Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

• Published in: Scientific reports Vol. 7; no. 1; pp. 17690 - 7
• Main Authors: Sykora-Bodie, Seth T., Bezy, Vanessa, Johnston, David W., Newton, Everette, Lohmann, Kenneth J.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 18.12.2017; Nature Publishing Group
• Subjects: 704/158/1745; 704/172; Aerial surveys; Aircraft; Animals; Aquatic reptiles; Bycatch; Coastal ecosystems; Conservation; Conservation of Natural Resources; Costa Rica; Ecological Parameter Monitoring - methods; Ecosystem; Humanities and Social Sciences; Lepidochelys olivacea; Marine ecosystems; multidisciplinary; Nesting; Nesting Behavior - classification; Pilot Projects; Population Density; Population Dynamics - trends; Reptiles & amphibians; Science; Science (multidisciplinary); Turtles; Costa Rica
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-17719-x

Although sea turtles face significant pressure from human activities, some populations are recovering due to conservation programs, bans on the trade of turtle products, and reductions in bycatch. While these trends are encouraging, the status of many populations remains unknown and scientific monitoring is needed to inform conservation and management decisions. To address these gaps, this study presents methods for using unmanned aerial systems (UAS) to conduct population assessments. Using a fixed-wing UAS and a modified strip-transect method, we conducted aerial surveys along a three-kilometer track line at Ostional, Costa Rica during a mass-nesting event of olive ridley turtles ( Lepidochelys olivacea ). We visually assessed images collected during six transects for sea turtle presence, resulting in 682 certain detections. A cumulative total of 1091 certain and probable turtles were detected in the collected imagery. Using these data, we calculate estimates of sea turtle density (km −2 ) in nearshore waters. After adjusting for both availability and perception biases, we developed a low-end estimate of 1299 ± 458 and a high-end estimate of 2086 ± 803 turtles km −2 . This pilot study illustrates how UAS can be used to conduct robust, safe, and cost-effective population assessments of sea turtle populations in coastal marine ecosystems.