Dr. Amy Van Scoyoc is a computational ecologist working at the intersection of bioacoustics, machine learning, and large-scale wildlife monitoring across California's working lands and wildlife corridors. Her current work focuses on building open science tools and benchmarking ML pipelines for audio classification and species detection, using the vast camera trap and acoustic data streams produced by environmental sensor networks. Her broader research program in movement and landscape ecology uses hierarchical state-space models and remote sensing to track how habitat fragmentation affects wildlife populations, behavior, and interactions. Dr. Van Scoyoc has worked in partnership with academic, state and tribal government, and community collaborators to advance open science and build durable tools for biodiversity research.
Education
BA, Biology, Dartmouth College, Hanover, NH, 2013
PhD, Environmental Science, Policy & Management, UC Berkeley, CA, 2023
Research Lab
Eric & Wendy Schmidt Center for Data Science & Environment (DSE)
Boettiger Group (affiliate)
Selected Publications
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Calhoun, K. L., Smith, J. A., Tingley, M. W., Heeren, A., Van Scoyoc, A., Serota, M. W., Brashares, J. S. & Furnas, B. J. (2025). Human-wildlife conflict is amplified during periods of drought. Science Advances, 11(46), eadx0286. https://doi.org/10.1126/sciadv.adx0286
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Van Scoyoc, A., Calhoun, K. L., & Brashares, J. S. (2024). Using multiple scales of movement to highlight risk–reward strategies of coyotes (Canis latrans) in mixed‐use landscapes. Ecosphere, 15(8), e4977. https://doi.org/10.1002/ecs2.4977
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Van Scoyoc, A., Smith, J. A., Gaynor, K. M., Barker, K., & Brashares, J. S. (2023). The influence of human activity on predator-prey spatiotemporal overlap. The Journal of Animal Ecology. 92(6), 1124-1134. https://doi.org/10.1111/1365-2656.13892
Read more at Google Scholar
Selected Honors and Awards
- Dissertation Writing Award for Outstanding Contributions to Department, 2023
- National Science Foundation Graduate Research Fellow, 2018
Bioacoustics, deep learning, wildlife ecology, remote sensing, open science