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Article

Incorporating Geographical Scale and Multiple Environmental Factors to Delineate the Breeding Distribution of Sea Turtles

1
School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK
2
National Marine Park of Zakynthos, 1 El. Venizelou Str., 29100 Zakynthos, Greece
*
Author to whom correspondence should be addressed.
Academic Editor: Adam T. Cross
Drones 2021, 5(4), 142; https://doi.org/10.3390/drones5040142
Received: 26 October 2021 / Revised: 22 November 2021 / Accepted: 23 November 2021 / Published: 26 November 2021
(This article belongs to the Special Issue Ecological Applications of Drone-Based Remote Sensing)
Temperature is often used to infer how climate influences wildlife distributions; yet, other parameters also contribute, separately and combined, with effects varying across geographical scales. Here, we used an unoccupied aircraft system to explore how environmental parameters affect the regional distribution of the terrestrial and marine breeding habitats of threatened loggerhead sea turtles (Caretta caretta). Surveys spanned four years and ~620 km coastline of western Greece, encompassing low (<10 nests/km) to high (100–500 nests/km) density nesting areas. We recorded 2395 tracks left by turtles on beaches and 1928 turtles occupying waters adjacent to these beaches. Variation in beach track and inwater turtle densities was explained by temperature, offshore prevailing wind, and physical marine and terrestrial factors combined. The highest beach-track densities (400 tracks/km) occurred on beaches with steep slopes and higher sand temperatures, sheltered from prevailing offshore winds. The highest inwater turtle densities (270 turtles/km) occurred over submerged sandbanks, with warmer sea temperatures associated with offshore wind. Most turtles (90%) occurred over nearshore submerged sandbanks within 10 km of beaches supporting the highest track densities, showing the strong linkage between optimal marine and terrestrial environments for breeding. Our findings demonstrate the utility of UASs in surveying marine megafauna and environmental data at large scales and the importance of integrating multiple factors in climate change models to predict species distributions. View Full-Text
Keywords: Caretta caretta; aerial drone; climate change; conservation management; habitat-performance relationships; distribution surveys; physical–biological coupling; remote sensing; species distribution Caretta caretta; aerial drone; climate change; conservation management; habitat-performance relationships; distribution surveys; physical–biological coupling; remote sensing; species distribution
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MDPI and ACS Style

Dickson, L.C.; Katselidis, K.A.; Eizaguirre, C.; Schofield, G. Incorporating Geographical Scale and Multiple Environmental Factors to Delineate the Breeding Distribution of Sea Turtles. Drones 2021, 5, 142. https://doi.org/10.3390/drones5040142

AMA Style

Dickson LC, Katselidis KA, Eizaguirre C, Schofield G. Incorporating Geographical Scale and Multiple Environmental Factors to Delineate the Breeding Distribution of Sea Turtles. Drones. 2021; 5(4):142. https://doi.org/10.3390/drones5040142

Chicago/Turabian Style

Dickson, Liam C., Kostas A. Katselidis, Christophe Eizaguirre, and Gail Schofield. 2021. "Incorporating Geographical Scale and Multiple Environmental Factors to Delineate the Breeding Distribution of Sea Turtles" Drones 5, no. 4: 142. https://doi.org/10.3390/drones5040142

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