Connor Wood, Ph.D.

Connor Wood checking the recording settings on a SWIFT unit.
Connor Wood checking the recording settings on a SWIFT unit.

I am the leader of the BirdNET Ecology Team. My research focuses on biodiversity conservation through the combination of bioacoustics and quantitative ecology; various forms of the BirdNET algorithm – which can currently identify over 3,000 birds by sound – underpin much of my work. My work on landscape-scale acoustic monitoring has three themes: endangered species conservationcommunity ecology, and the development of novel methodologiesCommunity-driven science is my second broad research area, a bottom-up approach to conservation that prioritizes the needs, interests, and values of people outside the traditional research apparatus.

Connor Wood GPS tagging a spotted owl
Connor Wood GPS tagging a spotted owl

My primary project is the Sierra Nevada acoustic monitoring program, which I began in 2016 as a Ph.D. student with Dr. Zach Peery at UW-Madison. At the beginning, it focused on Spotted Owls and an invasive competitor, the Barred Owl in the northern third of the region. The project enabled the successful eradication of the Barred Owl from the Sierra Nevada, averting the near-certain collapse of the California Spotted Owl population and widespread trophic cascades. Now, the monitoring program encompasses over 18,000 km2 across the entire Sierra Nevada, generates 1,000,000 hours of audio annually, and yields data on over 200 species of bird. With funding from NASA and other sources, we are developing cutting-edge tools to enable the conservation of a magnificent ecosystem that is on the brink of total transformation. Broadly, I am studying species richness with high resolution and landscape scales with an emphasis on conservation applications.

Spotted Owls remain a priority species; others include the Yosemite Toad, the gray wolf, and the Yucatan black howler monkey. Yet—as the Sierra Nevada project is demonstrating—BirdNET has enabled me to look beyond single-species conservation to study how whole communities respond to ecological disturbances. By working closely with managers and policy-makers, I hope that community-level research can inform holistic ecosystem management.

At present, I am primarily using the BirdNET app as a tool for community-driven science. My approach is to develop flexible tools that people can use as they see fit; my priority is supporting projects related to land sovereignty and sustainable development.

Year Hired: 2020

Contact Information
K. Lisa Yang Center for Conservation Bioacoustics
Cornell Lab of Ornithology
159 Sapsucker Woods Road, Ithaca, NY 14850, USA
Phone: +1-607.254.6250
Email: cmw289@cornell.edu

Degree(s):
Ph.D., University of Wisconsin, 2020
M.Sc., University of Maine
B.A., Middlebury College

