Fotoidentificação de tartarugas marinhas: uma ferramenta participativa de conservação - Oliveira, Yeda Christina Bezerra Barbosa de (2017)
Sea turtles are representative umbrella species in marine ecology and conservation. Prior knowledge about the species, from their distribution to population structure and dynamics of them start by individual monitoring. One of the recommended methods is the photo-identification, due to the low cost, high accuracy and non-invasive procedure. Photographic analyses are based on natural marks from animal body, and can be performed by naked eye or computer-assisted. The ease in collecting data is also a further advantage over artificial tags, in which allow the contribution of citizen scientists. Our work aimed to define parameters for the photo-identification of Chelonia mydas and Eretmochelys imbricata using I3S software, based on already used facial scales and the new method from the hind flippers. Focusing on citizen-science projects, we evaluated the quality of the data collected by volunteer divers with different profiles. A total of 53 individuals was captured, Chelonia mydas (n = 47) and Eretmochelys imbricata (n = 6), and 4 recaptures of each species were registered in Fernando de Noronha Archipelago as method validation. We cataloged the records independently on the database, with a set of facial profiles and hind flipper fingerprints. We tested the accuracy of the program in (1) recognizing each individual and (2) differing them among the population. Our results show that both body regions are efficient for photo-identification, and species is the main effect on the scores calculated by the program. Hind flippers indicate to be highly differentiated in E. imbricata, unlike C. mydas, in which are prone to the false-negative errors. Among the 83 records provided by citizen scientists, 43% were discarded mainly due to the angle-of-view and framing errors. The proposed method may help to overcome problems in identification of sea turtles and represents new opportunities of study. However, training on records is highly recommended to enhance data quality.