Abstract
Population studies often incorporate capture‐mark‐recapture (CMR) techniques to gather information on long‐term biological and demographic characteristics. A fundamental requirement for CMR studies is that an individual must be uniquely and permanently marked to ensure reliable reidentification throughout its lifespan. Photographic identification involving automated photographic identification software has become a popular and efficient noninvasive method for identifying individuals based on natural markings. However, few studies have (a) robustly assessed the performance of automated programs by using a double‐marking system or (b) determined their efficacy for long‐term studies by incorporating multi‐year data. Here, we evaluated the performance of the program Interactive Individual Identification System (I3S) by cross‐validating photographic identifications based on the head scale pattern of the prairie lizard (Sceloporus consobrinus) with individual microsatellite genotyping (N = 863). Further, we assessed the efficacy of the program to identify individuals over time by comparing error rates between within‐year and between‐year recaptures. Recaptured lizards were correctly identified by I3S in 94.1% of cases. We estimated a false rejection rate (FRR) of 5.9% and a false acceptance rate (FAR) of 0%. By using I3S, we correctly identified 97.8% of within‐year recaptures (FRR = 2.2%; FAR = 0%) and 91.1% of between‐year recaptures (FRR = 8.9%; FAR = 0%). Misidentifications were primarily due to poor photograph quality (N = 4). However, two misidentifications were caused by indistinct scale configuration due to scale damage (N = 1) and ontogenetic changes in head scalation between capture events (N = 1). We conclude that automated photographic identification based on head scale patterns is a reliable and accurate method for identifying individuals over time. Because many lizard or reptilian species possess variable head squamation, this method has potential for successful application in many species.
Highlights
Population studies often incorporate capture-mark-recapture (CMR) techniques to gather information on long-term biological and demographic characteristics (Kacoliris et al, 2009, Sreekar et al 2013)
We evaluated the performance of the program Interactive Individual Identification System (I3S) by cross-validating photographic identifications based on the head scale pattern of the prairie lizard (Sceloporus consobrinus) with individual microsatellite genotyping (N = 863)
Our findings demonstrate that the semiautomated photographic identification software I3S is a reliable tool for identifying individual prairie lizards based on head scale patterns
Summary
Population studies often incorporate capture-mark-recapture (CMR) techniques to gather information on long-term biological and demographic characteristics (Kacoliris et al, 2009, Sreekar et al 2013). Cross-validating photographic identification with a different technique yields more precise error rates because each method relies on different parameters (e.g., variable spot patterns, highly polymorphic microsatellites [Drechsler et al, 2015]), leading to different misidentifications and allowing for cross-validation between the two methods It is unclear whether photographic identification is effective in multi-year studies because in some species natural markings can change over time due to ontogenetic affects (Bendik et al, 2013; Germano & Williams, 2007; Treilibs et al, 2016) or damage to the skin (Bauwens et al, 2018; Moro & MacAulay, 2014). Our two objectives for this study are: (a) determine misidentification rates of I3S in a CMR environment by cross-validating capture histories with genotyping, and (b) compare the relative ability of I3S to correctly identify recaptures made within the same year and between different years
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