1. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research The overlap between Science and Advice; the example of North Sea cod. Stuart A. Reeves

2. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research The current role of science within advice Quality –Is the science good enough ? Coverage –Input required from other areas ? Science ‘Others’

3. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research Assessments and catch forecasts N 1 N 2 N 3 N 4 …. Numbers at age in the stock at year start N 1 N 2 N 3 N 4 …. Assumed Fishing Mortality N 1 N 2 N 3 N 4 …. Assumed or estimated value Years 1 to t-1 (Catch data years) Year t (Assessment year) Year t+1 (TAC year) Required Fishing Mortality + Assumed weights at age TAC

7. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research North Sea cod; mean F from past assessments

10. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research Assessment consistency (terminal F compared to 2002 assessment) Trends in Effort Iterative Fs Gamma approach Rho Method Catchability analysis Laurec- Shepherd tuning Extended Survivors Analysis (XSA)

11. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research Possible causes of observed assessment inconsistency 1.Assessment method (XSA) 2.Market sampling 3.Discarding 4.Survey data 5.Commercial CPUE data 6.Biological data 7. Misreporting 1.Worked well earlier but possibly over-conservative 2.Not a problem 3.Possible – 96 year-class 4.Data of good quality 5.May have contributed, but removal hasn’t helped 6.Not a problem 7.Likely major cause

12. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research Assessments and catch forecasts N 1 N 2 N 3 N 4 …. Numbers at age in the stock at year start N 1 N 2 N 3 N 4 …. Assumed Fishing Mortality N 1 N 2 N 3 N 4 …. Assumed or estimated value Years 1 to t-1 (Catch data years) Year t (Assessment year) Year t+1 (TAC year) Required Fishing Mortality + Assumed weights at age TAC

13. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research Evaluation of catch forecasts

15. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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. Ministry of Food, Agriculture and Fisheries Danish Institute for Fisheries Research 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.