Biffi Daniella, Tucker Mary R, Ackel Alexis, Williams Dean A
Andrews Institute for Research in Mathematics & Science Education Texas Christian University Fort Worth Texas USA.
Department of Biology Texas Christian University Fort Worth Texas USA.
Ecol Evol. 2025 Mar 24;15(3):e71167. doi: 10.1002/ece3.71167. eCollection 2025 Mar.
Identifying individuals within a species is vital for monitoring population dynamics and determining appropriate conservation efforts. Traditional methods for marking individual lizards include toe-clipping, branding, tattooing, and passive integrated transponder (PIT) tags. However, some of these methods can potentially cause stress, affect performance and survival, and raise concerns about the ethical treatment of animals. We conducted a long-term study on the urban ecology of Texas horned lizards living in two small towns in south Texas, USA. Our study was in the unique position of possessing a dataset of individuals that were PIT tagged, genotyped, and photographed, which allowed us to validate genotyping and natural markings for individual identification. We calculated our genotyping error rate by comparing genotypes of recaptured individuals identified by PIT tags. Our mean error rate per allele was 0.0016, our mean error rate per multilocus genotype was 0.032, and we had high power to identify individuals. We used HotSpotter software to match photographs of individuals identified by PIT tags and genotyping. HotSpotter successfully matched photographs of the same individual 94% of the time. This could be increased to almost 100% by looking at the top 10 picture matches by eye to validate the matching. Additionally, individual spot patterns were unique and stable across years. Using pictures of ventral spots is an easy way to identify individuals, avoids potential rare infection or mortality, and is inexpensive relative to PIT tags and genotyping.
识别物种内的个体对于监测种群动态和确定适当的保护措施至关重要。标记个体蜥蜴的传统方法包括趾尖切断、烙印、纹身和被动集成应答器(PIT)标签。然而,其中一些方法可能会造成压力,影响其表现和生存,并引发对动物伦理对待的担忧。我们对生活在美国得克萨斯州南部两个小镇的德州角蜥的城市生态进行了一项长期研究。我们的研究处于独特的地位,拥有一个关于经过PIT标签标记、基因分型和拍照的个体的数据集,这使我们能够验证用于个体识别的基因分型和自然标记。我们通过比较由PIT标签识别的重新捕获个体的基因型来计算我们的基因分型错误率。我们每个等位基因的平均错误率为0.0016,每个多位点基因型的平均错误率为0.032,并且我们有很高的能力识别个体。我们使用HotSpotter软件来匹配由PIT标签和基因分型识别的个体的照片。HotSpotter成功匹配同一个体照片的时间占94%。通过肉眼查看前10个图片匹配来验证匹配,这一比例可以提高到几乎100%。此外,个体的斑点图案多年来都是独特且稳定的。使用腹部斑点的照片是识别个体的一种简单方法,避免了潜在的罕见感染或死亡,并且相对于PIT标签和基因分型来说成本较低。