Spatial distribution modelling of striped dolphin (Stenella coeruleoalba) at different geographical scales within the EU Adriatic and Ionian Sea Region, central-eastern Mediterranean Sea

The striped dolphin (Stenella coeruleoalba)is one of the most abundant cetaceans of the Mediterranean Sea. Nevertheless, it is ranked as 'Vulnerable' by IUCN Red List experts. To implement conservation strategies within the Mediterranean Sea, it is crucial to understand how striped dolphins are distributed at different geographical scales. The present study investigates its distribution within the EU Adriatic and Ionian Sea Region. To model striped dolphin distribution, topographic (distance from shore, depth and slope) and oceanographic variables (sea surface temperature and phytoplankton concentration) were employed, and species distribution models (SDMs) were developed using Maxent software. Generalized additive models (GAMs) were used to improve the information supplied by the SDMs, allowing the description of response curves to striped dolphin occurrences. Statistical analysis shows that striped dolphins are not evenly distributed within the investigated area. The higher encounter rates observed in the Gulf of Taranto and the Gulf of Corinth confirm that both sub-regions are crucial for its conservation. Furthermore, SDMs also indicate suitable areas in the offshore waters of the Adriatic Sea, along the continental slope of the north-eastern Ionian Sea and over its continental shelf. Within the EU Adriatic and Ionian Sea Region, striped dolphins prefer areas at a greater distance from shore, with steeper slopes, deeper waters, and higher sea surface temperature. The topographic variables are the most explicative factors for both modelling approaches. The analysis of striped dolphin SDMs allows the identification of important areas for conservation and highlights zones where appropriate mitigation strategies could reduce the impact of human activities on this Vulnerable species. Further analysis of SDMs for different periods of the year, as well as a genetic study, could highlight seasonal movements across and within sub-regions.