PDF(Pubmed)
Abstract：
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.
摘要：
斑点灯笼是一种侵入性害虫，我们缺乏个体运动数据，部分原因是个体识别带来的困难。我们开发了一种计算机辅助方法，使用软件I3S处理的照片中的翼点图案来识别单个成年斑点灯，并通过实验室和现场验证证明了该方法的准确性。根据实验室的176个人，我们表明，将一个机翼的斑点数字化可以实现100％可靠的个人识别。与个体间的变化相比,由于用户输入和图像角度的变化引起的误差在很大程度上可以忽略不计。我们在标记重新捕获实验的背景下应用了该方法，以评估该方法在现场的可行性。我们最初确定了总共84只独特的斑点灯笼，其中31人在四小时后与49名新个体一起被重新捕获。我们确定，重新捕获的分析可能可以基于分数自动进行，并且可能不需要系统的视觉成对比较。这种方法在相对较小的样本量上的有效性证明使其成为现场实验和实验室操作的有前途的工具。一旦在更大的数据集上和不同的上下文中验证，它将提供充足的机会来收集有关斑点灯笼生态的有用数据，这些数据可以为管理部门提供很大的信息。
