Photographic identification method (PIM) using natural body marks: A simple tool to make a long story short

Spotted! Computer-aided individual photo-identification allows for mark-recapture of invasive spotted lanternfly (Lycorma delicatula)

The spotted lanternfly is an invasive pest for which we lack individual movement data due in part to the difficulty posed by individual identification. We developed a computer-aided method to identify individual adult spotted lanternfly using wing spot patterns from photos processed in the software I3S and demonstrated the method's accuracy with lab and field validations. Based on 176 individuals in the lab, we showed that digitizing the spots of one wing allowed a 100% reliable individual identification. The errors due to user input and the variation in the angle of the image were largely negligible compared to inter-individual variations. We applied this method in the context of a mark-recapture experiment to assess the feasibility of this method in the field. We initially identified a total of 84 unique spotted lanternflies, 31 of which were recaptured after four hours along with 49 new individuals. We established that the analysis of recaptures can possibly be automated based on scores and may not require systematic visual pairwise comparison. The demonstration of the effectiveness of this method on relatively small sample sizes makes it a promising tool for field experimentation as well as lab manipulations. Once validated on larger datasets and in different contexts, it will provide ample opportunity to collect useful data on spotted lanternfly ecology that can greatly inform management.

Shot the spots: A reliable field method for individual identification of Amolops formosus (Anura, Ranidae)

Natural body patterns in amphibians are widely used for individual recognition. In this study, we photographed individuals of Amolops formosus for four days of sampling without handling them. We processed 301 photographs of dorsal blotch pattern in HotSpotter software and verified them visually for confirmation. We identified 160 unique individuals of A. formosus based on the images taken in the field, resulting in an abundance estimate of 180 individuals. The success rate in identifying individuals of A. formosus using the HotSpotter software was 94.3%. We tested the effect of image quality and distance on recognition efficiency. Poor image quality reduced the recognition efficiency of the software but with a careful user review it was possible to identify the individual. The difference between using only the software and software plus human confirmation was very small. This protocol is useful for rapid population estimation of frogs with natural body patterns.