Catch and Length Models in the Stock Synthesis Framework: Expanded Application to Data-Moderate Stocks

Many fisheries in the world are data-moderate, with data types (e.g., total removals, abundance indices, and biological composition data) of varied quality limited time series or representative samples) available data. Integrated stock assessments useful tools for data-moderate as they can include all information, be updated due to availability more information over time, directly test inclusion exclusion specific types. This study uses simulation testing systematic reduction from US West Coast benchmark examine performance Stock Synthesis catch length (SS-CL) compositions only. The various life histories, recruitment variabilities, scenarios found that correctly specified SS-CL estimate unbiased key population quantities such status little 1 year although 5 years may reliable. error is decreased an increase sample size removal often caused large model deviations outputs compared other sources, indicating importance integrated models. Models data, excluding indices age composition, generally provided informative estimates relative reference model, most falling within CIs model. results analysis indicated potentially viable USA, thus reducing precautionary buffers on limits many stocks previously assessed a lower tier using catch-only could also applied around world, maximizing use via well tested, multifeature benefits SS.