WhoseEgg: classification software for invasive carp eggs

Abstract

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 via 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.

Keywords

• Bigheaded carp
• Invasive species
• Machine learning
• Morphometrics
• R Shiny
• Random forests