Gloria Antonini, Emanuela Solano, Sarah Rossi de Gasperis, Emiliano Mancini, Giuseppe M. Carpaneto, Giulio Nigro, Alessandro Cini, Fabio Mosconi, Pio Federico Roversi, Franco Mason, Giuseppino Sabbatini Peverieri, Lara Redolfi De Zan, Alessandro Campanaro, Stefano Chiari, Rossi de Gasperis, S, Carpaneto, Giuseppe, Nigro, G, Antonini, G, Chiari, S, Cini, A, Mancini, Emiliano, Mason, F, Mosconi, L, Redolfi de Zan, L, Roversi, Pf, Sabbatini Peverieri, G, Solano, E, and Campanaro, A.
Assessing the conservation status of protected species needs quantitative population data, generally obtained using Capture-Mark-Recapture methods (CMR). The exploitation of natural marking (e.g. individual morphological traits) offers an interesting alternative, based on image analyses, which may result in a less manipulation of protected species compared to the typical artificial marking method. In our 2-year CMR study, we tested for the first time in the natural setting the feasibility and the application of the computer-aided photographic identification method of Rosalia alpina using the individual elytral spots as the natural marking. The I3SC software was used for the photographic analysis. Data were collected from populations of two National Parks of central Italy during July–August in 2014 and 2015. We developed a standard procedure in order to optimise the image acquisition in the field and to acquire clear and comparable images, facilitating the I3SC screening process. The results demonstrated that the computer-aided photographic identification of natural markings can be implemented in a CMR population study of R. alpina. Our image processing approach showed that using only the elytral central spot contours made the tracing contour process less time-consuming obtaining reliable results. Furthermore, I3SC output scores were used to identify a threshold value for the identification of new individuals or recaptures, facilitating the final identification proposed by operators. Finally, we assessed the possibility of performing the methodology using a Citizen Science approach.