UW Aquatic & Fishery Sciences Quantitative Seminar

Chris Free

Graduate Student, Rutgers University

The refined ORCS approach: a catch-based method for estimating stock status and catch limits for data-poor fish stocks

Abstract

The "Only Reliable Catch Stocks" (ORCS) Working Group approach to data-poor fisheries stock status and catch limit estimation has been used by U.S. fisheries managers but has yet to be fully evaluated. The ORCS approach estimates stock status using a fourteen question "Table of Attributes" and the overfishing limit by multiplying a historic catch statistic by a scalar based on the estimated status. We evaluated the performance of the approach by applying it to 185 stocks with data-rich stock assessments and comparing predictions of the status and overfishing limit from the ORCS approach with the assessment model estimates. The approach classified all but three stocks as fully exploited indicating that it is a poor predictor of status and should not be used by managers. We refined the original ORCS approach by: (1) developing a more predictive model of stock status using boosted classification trees; and (2) identifying the historic catch statistics and scalars that best estimate overfishing limits using assessment model data. The refined ORCS approach correctly classified 72% of all stocks and 51% of overexploited stocks in the training dataset and 75% of all stocks and 60% of overexploited stocks in the independent test dataset. The refined approach performed better than other widely used catch-only models. However, the overfishing limits estimated by the refined approach would further deplete overexploited stocks without the use of conservative catch scalars to buffer against classification uncertainty. Conservative catch scalars reduce the probability of overfishing overexploited stocks to 50%, the U.S. legal maximum, but would concomitantly underutilize many underexploited and fully exploited stocks. The refined ORCS approach may therefore be useful when other methods are not possible or appropriate and some risk of underexploitation is acceptable. We provide a web tool for managers to implement the refined approach.