkeley (Environmental Science, Policy, and Management) and his B.S. and M.S. degrees from Stanford University (Earth Systems).