Evaluation of drones as a tool for multi‐species nest surveys on linear rights‐of‐way

Abstract The varying application of drone use in wildlife research has expanded in recent years. With the ability to utilize a variety of different sensors (e.g., infrared [IR] and high‐resolution cameras), drones have the potential to be an effective tool for surveying wildlife. However, additional validation studies are needed, particularly when surveys are designed to conform with regulatory requirements concerning the prevention or minimization of disturbance to birds and nests as protected under provincial, state, or federal law. We compared the performance of drones with mounted IR and RGB (red, green, blue) lenses against standard ground‐based nest surveys in the detection of active bird nests in native grassland and tame pasture habitats on pipeline rights‐of‐way in Alberta in 2020 and 2022. We found that a drone team, consisting of a drone pilot and a wildlife biologist on foot, was as effective and efficient at detecting nests of ground‐nesting and low‐nesting birds (i.e., nests lower than 2 m above ground surface) as the standard method of 2 biologists working on foot. Specifically, nest disturbance duration (measured in 2022 only; drone team: 2 min 13 sec; human team: 2 min 34 sec; P = 0.341), nests per km 2 (2020: 19.394 v. 14.564, P = 0.372; 2022: 11.883 v. 11.950, P = 0.674), and nests detected per hour (2020: 0.517 v. 0.312, P = 0.075; 2022: 0.484 v. 0.369, P = 0.276) did not differ statistically between a drone team and a human team. Nest detection probabilities across both years of the study were similar for the drone team (0.141, 95% CI = 0.057–0.308) and human team (0.093, 95% CI: 0.026–0.285). Drone technology has the potential to reduce construction and operation delays, and personnel requirements, whilst providing accuracy, efficiency, scientific robustness, and a valuable tool in right‐of‐way management.

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Publication Details

Journal
Wildlife Society Bulletin
Published
2026-01-07
DOI
https://doi.org/10.1002/wsb.70018
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluation of drones as a tool for multi‐species nest surveys on linear rights‐of‐way

Karl L. Kosciuch, Nick Bartok, Kirsten Pearson, Jared Swenson et al.
Wildlife Society Bulletin
UAV Applications and Optimization
article

Evaluation of drones as a tool for multi‐species nest surveys on linear rights‐of‐way

Karl L. Kosciuch, Nick Bartok, Kirsten Pearson, Jared Swenson, John D. Lloyd, Nathan Mayer
article en

Abstract

Abstract The varying application of drone use in wildlife research has expanded in recent years. With the ability to utilize a variety of different sensors (e.g., infrared [IR] and high‐resolution cameras), drones have the potential to be an effective tool for surveying wildlife. However, additional validation studies are needed, particularly when surveys are designed to conform with regulatory requirements concerning the prevention or minimization of disturbance to birds and nests as protected under provincial, state, or federal law. We compared the performance of drones with mounted IR and RGB (red, green, blue) lenses against standard ground‐based nest surveys in the detection of active bird nests in native grassland and tame pasture habitats on pipeline rights‐of‐way in Alberta in 2020 and 2022. We found that a drone team, consisting of a drone pilot and a wildlife biologist on foot, was as effective and efficient at detecting nests of ground‐nesting and low‐nesting birds (i.e., nests lower than 2 m above ground surface) as the standard method of 2 biologists working on foot. Specifically, nest disturbance duration (measured in 2022 only; drone team: 2 min 13 sec; human team: 2 min 34 sec; P = 0.341), nests per km 2 (2020: 19.394 v. 14.564, P = 0.372; 2022: 11.883 v. 11.950, P = 0.674), and nests detected per hour (2020: 0.517 v. 0.312, P = 0.075; 2022: 0.484 v. 0.369, P = 0.276) did not differ statistically between a drone team and a human team. Nest detection probabilities across both years of the study were similar for the drone team (0.141, 95% CI = 0.057–0.308) and human team (0.093, 95% CI: 0.026–0.285). Drone technology has the potential to reduce construction and operation delays, and personnel requirements, whilst providing accuracy, efficiency, scientific robustness, and a valuable tool in right‐of‐way management.

Wildlife Society BulletinVol. 50(1)
Geological Survey of Canada (CA), Western EcoSystems Technology (United States) (US)
Life in Land
Openalex Percentile: Top 96%
UAV Applications and Optimization
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