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The overlap between Science and Advice; the example of North Sea cod. Stuart A. Reeves. The current role of science within advice. Quality Is the science good enough ? Coverage Input required from other areas ? Science ‘Others’. Background. EU project PKFM

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The overlap between Science and Advice; the example of North Sea cod. Stuart A. Reeves


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    1. The overlap between Science and Advice; the example of North Sea cod. Stuart A. Reeves

    2. The current role of science within advice • Quality • Is the science good enough ? • Coverage • Input required from other areas ? • Science • ‘Others’

    3. Background • EU project PKFM • Policy and Knowledge in Fishery Management • WP4 : “Evaluation of the methodology to produce the research based scientific advice” • North Sea cod case-study • Assessments by ICES Working Group on the Assessment of Demersal Stocks in the North Sea and Skagerrak (WGNSSK) • How well does the WG do it’s job ?

    4. North Sea Cod • Well-sampled stock • Data since 1963 • Assessments since 1974 • Caught in an international mixed demersal fishery • Haddock/Whiting/Saithe/Plaice/Sole • Management primarily by TAC • Additional measures/recovery plans since 2001

    5. Assessment and Advice • “Assessment” • Describes current state of stock • “Advice” • Proposes what should be done about it • Form of advice • Determined by tools in use by managers • North Sea cod • Catch-advice (TAC)

    6. Assumed or estimated value Numbers at age in the stock at year start N1 N2 N3 N4 …. Required Fishing Mortality + Assumed weights at age TAC Year t (Assessment year) Year t+1 (TAC year) Years 1 to t-1 (Catch data years) Assessments and catch forecasts N1 N2 N3 N4 …. N1 N2 N3 N4 …. AssumedFishing Mortality

    7. To evaluate the TAC advice process we need to consider : • The Estimation component • Population numbers and fishing mortalities • The “assessment” • The Assumed components • Assumed fishing mortality in assessment year • The “technical” component • Assumed weight at age in TAC year • The “biological” component

    8. Assessment evaluation • A stock assessment performs well if … • All data tell the same story about the stock • The stock trends seen in this year’s assessment are consistent with previous assessments • [The results correspond to ‘reality’] • We require a consistent picture of the stock • A TAC is set to reach a certain fishing mortality • Good performance if TAC results in this fishing mortality.

    9. North Sea cod; mean F from past assessments

    10. Trends in Effort Laurec- Shepherd tuning Gamma approach Catchability analysis Rho Method Iterative Fs Extended Survivors Analysis (XSA) Assessment consistency (terminal F compared to 2002 assessment)

    11. Assessment method (XSA) Market sampling Discarding Survey data Commercial CPUE data Biological data Misreporting Worked well earlier but possibly over-conservative Not a problem Possible – 96 year-class Data of good quality May have contributed, but removal hasn’t helped Not a problem Likely major cause Possible causes of observed assessment inconsistency

    12. Assumed or estimated value Numbers at age in the stock at year start N1 N2 N3 N4 …. Required Fishing Mortality + Assumed weights at age TAC Year t (Assessment year) Year t+1 (TAC year) Years 1 to t-1 (Catch data years) Assessments and catch forecasts N1 N2 N3 N4 …. N1 N2 N3 N4 …. AssumedFishing Mortality

    13. Catch forecasts • Inputs • Stock numbers from VPA • Assumed F during current year • Assumed weights at age during TAC year • Recruitment during current & TAC years • Evaluation • Prepare ‘reference forecasts’ using observed inputs • Compare WG forecasts with reference values • Stepwise comparison of inputs

    14. Evaluation of catch forecasts

    15. Assessment & Advice – performance summary • Assessment • Model “old technology” • Recent biases probably due to misreporting • Forecast • Always over-optimistic • Stock numbers • Recruitment estimation • Weights at age

    16. Causes of problems • Misreporting • Industry response to restrictive TACs • Over-estimation of recruitment • Software problem • Average not appropriate due to trend • Over-estimation of growth • Average not appropriate due to trend • Stagnation in model development • Drift from ‘state of the art’ to ICES default

    17. How could WG have addressed problems ? • Misreporting • Additional analyses • ‘Guesstimate’ quantities • Better contact with fishing industry ? • Over-estimation of growth and recruitment • Correctable if detected • More input from biological research ? • Lack of model development • Make assessment a less routine task ??

    18. Some comments… • Uncertainty ? • No • Best available science ? • No recent model development • No uncertainty estimation • Form of advice is part of the problem • TACs => Misreporting • Forecast amplifies assessment problems • When management works assessment/forecast doesn’t…

    19. The future role of science in advice ? • Improved review process • How is HCR performing • Identify and address problems • Wider range of expertise • Need for a more dynamic scientific environment • Recognition that there is more to ‘science’ than just the assessment • Closer and more systematic contact with industry.