Student Authors
Marisa Immordino '20
Precious Ozoh '20
Lauren Sherman '21
McKenzie Somers '20
Document Type
Article
Publication Date
7-15-2022
Department 1
Environmental Studies
Department 2
Mathematics
Abstract
Using drones to conduct airborne bioacoustics surveys is a potentially useful new way to estimate the abundance of vocal bird species. Here we show that by using two audio recorders suspended from a quadcopter drone it is possible to estimate distances to birds with precision. In an experimental test, the mean error of our estimated distances to a broadcast song across 11 points between 0 and 100 m away was just 3.47 m. In field tests, we compared 1 min airborne counts with 5 min terrestrial counts at 34 count locations. We found that the airborne counts yielded similar data to the terrestrial point counts for most of the 10 songbird species included in our analysis, and that the effective detection radii were also similar. However, airborne counts significantly under-detected the Northern Cardinal (χ29 = 22.8, post-hoc test P = 0.007), which we attribute to a behavioral response to the drone. Airborne counts work best for species that vocalize close to the ground and have high-frequency-range songs. Under those circumstances, airborne bioacoustics could have several advantages over ground-based surveys, including increased precision, increased repeatability, and easier access to difficult terrain. Further, we show that it is possible to do rapid surveys using airborne techniques, which could lead to the development of much more efficient survey protocols than are possible using traditional survey techniques.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
DOI
10.1139/dsa-2022-0015
Version
Version of Record
Recommended Citation
Andrew M. Wilson, Darren B. Glass, Marisa A. Immordino, Precious S. Ozoh, Lauren B. Sherman, and McKenzie D. Somers. 2022. A method for estimating songbird abundance with drones. Drone Systems and Applications. 10(1): 367-381. https://doi.org/10.1139/dsa-2022-0015
Required Publisher's Statement
This article is available from the publisher's website.