Figure - available from: Canadian Journal of Zoology
This content is subject to copyright. Terms and conditions apply.
![Representation of the reference position (yellow dots) and the accessory (orange dots) points selected in different parts of Hermann’s Tortoise (Testudo hermanni) (A and B) and European Pond Turtle (Emys orbicularis) (C and D) when the ITM (A and C) and SPM (B and D) procedures of APHIS software were used. [Color online.]](publication/362179146/figure/fig1/AS:11431281257285001@1719599966663/Representation-of-the-reference-position-yellow-dots-and-the-accessory-orange-dots.jpg)
Representation of the reference position (yellow dots) and the accessory (orange dots) points selected in different parts of Hermann’s Tortoise (Testudo hermanni) (A and B) and European Pond Turtle (Emys orbicularis) (C and D) when the ITM (A and C) and SPM (B and D) procedures of APHIS software were used. [Color online.]
Source publication
Natural marks have increasingly been used as a tool for individual identification in capture–mark–recapture techniques. Photo-identification is a noninvasive alternative to traditional marking techniques, allowing individual recognition of species through time and space. We tested the APHIS (Automatic Photo Identification Suite) software as a softw...
Citations
... It was thought to be able to identify lizards (Moya et al. 2015), but its potential has since been tested with different model species (Table 1). In this context, it is worth highlighting the extensive experience of our research group in the use of APHIS in various and very different species (Díaz-Calafat et al. 2018;Salom-Oliver et al. 2022) (Table 1). This experience extends even to smaller amphibians such as Aytes muletensis (Sanchiz & Adrover, 1979) (Pinya and Pérez-Mellado 2009). ...
This study explores the potential of photo-identification methods (PIMs) as a viable, non-invasive, and ethical tool for wildlife studies, with a specific focus on anuran species such as Bufotes viridis balearicus (Boettger, 1880). Although the automatic photo-identification suite (APHIS) software was initially designed for lizard identification, our research shows its adaptability for anuran species, achieving a high detection accuracy rate of 95.28%, thus obtaining outstanding and higher values in compared to previous studies on this species. Crucially, our findings indicate that the success of PIM and the efficacy of image identification software like APHIS is dependent on the quality and standardization of the images collected. The study also underscores the importance of practical experience and continuous learning for the optimal utilization of software like APHIS. Despite occasional false rejected matches, the overall strong performance metrics with low false rejection rate demonstrate that these instances do not significantly impact the reliability of the technique. Thus, this research highlights the importance of careful implementation, continuous learning, and image quality control in leveraging the full potential of image identification software in wildlife studies.
