1. Harvest control rules in context – limits, possibilities and the ICES experience Poul Degnbol IFM, Denmark & ICES Workshop on Harvest Control Rules for Sustainable Fisheries Management 13-15 September 2004, Bergen, Norway

2. Trailer The context of Harvest control rules Harvest control rules and reference points Evaluation criteria Evaluation approach How to get there

3. The context of Harvest control rules

4. Why harvest control rules? Harvest control rules is a fix to avoid the annual dealing and wheeling during fisheries negotiations Harvest control rules is an element in a policy to move the focus in fisheries management from tactical (annual) decisions to decisions regarding longer term goals

5. Harvest control rules is the tactical element of a management strategy Management strategies include –Decision (explicit or implicit) on longer term management objectives and performance criteria –Decision on the relevant knowledge base for tactical management decisions –Decision on implementation framework (mainly input or output control etc.) –Implementation modes such as a management plan including Sanctions Rules for tactical management decisions regarding the fisheries in the current or coming fishing season (harvest control rules) Monitoring requirements

6. The fisheries management system

7. Strategic decision system /Management strategy Relevant Knowledge Implementation framework Objectives Performance criteria Harvest control rule If state=xx then do yy Tactical decision system Corrections to objectives (‘flexibility’) Accept of knowledge Management plan Monitoring requirements SanctionsSociety: Fleet adaptation Nature: Variation within regime Regime shifts Fishery system

8. Strategic decision system /Management strategy Relevant Knowledge Implementation framework Objectives Performance criteria Harvest control rule If state=xx then do yy Tactical decision system Corrections to objectives (‘flexibility’) Accept of knowledge Management plan Monitoring requirements SanctionsSociety: Fleet adaptation Nature: Variation within regime Regime shifts Fishery system

9. The normative string - Objectives and performance Achievement of explicit and implicit objectives –Sustainability Maintenance of reproductive capacity Delivery of ecosystem services –Societal benefits High long term yields Social and economic objectives? –Justice/Equity Performance criteria –Robustness –Cost efficiency –Transparancy and legitimacy

10. The regulatory string – implementation means Implementation means – basic choice of main instruments –Output - TACs –Input – effort –Technical incl closed areas The choice of implementation means defines options for distributions of benefits Once implementation means have been chosen this may become a nearly irreversible choice due to the distributional implications (Example – CFP)

11. The cognitive string – Predictive- Adaptive balance? Uncertainty is here to stay! Predict or learn by experience from implementation Passive adaptivity: predict and correct through next years prediction –Requires either that relevant reference points can be estimated and that predictions make sense technically and operationally Active adaptivity: explore a range of exploitation ranges and adapt –Stocks for which data series short or only one state known: explore production dynamics –Target reference points for stocks where biological interactions are important or only low productivity seen –Regime shifts? –Stocks where we are uncertain about present state or stock dynamics Adaptive elements should be considered for several stocks in the NE Atlantic where dynamics is poorly known Dont hardwire HCR parameters if it can be avoided –identify conceptual basis –identify processes to modify

12. The cognitive string – what is relevant, valid and sufficient knowledge? The relevance of knowledge relates to objectives The validity of knowledge relates to acceptance by stakeholders Sufficency of knowledge relates to the desired robustness of the management strategy

13. Harvest control rules cannot be developed or evaluated independently of their normative, cognitive and regulatory context. HCRs must always be seen as one element in a management institution which is subject to external constraints and includes a range of decisions and assumptions regarding objectives, knowledge and implementation

14. Distortions in the normative, cognitive or regulatory embeddedness of HCRs in the management institution will lead to failure to achieve objectives and ultimately to conflict

15. If harvest control rules ar used as a fix to solve problems in the decision making process they will fail – HCRs will only work if the existing problems are addressed simultaneously. Harvest control rules should only be considered as elements in a management strategy which simultaneously addresses the cognitive, normative and regulatory issues which are external to the HCR but conditional for its operation

