Dorothy's fisheries management dissertation


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Dorothy's fisheries management dissertation June 12, 2009, Bergen, Norway

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Dorothy's fisheries management dissertation

  1. 1. Building Blocks of Sustainability in Marine Fisheries Stakeholders, objectives, and strategies Dorothy J. Dankel
  2. 2. Introduction <ul><li>Why should we be concerned about fisheries? </li></ul>
  3. 3. Why be concerned about fisheries? FAO SOFIA 2008
  4. 4. Describing the fisheries problem “ The alarming trends in the world’s fisheries demand a fundamental change in management and fishing practices.” “ An integrated solution to the complexity of managing wild resources seems not to have been achieved.”
  5. 5. What is fisheries management? <ul><li>The quest for sustainable use of marine resources </li></ul><ul><ul><li>Objectives </li></ul></ul><ul><ul><ul><li>Dialogue between stakeholders, managers & scientists </li></ul></ul></ul><ul><ul><li>Strategies </li></ul></ul><ul><ul><ul><li>A plan how to realize objectives </li></ul></ul></ul><ul><ul><li>Tactics </li></ul></ul><ul><ul><ul><li>Regulations (mesh size, min size, area closures, etc) </li></ul></ul></ul>
  6. 6. Describing the fisheries problem “ I believe that rocket scientists have it easy... The USA was able to put a man on the moon within a decade of setting that goal. Achieving biological and economically sustainable fisheries has proven more elusive.”
  7. 7. The fishery system Charles 2001 <ul><li>Complexity & Diversity! </li></ul><ul><li>Human system is integral </li></ul>Interdisciplinary science Natural ecosystem Human system Management system
  8. 8. What are we dealing with? Scientific paradigms <ul><li>Normal science </li></ul><ul><li>Definition by Thomas S. Kuhn and elaborated in The Structure of Scientific Revolutions </li></ul><ul><ul><li>the relatively routine work of scientists experimenting within a paradigm, not challenging that paradigm </li></ul></ul><ul><ul><li>&quot;puzzle-solving” </li></ul></ul><ul><li>Post-normal science </li></ul><ul><li>Definition Silvio Funtowicz and Jerome Ravetz </li></ul><ul><ul><li>a methodology of inquiry for cases where &quot;facts are uncertain, values in dispute, stakes high and decisions urgent&quot;. </li></ul></ul><ul><ul><li>since values are embedded in science, post-normal science should integrate stakeholders in an extended peer-community </li></ul></ul>
  9. 9. Visualizing scientific paradigms Not exactly a scientific revolution, but more a response to mgmt questions Normal science Post-normal science Academic Academic & social Mono-disciplinary Trans-disciplinary Technocratic Participative Certain Uncertain Predictive Exploratory
  10. 10. <ul><li>Fisheries provide food, jobs, money & heritage for society </li></ul><ul><li>But, resource base is finite </li></ul>Motivations for fisheries management How can we manage for sustainability? Why should we be concerned about fisheries?
  11. 11. Outline of presentation: Builiding blocks of fisheries sustainability (I) Fisheries management in practice: review of 13 stocks (II) Can we reconcile stakeholder conflicts? (III) Generic properties of harvest rules (IV) Can we increase haddock yield & save the by-catch for later?
