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Dr. James Hastie Manager, Population Ecology Program FRAM Division

A Brief Review of the Evolution of Data-Limited Assessments for Pacific Coast Groundfish Species since 2007. Dr. James Hastie Manager, Population Ecology Program FRAM Division. NW Fisheries Science Center. April 22,2013. Outline. Motivations Catch-only methods

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Dr. James Hastie Manager, Population Ecology Program FRAM Division

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  1. A Brief Review of the Evolution of Data-Limited Assessments for Pacific Coast GroundfishSpecies since 2007 • Dr. James Hastie • Manager, Population Ecology Program • FRAM Division • NW Fisheries • Science Center • April 22,2013

  2. Outline Motivations Catch-only methods Development of extended methods Outcomes from prior SSC reviews of methods

  3. Beginning in 2007 Magnuson-Stevens Act Reauthorization: End Overfishing NMFS calls for all managed species to be covered by Overfishing Limits and Annual Catch Limits (ACLs) Dick and MacCall Develop DB-SRA and DCAC In 2009, Pacific Council uses DB-SRA/DCAC assessment results to improve the 2011-12 specification of OFLs for unassessed species (or the assemblages in which they are managed) Pacific Council asks the SSC to review these methods

  4. Review of Data-poor Assessment Methods Held in April, 2011 Examination of data requirements, assumptions, suitability conditions, robustness Primary focus on DB-SRA and DCAC Secondary focus on extended DB-SRA and Stock Synthesis implementation of similar methods Some data-moderate methods were proposed, but not accepted Continued use of DB-SRA and DCAC was recommended Research recommendations were identified

  5. Next Steps These data-poor methods do not provide adequate estimates of stock status Knowledge of stock status is key to preventing stocks from becoming depleted and rebuilding ones that have become so PFMC faces two issues: Species with very limited data Species with greater data availability, but lower priority for inclusion in the intensive benchmark STAR process Council asks SSC to review extensions of Data-poor approaches in which status can be estimated and harvest guidance may be improved

  6. Review of Data-moderate Assessment Methods Held in June, 2012 Review improvements to Data-poor methods Review progress on XDB-SRA and exSSS Compare results from these methods to existing benchmark assessments Panel endorsed XDB-SRA and exSSS for use in Data-moderate assessments Recommendations: more simulation testing, improve specification of inputs, explore treatment of uncertainty, use STAR process for first review

  7. Other Data-moderate Methods Agreements Include only catch and indices of abundance (from survey or fishery data) Avoid need to evaluate model fits to composition data Measures of uncertainty from exSSS should be based on SIR Show the transition from Priors to Posteriors in XDB-SRA Use recent standard methods of treating survey data Use new GLMM; explore alt.s; Triennial: omit 1977; split time series Inconsistency with survey data seen as principle means of identifying poor model performance Rec indices beyond 2000 should address mgmt. changes Use corrected H&L Survey

  8. Range of Assessments

  9. Use of D-M Assessment Results

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