Rapid colour changes in a tiny threatened gecko do not impede computer-assisted individual recognition

Photo-identification is a non-invasive method used for recognising wild animals with distinctive and stable patterns over time. This method is now widely used for capture-recapture wildlife monitoring. However, in species exhibiting rapid colouration changes, the evolving body patterns can lead to errors in individual recognition. In this study, we assessed the effect of dorsal physiological colour change of the tiny threatened European leaf-toed gecko (Euleptes europaea) on the performance of Wild-ID and Hotspotter, the two most commonly used individual recognition software for wildlife monitoring. We exposed 30 European leaf-toed geckos to several semi-controlled parameters (substrate type, temperature and light from natural diurnal/nocturnal cycles) in order to characterise the extent of variation in dorsal colouration, by standardised reflectance measurements. The colour of the substrate had a significant effect on individual reflectance changes. Body temperature also seemed to significantly affect the reflectance but the experimental conditions did not allow us to clearly distinguish the effect of temperature and light. For each of the 30 geckos, four photographic databases (n = 4*280) were then analysed by both software packages, under two extreme reflectance conditions. Despite the large changes in individual reflectance, Wild-ID and Hotspotter proved to be extremely reliable with a 100% recognition rate. The analysis of similarity scores suggests that Hotspotter is less sensitive to chromatic variation than Wild-ID. We provide here the first evidence that physiological colour change is not a barrier to computer-assisted individual recognition. This study advocates the use of Hotspotter for monitoring populations of European leaf-toed geckos and other saurians that generate significant colouration change over a short time.