Nest site selection has important consequences on the fitness and the development of Hawksbill hatchlings, however, the factors influencing nest site selection has proven difficult to decipher. To determine the factors influencing nest site selection of Hawksbill turtles across six beaches in the South of Mahé in Seychelles, a Generalized Linear Model was conducted using ground data gathered over a two-year period. Furthermore, to assess the potential use of Unmanned Aerial Vehicles (UAV) in the identification of nesting areas, an Optimized Hotspot Analysis was performed. Results suggest that vegetation type, percentage canopy cover and percentage ground cover affect the number of nests (P<0.01, AIC= 1209.6). However, slope, width, and zonation did not have a significant effect on the number of nests. The results of the Optimized Hotspot Analysis (OHA) using drone imagery revealed a significant clustering of nests. The GetisOrd Gi* Statistic determined the optimal beach consisted of a 10% natural debris ground vegetation, 30% Scaevola canopy vegetation or 50% Coconut canopy vegetation, a slope of -5◦ and a beach width of 18m. The results also indicate the potential use of UAVs in future conservation strategies as the OHA was able to accurately predict (87%) Hawksbill nesting sites.
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