Other: Website, Google Scholar

De León-Girón, G. et al. (2024) ‘Vocalization recordings of the Spotted Owl (<em>Strix occidentalis</em>) in the Sierra San Pedro Mártir, Baja California, Mexico’, Western North American Naturalist, 84(1). Available at: https://scholarsarchive.byu.edu/wnan/vol84/iss1/14.
Wood, C.M. and Kahl, S. (2024) ‘Guidelines for appropriate use of BirdNET scores and other detector outputs’, Journal of Ornithology [Preprint]. Available at: https://doi.org/10.1007/s10336-024-02144-5.
Bielski, L. et al. (2024) ‘Can the Hermit Warbler (<em>Setophaga occidentalis</em>) serve as an old-forest indicator species in the Sierra Nevada?’, Journal of Field Ornithology, 95(1). Available at: https://doi.org/10.5751/JFO-00390-950104.
Wood, C.M. et al. (2024) ‘A scalable and transferable approach to combining emerging conservation technologies to identify biodiversity change after large disturbances’, Journal of Applied Ecology, 61(4), pp. 797–808. Available at: https://doi.org/10.1111/1365-2664.14579.
Hack, B. et al. (2023) ‘Fine-scale forest structure, not management regime, drives occupancy of a declining songbird, the Olive-sided Flycatcher, in the core of its range’, Ornithological Applications, p. duad065. Available at: https://doi.org/10.1093/ornithapp/duad065.
Sossover, D. et al. (2023) ‘Using the BirdNET algorithm to identify wolves, coyotes, and potentially their interactions in a large audio dataset’, Mammal Research [Preprint]. Available at: https://doi.org/10.1007/s13364-023-00725-y.
Kelly, K.G. et al. (2023) ‘Estimating population size for California spotted owls and barred owls across the Sierra Nevada ecosystem with bioacoustics’, Ecological Indicators, 154, p. 110851. Available at: https://doi.org/10.1016/j.ecolind.2023.110851.
Watson, W.A. et al. (2023) ‘Passive acoustic monitoring indicates Barred Owls are established in northern coastal California and management intervention is warranted’, Ornithological Applications, p. duad017. Available at: https://doi.org/10.1093/ornithapp/duad017.
McGinn, K. et al. (2023) ‘Feature embeddings from the BirdNET algorithm provide insights into avian ecology’, Ecological Informatics, 74, p. 101995. Available at: https://doi.org/10.1016/j.ecoinf.2023.101995.
Brunk, K.M. et al. (2023) ‘Quail on fire: changing fire regimes may benefit mountain quail in fire-adapted forests’, Fire Ecology, 19(1), p. 19. Available at: https://doi.org/10.1186/s42408-023-00180-9.
Ross, S.R.P.-J. et al. (2023) ‘Passive Acoustic Monitoring provides a fresh perspective on fundamental ecological questions’, Functional Ecology, 37, pp. 959–975. Available at: https://doi.org/10.1111/1365-2435.14275.
Wood, C.M. et al. (2023) ‘Challenges and opportunities for bioacoustics in the study of rare species in remote environments’, Conservation Science and Practice, n/a(n/a), p. e12941. Available at: https://doi.org/10.1111/csp2.12941.
Kryshak, N.F. et al. (2022) ‘DNA metabarcoding reveals the threat of rapidly expanding barred owl populations to native wildlife in western North America’, Biological Conservation, 273, p. 109678. Available at: https://doi.org/10.1016/j.biocon.2022.109678.
Reid, D.S. et al. (2022) ‘Breeding status shapes territoriality and vocalization patterns in spotted owls’, Journal of Avian Biology, 8(e02952). Available at: https://doi.org/10.1111/jav.02952.
Hofstadter, D.F. et al. (2022) ‘Arresting the spread of invasive species in continental systems’, Frontiers in Ecology and the Environment, 20(5), pp. 278–284. Available at: https://doi.org/10.1002/fee.2458.
Wood, C.M. et al. (2022) ‘The machine learning–powered BirdNET App reduces barriers to global bird research by enabling citizen science participation’, PLOS Biology, 20(6), p. e3001670. Available at: https://doi.org/10.1371/journal.pbio.3001670.
Wood, C.M. and Peery, M.Z. (2022) ‘What does “occupancy” mean in passive acoustic surveys?’, Ibis, 164(4), pp. 1295–1300. Available at: https://doi.org/10.1111/ibi.13092.
Reid, D.S. et al. (2021) ‘Noisy neighbors and reticent residents: Distinguishing resident from non-resident individuals to improve passive acoustic monitoring’, Global Ecology and Conservation, 28, p. e01710. Available at: https://doi.org/10.1016/j.gecco.2021.e01710.
Hofstadter, D.F. et al. (2021) ‘High rates of anticoagulant rodenticide exposure in California Barred Owls are associated with the wildland–urban interface’, Ornithological Applications [Preprint], (duab036). Available at: https://doi.org/10.1093/ornithapp/duab036.
Wood, C.M. (2021) ‘Optimizing landscape-scale monitoring programmes to detect the effects of megafires’, Diversity and Distributions, n/a(n/a). Available at: https://doi.org/10.1111/ddi.13308.
Wood, C.M. et al. (2021) ‘Survey coverage, recording duration and community composition affect observed species richness in passive acoustic surveys’, Methods in Ecology and Evolution [Preprint]. Available at: https://doi.org/10.1111/2041-210X.13571.
Wood, C.M. et al. (2021) ‘Illuminating the Nocturnal Habits of Owls with Emerging Tagging Technologies’, Wildlife Society Bulletin [Preprint]. Available at: https://doi.org/10.1002/wsb.1156.
Wood, C.M. et al. (2021) ‘Density dependence influences competition and hybridization at an invasion front’, Diversity and Distributions, 27(5), pp. 901–912.
Kahl, S. et al. (2021) ‘BirdNET: A deep learning solution for avian diversity monitoring’, Ecological Informatics [Preprint]. Available at: https://doi.org/10.1016/j.ecoinf.2021.101236.
Wood, C.M. et al. (2020) ‘Using the ecological significance of animal vocalizations to improve inference in acoustic monitoring programs’, Conservation Biology [Preprint]. Available at: https://doi.org/10.1111/cobi.13516.
Wood, C.M. et al. (2019) ‘Detecting small changes in populations at landscape scales: a bioacoustic site-occupancy framework’, Ecological Indicators, 98, pp. 492–507. Available at: https://doi.org/https://doi.org/10.1016/j.ecolind.2018.11.018.
Klinck, H. et al. (2012) ‘Near-real-time acoustic monitoring of beaked whales and other cetaceans using a seagliderTM’, PLoS ONE, 7(5). Available at: https://doi.org/10.1371/journal.pone.0036128.