Fishery catch records support machine learning-based prediction of illegal fishing off US West Coast.

ABSTRACT: 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. 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. We built classification models (random forest and gradient boosting ensemble tree estimators) using labeled data from nearly 10,000 fishing trips for which we had landing records (i.e., catch data) and observer data. We identified a set of varia

SUBMITTER: Watson JT 

PROVIDER: S-EPMC10590572 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature