Department of Statistics, Iowa State University, Ames, Iowa, United States.
Natural Resource Ecology and Management, Iowa State University, Ames, Iowa, United States.
PeerJ. 2023 Feb 27;11:e14787. doi: 10.7717/peerj.14787. eCollection 2023.
The collection of fish eggs is a commonly used technique for monitoring invasive carp. Genetic identification is the most trusted method for identifying fish eggs but is expensive and slow. Recent work suggests random forest models could provide an inexpensive method for identifying invasive carp eggs based on morphometric egg characteristics. While random forests provide accurate predictions, they do not produce a simple formula for obtaining new predictions. Instead, individuals must have knowledge of the R coding language, limiting the individuals who can use the random forests for resource management. We present WhoseEgg: a web-based point-and-click application that allows non-R users to access random forests a point and click interface to rapidly identify fish eggs with an objective of detecting invasive carp (Bighead, Grass, and Silver Carp) in the Upper Mississippi River basin. This article provides an overview of WhoseEgg, an example application, and future research directions.
采集鱼卵是监测入侵鲤鱼的常用技术。遗传鉴定是识别鱼卵最可信的方法，但昂贵且耗时。最近的研究表明，基于形态特征的随机森林模型可以为识别入侵鲤鱼卵提供一种廉价的方法。虽然随机森林可以提供准确的预测，但它们并没有提供一个简单的公式来获取新的预测。相反，个体必须具备 R 编程语言的知识，这限制了可以将随机森林用于资源管理的个体。我们提出了 WhoseEgg：一个基于网络的点击式应用程序，允许非 R 用户访问随机森林——通过点击界面，可以快速识别鱼类的卵，目的是在密西西比河流域上检测入侵鲤鱼（大头鱼、草鱼和银鲤鱼）。本文概述了 WhoseEgg，包括一个应用实例和未来的研究方向。
