Spotted! Computer-aided individual photo-identification allows for mark-recapture of invasive spotted lanternfly (Lycorma delicatula)

Nadège Bélouard, J. Behm
{"title":"Spotted! Computer-aided individual photo-identification allows for mark-recapture of invasive spotted lanternfly (Lycorma delicatula)","authors":"Nadège Bélouard, J. Behm","doi":"10.3389/finsc.2023.1112551","DOIUrl":null,"url":null,"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.","PeriodicalId":106657,"journal":{"name":"Frontiers in Insect Science","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Insect Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/finsc.2023.1112551","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

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.
发现了!计算机辅助个人照片识别允许入侵斑点灯笼蝇(Lycorma delicatula)的标记重新捕获
斑灯蝇是一种入侵害虫,我们缺乏个体运动数据,部分原因是个体识别困难。我们开发了一种计算机辅助方法,利用I3S软件处理的照片中的翅膀斑点图案来识别成年斑灯蝇,并通过实验室和现场验证证明了该方法的准确性。基于实验室里的176只个体,我们证明了对一只翅膀的斑点进行数字化可以100%可靠地识别个体。与个体间的变化相比,用户输入和图像角度变化引起的误差在很大程度上可以忽略不计。我们将此方法应用于标记重新捕获实验中,以评估该方法在现场的可行性。我们最初确定了84只独特的斑点灯笼蝇,其中31只在4小时后被重新捕获,还有49只新个体。我们确定,重新捕获的分析可能是基于分数的自动化,可能不需要系统的视觉两两比较。该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和不同的环境中得到验证,它将提供充足的机会收集有关斑点灯笼蝇生态的有用数据,这些数据可以极大地为管理提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信