16. Strategic decision system /Management strategy Relevant Knowledge Implementation framework Objectives Performance criteria Harvest control rule If state=xx then do yy Tactical decision system Corrections to objectives (‘flexibility’) Accept of knowledge Management plan Monitoring requirements SanctionsSociety: Fleet adaptation Nature: Variation within regime Regime shifts Fishery system

17. HCR parameters

18. Limit points –Relates to conservation (reproductive capacity, ecosystem services) Target points –Relates to societal benefits Trigger points –Technical signpost for decisions

19. Default current HCR TAC decision based on two-year catch forecast based on stock size one year prior to fishing season Limits: Blim and derived from this Flim Trigger points: PA reference points No target reference points

20. PA reference points are only relevant as trigger points within current default HCR In other management strategies present PA reference points may be irrelevant With the introduction of an extended range of management strategies we will need to change the advice framework to link to management plans beyond present default option

21. The present pa advisory framework is just a special case for one strategy variant

22. HCR evaluation criteria

23. Management strategy evaluation criteria Achievement of explicit and implicit objectives –Sustainability Maintenance of reproductive capacity Delivery of ecosystem services –Societal benefits High long term yields Social and economic objectives? –Justice/equity Performance criteria –Robustness –Cost efficiency –Transparanecy and legitimacy

24. The PA and HCR evaluation The precautionary approach: –Robustness of management regime to uncertainties regarding achievement of sustainability –Sustainability: reproductive capacity and ecosystem services Robustness to –Data uncertainty May be estimated but... –Model uncertainty Sensitivity to model choice –Implementation uncertainty Sensitivity – historical performance Bias – nonreporting and discards –Uncertainty about future state of nature Sensitivity – S/R parameters, growth, M, maturity

25. Performance evaluation Robustness Cost efficiency –Data requirements –Assessment costs – complexity, updates –Implementation requirements (MCS) Transparency –Methods acceptance – complex, intuitive? –Process open to public scrutiny

26. Evaluation approach

27. HCR evaluation from objectives Objectives Performance criteria Evaluation Management regime Harvest control rule and its parameters such as trigger and target points

28. HCR evaluation by trial and error Objective achievement Performance Evaluation Harvest control rule and its parameters such as trigger and target points Management regime

29. Uncertainty in HCR evaluations Robustness to –Data uncertainty May be estimated but... –Model uncertainty Sensitivity to model choice –Implementation uncertainty Sensitivity – historical performance Bias – nonreporting and discards –Uncertainty about future state of nature Sensitivity – S/R parameters, growth, M, maturity All these should be included in a HCR evaluation Two approaches: –stochastic modelling when uncertanties can be estimated –Sensitivity analysis when uncertainties cannot be estimated or modelled Stochastic modelling on basis of estimates of uncertainty: –Data uncertainty Sensitivity analysis –model uncertainty –implementation uncertainty –uncertainty about future state of nature

30. How to get there

31. ICES transition Develop conceptual base for management strategy evaluations incl HCR evaluations, include in form of advice framework (2005) SG to provide tools for WGs for HCR and target ref point candidates in 2005 – initially based on trial-and-error framework 2005 forward –Dialogue with clients about management strategies – to develop HCRs in context –modify advisory framework to relate to management strategies – from pa reference points to management strategies –Develop appropriate management strategy evaluation tools

32. Short term problem in implementation The present pa framework is percieved as universally applicaple independently of management strategies Communication issue: develop and accept management plans which are precautionary relative to sustainability concerns but do not relate to the present pa reference point framework except for Blim.

33. Longer term – changed advice delivery mechanisms We need to move from ’Vatican’ model (smoke out of chimney after closed non-transparent process) –To ’Socratic’ model - exploratory, dialogue based search evaluation of options Requires that advice is presented as a wider range of options with implications and that stakeholders & advisors spend considerable time exploring these Handling unceratinties and risks should be a shared responsibility

34. Strategic decision system /Management strategy Relevant Knowledge Implementation framework Objectives Performance criteria Harvest control rule If state=xx then do yy Tactical decision system Corrections to objectives (‘flexibility’) Accept of knowledge Management plan Monitoring requirements SanctionsSociety: Fleet adaptation Nature: Variation within regime Regime shifts Fishery system