  12. 12. EVALUATING CURRENT MANAGEMENT PRACTICES <ul><li>Paper I </li></ul>
  13. 13. Evaluating fisheries management ( I )
  14. 14. Evaluating fisheries management ( I )
  15. 15. Conclusions: learning from the past ( I ) <ul><li>Problematic stocks: Greenland halibut, Southern bluefin tuna, Patagonian toothfish </li></ul><ul><ul><li>Overcapacity of low-fecund stocks </li></ul></ul><ul><ul><ul><li>Need fleet control </li></ul></ul></ul><ul><ul><li>Muliti-nation management </li></ul></ul><ul><ul><li>High market demand </li></ul></ul><ul><ul><ul><li>Market coop.  control of demand(?) </li></ul></ul></ul>
  16. 16. <ul><li>Success stocks: Alaskan sockeye salmon, South African cape hakes, Pacific halibut </li></ul><ul><li>Relative coastal isolation </li></ul><ul><ul><li>Fleet control </li></ul></ul><ul><ul><li>(single nation management) </li></ul></ul><ul><ul><li>Stakeholder involvement </li></ul></ul><ul><ul><li>leading to consensus of a </li></ul></ul><ul><ul><li>management strategy </li></ul></ul>Conclusions: learning from the past ( I )
  17. 17. INTEGRATING STAKEHOLDER OBJECTIVES <ul><li>Paper II </li></ul>
  18. 18. Stakeholders are diverse
  19. 19. Yield Profit Ecosystem Employment Examples of utility components
  20. 20. Stakeholders & diverse preferences Yield Profit Ecosystem Employment
  21. 21. ecosystem preservation Fishing Effort Benefits (utility) employment yield profit 0 population crash Motivation for Paper II Hilborn, R. (2007). &quot;Defining success in fisheries and conflicts in objectives.&quot; Marine Policy 31: 153-158. Can we quantify this zone of consensus? <ul><li>Faciltate the formation of compatible objectives towards successful management </li></ul><ul><li>Increase user participation & dialogue </li></ul><ul><ul><li>less focus on negotiations </li></ul></ul><ul><ul><li>build user buy-in </li></ul></ul>zone of new consensus zone of traditional fisheries management WHY??
  22. 22. <ul><li>Biological model </li></ul><ul><ul><li>Northeast Arctic cod </li></ul></ul><ul><ul><li>Barents sea capelin </li></ul></ul><ul><li>Socio-economic model </li></ul><ul><ul><li>Industrial fleet costs, revenues & effort/employment relationship estimated from the Norwegian Fisheries Directorate Profitability surveys (Lønnsomhetsundersøkelsen 2008) </li></ul></ul><ul><li>Stakeholder model </li></ul><ul><ul><li>5 heterogenic interest groups </li></ul></ul>Quantifying the zone of consensus: ( II )
  23. 23. Stakeholder preferences assumption: stakeholder group consensus YIELD EMPLOYMENT PROFIT STOCK LEVEL (spawning stock biomass) FISHERMEN ” industrial” 0.3 0 0.7 0 ” artisanal” 0.5 0.1 0.1 0.3 SOCIETY ” employment-oriented” 0.2 0.5 0 0.3 ” profit-oriented” 0.2 0 0.6 0.2 CONSERVATIONISTS 0.1 0.2 0.2 0.5
  24. 24. Quantifying stakeholder utilities
  25. 25. Quantifying the zone of consensus Area of joint satisfaction Most likely zone of consensus Stakeholder A Stakeholder B
  26. 26. Harvest proportion (%) Minimum size (cm) status quo Zone of Consensus Capelin Cod 70%consensus 90%consensus
  28. 28. Harvest control rule (HCR) <ul><li>An HCR is an explicit set of directions that describe how much exploitation should occur given the state of a selected parameter (i.e. spawning stock biomass) </li></ul><ul><li>Concrete tool for realizing a management strategy </li></ul><ul><li>Flexible & practical (potential platform for interdisciplinary studies) </li></ul><ul><li>Should be tailored to each stock(s) & objectives </li></ul>
  29. 29. Generic examples of HCRs Biomass Fishing mortality constant F proportional threshold escapement = parameter
  30. 30. Empirical example: North Sea herring <ul><li>1) Every effort shall be made to maintain a level of Spawning Stock Biomass (SSB) greater than the 800 000 tonnes (Blim). </li></ul><ul><li>2)Where the SSB is estimated to be above 1.3 million tonnes the Parties agree to set quotas for the directed fishery and for by‐catches in other fisheries , reflecting a fishing mortality rate of no more than 0.25 for 2 ringers and older and no more than 0.12 for 0‐1 ringers. </li></ul><ul><li>3) Where the SSB is estimated to be below 1.3 million tonnes but above 800 000 tonnes, the Parties agree to set quotas for the direct fishery and for by‐catches in other fisheries, reflecting a fishing mortality rate equal to: </li></ul><ul><ul><li>0.25 – (0.15*(1,300,000‐SSB)/500,000) for 2 ringers and older, and </li></ul></ul><ul><ul><li>0.12 – (0.08*(1,300,000‐SSB)/500,000) for 0‐1 ringers. </li></ul></ul><ul><li>4) Where the SSB is estimated to be below 800 000 tonnes the Parties agree to set quotas for the directed fishery and for by‐catches in other fisheries, reflecting a fishing mortality rate of less than 0.1 for 2 ringers and older and less than 0.04 for 0‐1ringers. </li></ul><ul><li>5) Where the rules in paragraphs 2 and 3 would lead to a TAC which deviates by more than 15% from the TAC of the preceding year the Parties shall fix a TAC that is no more than 15% greater or 15% less than the TAC of the preceding year. </li></ul><ul><li>6) Not withstanding paragraph 5 the Parties may, where considered appropriate, reduce the TAC by more than 15% compared to the TAC of the preceding year. </li></ul><ul><li>7) By‐catches of herring may only be landed in ports where adequate sampling schemes to effectively monitor the landings have been set up. All catches landed shall be deducted from the respective quotas set, and the fisheries shall be stopped immediately in the event that the quotas are exhausted </li></ul><ul><li>8) The allocation of TAC for the directed fishery for herring shall be 29% to Norway and 71% to the Community. The by‐catch quota for herring shall be allocated to the Community </li></ul><ul><li>9) A review of this arrangement shall take place no later than 31 December 2007 . </li></ul><ul><li>10) This arrangement enters in to force on 1 January 2005. </li></ul>Biomass (tons) Fishing mortality B lim 800 000 900 000 1.3 mill 0.25 0.13
  31. 31. Tips & tricks for HCRs <ul><li>If you can’t code it, it’s not good enough </li></ul><ul><ul><li>HCRs need to be tested! </li></ul></ul><ul><ul><li>Should be ”fool-proof”, not flexible for interpretations/negotiations over meanings </li></ul></ul><ul><ul><ul><li>Example: the HCR should ensure that the TAC is within sustainable levels in the long-term </li></ul></ul></ul><ul><ul><ul><ul><li>The TAC in what year? When is the data collected and when are the decisions made? </li></ul></ul></ul></ul><ul><ul><ul><ul><li>What are ”sustainable levels”? </li></ul></ul></ul></ul><ul><ul><ul><ul><li>What is the ”long-term”? 10 years? 50 years? </li></ul></ul></ul></ul>
  32. 32. Understanding harvest control rules for modern management ( III ) <ul><li>Objective: how do HCR parameters affect/react to various stock components? </li></ul><ul><li>Method: </li></ul><ul><li>apply a range of harvest rules to 2 modelled fish populations </li></ul><ul><li>look for patterns of rule behavior given a range of HCR parameter values </li></ul>
  33. 33. HCR parameter variation Biomass at time, t C 0 1:1 trigger biomass, B trigger constant catch α = 0 constant F α = C 0 /B trig constant escapement α = 1
  34. 34. <ul><li>NOTE: Very difficult to visualize 4 dimensions </li></ul><ul><li>Over from a scientific presenation to a stakeholder presention </li></ul>Evaluating generic HCRs: output according to parameter levels
  35. 35. Evaluating generic HCRs: output according to parameter levels Lowest CV Lowest biol. risk All rules the same Lowest CV Highest catch
  36. 36. Preliminary summary ( III ) <ul><li>We have developed a toolbox to which we can add (recruitment periodicities, more uncertainties, etc.) </li></ul><ul><li>3 parameter model covers a large range of HCRs </li></ul><ul><ul><li>Can scan over and get a lot of information & identify interesting areas </li></ul></ul><ul><li>For the current parameterization: </li></ul><ul><li>Constant harvest rate is best in regards to high & relatively stabile catches </li></ul><ul><li>” Constant catch” gives lowest CV around 60-75% of maximum catches & is best in regards to avoiding biologicial risk </li></ul>
  38. 38. Study area: Georges Bank, NW Atlantic
  39. 39. Fig. 2. Status of 19 groundfish stocks in 2007 with respect to F MSY and B MSY or their proxies based on the GARM III review (NOAA 2008). 2007 Status of Northeast groundfish Georges Bank
  40. 40. Separator trawl Ruhle trawl Otter trawl Trawl types for NE groundfishery
