ABUNDANCE AND DISTRIBUTION OF THE WHITE SHARK IN THE MEDITERRANEAN SEA

Conservation of apex predators is a key challenge both in marine and terrestrial ecosystems, and sharks represent one of the most endangered groups in the ocean as a consequence of fishing exploitation, high vulnerability and a generalized lack of data on ecology and conservation status. This situation is particularly critical in the Mediterranean Sea due to its millenarian history of exploitation. Even if the white shark is a rare but persistent inhabitant of the Mediterranean Sea, its ecology in the area is still largely unknown. We have scarce information about white shark distribution and habitat use, aspects that are critical for conservation and management. The species is currently assessed as “Critically Endangered” according to the IUCN Regional Redlist criteria. In this study, we built the most comprehensive database of white shark occurrence records in the area (773 observations) and used them to characterize the spatial and temporal patterns of abundance of Mediterranean white sharks within a large temporal window (1860-2016). We fitted generalized additive models to standardized occurrence rates and used spatially disaggregated information on human coastal population abundance as a proxy of observation effort. Our results suggest a complex trajectory of population change characterized by a historical increase and a more recent steep reduction (61.5%) since the second half of 20th-century. Declines ranged between 52% and 97% across different Mediterranean sectors, with a contemporary regional contraction of the spatial distribution. For the first time, these results would inform conservation assessments, underlining the importance to produce status assessments based on population trends that are not suspected but quantitatively inferred. Furthermore, our analyses resulted instrumental to advance new hypotheses on the white shark occurrence and ecology in the Mediterranean Sea and to plan tagging programs with the purpose of collecting high-quality ecological data such distribution, population structure, foraging and habitat use.