Aerial Drone Surveys Reveal the Efficacy of a Protected Area Network for Marine Megafauna and the Value of Sea Turtles as Umbrella Species

Abstract

Quantifying the capacity of protected area networks to shield multiple marine megafauna with diverse life histories is complicated, as many species are wide-ranging, requiring varied monitoring approaches. Yet, such information is needed to identify and assess the potential use of umbrella species and to plan how best to enhance conservation strategies. Here, we evaluated the effectiveness of part of the European Natura 2000 protected area network (western Greece) for marine megafauna and whether loggerhead sea turtles are viable umbrella species in this coastal region. We systematically surveyed inside and outside coastal marine protected areas (MPAs) at a regional scale using aerial drones (18,505 animal records) and combined them with distribution data from published datasets (tracking, sightings, strandings) of sea turtles, elasmobranchs, cetaceans and pinnipeds. MPAs covered 56% of the surveyed coastline (~1500 km). There was just a 22% overlap in the distributions of the four groups from aerial drone and other datasets, demonstrating the value of combining different approaches to improve records of coastal area use for effective management. All four taxonomic groups were more likely to be detected inside coastal MPAs than outside, confirming sufficient habitat diversity despite varied life history traits. Coastal habitats frequented by loggerhead turtles during breeding/non-breeding periods combined overlapped with 76% of areas used by the other three groups, supporting their potential use as an umbrella species. In conclusion, this study showed that aerial drones can be readily combined with other monitoring approaches in coastal areas to enhance the management of marine megafauna in protected area networks and to identify the efficacy of umbrella species.

Keywords

• functional diversity
• indicator species
• ocean health
• spatial prioritisation
• UAS
• UAV