  41. 41. <ul><li>based on Mixed-Species Yield-per-Recruitment Analyses Accounting for Technological Interactions (Murawski 1984) </li></ul><ul><li>Program non-equilibrium single stock projection models using population estimates for 9 groundfish stocks from 2004 </li></ul><ul><li>Use catchability coefficients to integrate single stock projection models to produce a mixed-species model </li></ul>Jacobson et al. Mixed-species yield model
  42. 42. An interdisciplinary aid to inform decision makers ( IV ) <ul><li>Problem: </li></ul><ul><ul><li>Georges Bank haddock has recovered, but current legislation prevents fishing it (managing by the weakest link) </li></ul></ul><ul><li>Objective: </li></ul><ul><ul><li>Assess the bio-socio-economic consequences of fishing with new more selective trawls </li></ul></ul><ul><li>Methods: </li></ul><ul><ul><li>a model incorporating dynamic aspects of single-spp. projections with gear interactions for mixed-spp. evaluations. </li></ul></ul><ul><ul><li>extends a traditional (but seldom applied) mixed-spp. yield-per-recruit model by incorporating stock–recruitment relationships Jacobson, N. and S. Cadrin (2008). Projecting Equilibrium, Mixed-species Yield of New England Groundfish. ICES ASC. Halifax, Canada. ICES CM 2008/I:02. </li></ul></ul>
  43. 43. Scenario results for haddock ( IV ) $$
  44. 44. Summary: Building blocks of sustainability for fisheries management <ul><li>I have outlined some techniques that can be used to promote more sustainable fisheries through 4 papers: </li></ul><ul><ul><li>Evaluates & benchmarks current management situations </li></ul></ul><ul><ul><li>Quantification of stakeholder objectives for clarification of consensus in management </li></ul></ul><ul><ul><li>Understanding properties of harvest control rules to strengthen the scientific base of this modern management tool </li></ul></ul><ul><ul><li>Facilitating the bio-socio-economic </li></ul></ul><ul><ul><li>evaluation of new gear technology </li></ul></ul>
  45. 45. Take home messages <ul><li>Stakeholder conflicts may not be so conflicting as thought </li></ul><ul><ul><li>our modelled cod had stronger consensus than capelin </li></ul></ul><ul><ul><li>room for an integrated solution in management </li></ul></ul><ul><li>Bio-socio-economic models shed light on utilities that matter to society & reflect the fishery system in a post-normal science paradigm </li></ul><ul><ul><li>the data are there, use them! </li></ul></ul><ul><li>For true sustainability, scientific rationale used in management should be understood by its users </li></ul><ul><ul><li>dialogue, observability & scientific facilitation </li></ul></ul><ul><ul><li>harvest rules as an interdisciplinary tool </li></ul></ul><ul><ul><li>scenario mapping sparks & assists the dialogue </li></ul></ul>
  46. 46. Acknowledgements <ul><li>Funding : the Norwegian Research Council & an extra grant from IIASA through the EU project FishACE </li></ul><ul><li>Advising : Mikko Heino , Dankert Skagen , Øyvind Ulltang, Ulf Dieckmann, Steve Cadrin </li></ul><ul><li>Other collaboration & discussions : Pelagic research group and colleagues at IMR, EvoFish research group (UiB), Nikki Jacobson, Steve Correia, Brian Rothschild, Dan Georgianna, Liz Brooks, Paul Rago, Peter Gullestad, ICES colleagues (SGMAS, Galway conference on Management Strategies), IIASA colleagues, & attendees at the Harvest Control Rule Sympsoium (AFS 2008) </li></ul>
  47. 48. Stakeholder utility results using 2 regulations Zone of consensus Harvest proportion (%) Minimum sIze (cm) Zone of consensus = minimum stakeholder whinge Use more imaginary example
  48. 49. Ruhle trawl results from Beutel et al. 2006
  49. 50. HCR parameter variation Biomass at time, t C 0 1:1 similar constant catch α = 0 constant F α = C 0 /B trig constant escapement α = 1 trigger biomass, B trigger
  50. 51. HCR parameter variation Biomass at time, t C 0 1:1 similar similar constant catch α = 0 constant F α = C 0 /B trig constant escapement α = 1 trigger biomass, B trigger
  51. 52. Not a simple task to visualize 4 dimensions Over from a scientific to a stakeholder presentation Evaluating generic HCRs: output according to parameter levels Lowest CV Lowest biol. risk compromise btwn building up stock and protecting with thres. B All rules the same Lowest CV Highest catch Too much protection that it is hard for B to > thres. B
  52. 53. Scenario results for all species ( IV ) $$
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