Unsupported Browser Detected

Internet Explorer lacks support for the features of this website. For the best experience, please use a modern browser such as Chrome, Firefox, or Edge.

Fishery Catch Records Support Machine Learning-Based Prediction of Illegal Fishing off US West Coast

October 19, 2023

We explored the use of supervised machine learning analysis in a partially observed fishery to identify potentially illicit behaviors when vessels did not have observers on board.

 

Illegal, unreported, and unregulated (IUU) fishing is a major problem worldwide, often made more challenging by a lack of at-sea and shoreside monitoring of commercial fishery catches. Off the US West Coast, as in many places, a primary concern for enforcement and management is whether vessels are illegally fishing in locations where they are not permitted to fish.

This project was developed at the request of fisheries enforcement investigators, and now an automated system analyzes all new unobserved landings records to identify those in need of additional investigation for potential violations. Similar approaches informed by the spatial preferences of species landed may support monitoring and enforcement efforts in any number of partially observed, or even totally unobserved, fisheries globally.


Watson JT, Ames R, Holycross B, Suter J, Somers K, Kohler C, Corrigan B 2023. Fishery catch records support machine learning-based prediction of illegal fishing off US West Coast PeerJ 11:e16215.
https://doi.org/10.7717/peerj.16215

Last updated by Pacific Islands Fisheries Science Center on 10/23/2023