Using social media image to identify threatened elasmobranch species caught by a small-scale fishery in a data-poor area

Abstract

Sharing fishing activity via social media attracts millions of views. The data from these shares includes key information for a fisheries database such as the species present in the catches and in many cases the number of specimens caught. Many countries in the Global South do not have official information about basic data on f ishing activity, especially small-scale activity. In many of such countries like Brazil, overfishing poses a significant threat to numerous threatened species, including elasmobranchs, due to the frailty of fisheries management and law enforcement. The lack of a national (Brazil) data collection program makes sharing data on social media a potential source of fisheries related information. Hence, this study aimed to verify the potential of social media data to describe artisanal fishing and identify elasmobranch species caught by a small-scale fleet in a data-poor Equatorial Southwest Atlantic region. The identification of elasmobranch species was made based on 250 videos shared by local fishers publicly on social media (Youtube™). Among these, sharks and rays were observed in 19 (8%) and 42 (17%) videos, respectively. A total of 98 specimens were recorded, of which 80% could be identified to a species level. Most of the records comprised the stingrays Hypanus berthalutzae and Hypanus guttatus, while Ginglymostoma cirratum was the most recorded shark. More than half of the elasmobranch species recorded are listed at some level of threat according to the IUCN Red List. According to the Brazilian legislation, at least 20% of the species identified in these videos are considered Endangered (EN) or Critically Endangered (CR). Therefore, fishing activity shared via social media can be considered effective in identifying threatened elasmobranch species, as well as providing data on species occurrence, number of specimens, or rare sightings. It is suggested that fishing activity shared via social media be used in parallel with traditional methods (e.g. on-board data and landing observations) to obtain fisheries information and data about endangered species in data poor areas.