Effects of environmental factors on the detection of subsurface green turtles in aerial drone surveys
Michael N. Odzer
A , Annabelle M. L. Brooks B , Michael R. Heithaus C and Elizabeth R. Whitman C D
+ Author Affiliations
- Author Affiliations
A Dr Michael M. Krop Senior High School, 1410 NE 215th St, North Miami Beach, FL 33179, USA.
B Cape Eleuthera Institute, PO Box EL-26029, Rock Sound, Eleuthera, The Bahamas.
C Institute of Environment, Department of Biological Sciences, Florida International University, 3000 NE 151st St, North Miami, FL 33181, USA.
D Corresponding author. Email: ewhitman@fiu.edu
Wildlife Research 49(1) 79-88 https://doi.org/10.1071/WR20207
Submitted: 7 December 2020 Accepted: 25 October 2021 Published: 4 February 2022
Abstract
Context: Aerial video surveys from unpiloted aerial systems (UAS) have become popular in wildlife research because of increased accessibility to remote areas, reduction of anthropogenic disruption to habitats and wildlife, low operating costs, and improved researcher safety. In shallow marine systems, they can provide opportunities to rapidly survey species that cannot easily be surveyed using boat- or land-based techniques. However, detectability of subsurface animals in marine habitats may be affected by environmental factors.
Aims: We investigated the effects of water depth, seagrass cover, surface glare, and observer numbers and expertise on the probability of detecting subsurface green turtles in UAS video surveys.
Methods: We deployed inanimate green turtle decoys at randomised intervals along 24 pre-determined transects across a depth gradient in a seagrass-dominated bay off Great Abaco, The Bahamas. We collected aerial videos of the transects by flying a DJI Phantom 3 Advanced quadcopter drone at an altitude of 10 m over each transect. Three independent observers watched each video and recorded decoy sightings to compare detection probabilities across observer experience levels. We used a generalised linear model to test for the effects of glare, water depth, wind speed, and seagrass cover on the detectability of turtle decoys. We also recorded glare conditions with aerial videos taken at 2-h intervals over a still body of water on cloudless days off North Miami, FL.
Key results: Individual observers performed similarly, but adding one additional observer increased detection by 11–12% and adding a third observer increased detections by up to 15%. Depth, seagrass cover, and glare significantly affected decoy detections. In both summer and fall, the optimal times and directions to minimise glare in aerial video surveys were 0800 hours, facing any direction other than north, and 1800 hours, facing any direction other than south.
Conclusions: The number of human observers and environmental variables, especially depth, seagrass cover, and glare, are important to explicitly consider when designing and analysing data from UAS surveys of subsurface animal abundances and distribution.
Implications: Our study draws attention to potential limitations of UAS-acquired data for subsurface observations if environmental conditions are not explicitly accounted for. Quantifying the effects of environmental factors, designing surveys to minimise variance in these factors, and having multiple observers are crucial for optimising UAS use in research and conservation of sea turtles and other marine fauna.
Keywords: unpiloted aerial vehicle, unmanned aerial system, drone surveys, Chelonia mydas, The Bahamas, aerial survey.
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