Recognition of individuals within an animal population is central to a range of estimates about population structure and dynamics. However, traditional methods of distinguishing individuals, by some form of physical marking, often rely on capture and handling which may affect aspects of normal behavior. Photographic identification has been used as a less‐invasive alternative, but limitations in both manual and computer‐automated recognition of individuals are particularly problematic for smaller taxa (<500 g). In this study, we explored the use of photographic identification for individuals of a free‐ranging, small terrestrial reptile using (a) independent observers, and (b) automated matching with the Interactive Individual Identification System (I3S Pattern) computer algorithm. We tested the technique on individuals of an Australian skink in the Egernia group, Slater's skink Liopholis slateri, whose natural history and varied scale markings make it a potentially suitable candidate for photo‐identification. From ‘photographic captures’ of skink head profiles, we designed a multi‐choice key based on alternate character states and tested the abilities of observers — with or without experience in wildlife survey — to identify individuals using categorized test photos. We also used the I3S Pattern algorithm to match the same set of test photos against a database of 30 individuals. Experienced observers identified a significantly higher proportion of photos correctly (74%) than those with no experience (63%) while the I3S software correctly matched 67% as the first ranked match and 83% of images in the top five ranks. This study is one of the first to investigate photo identification with a free‐ranging small vertebrate. The method demonstrated here has the potential to be applied to the developing field of camera‐traps for wildlife survey and thus a wide range of survey and monitoring applications.

No abstract

Imperfect detection of individuals within an animal population can bias estimates of abundance and other population metrics. However, detectability may be improved by timing surveys with conditions that increase detection among individuals of the population. We explored the weather conditions that promote surface activity in a burrowing desert lizard, Slater's skink Liopholis slateri, with the aim of increasing detectability in observational surveys for this endangered species. We matched repeated count data (n = 126) of individuals within a population of Slater's skink sampled across four survey years with corresponding weather observations. We used classification and regression tree (CART) models to determine the environmental conditions that promoted high skink counts, and by inference high levels of surface activity. We also investigated how individual activity patterns varied over a day-night cycle through the course of a survey year using remote infrared cameras at burrow entrances set to capture images every 30 min. We found that two weather variables, air temperature and humidity, influenced activity levels, but there was no consistent single covariate, or set of covariates that explained surface activity. Variation in results of analysis between morning and evening datasets suggests that lizards respond to different weather conditions at different times of the day. We also found evidence of previously unreported nocturnal activity during the hottest months of the year.

We characterised 14 new polymorphic microsatellite loci for the endangered lizard Liopholis slateri. Initially, 454 shotgun sequencing was used to identify 46 loci, which were trialled for amplification. Subsequently, 14 of these loci were screened for variation in 21 individuals from scat-derived DNA samples collected from Owen Springs Reserve in central Australia. All 14 loci were polymorphic, with observed heterozygosity ranging from 0.19 to 0.86 and the number of alleles per locus ranging from 2 to 10. These loci will be useful in understanding the genetic variation and connectivity within and among extant L. slateri populations.