Dorothy's fisheries management dissertation

Building Blocks of Sustainability in Marine Fisheries

Stakeholders, objectives, and strategies

Dorothy J. Dankel

Introduction

Why should we be concerned about fisheries?

Why be concerned about fisheries?

FAO SOFIA 2008

“The alarming trends in the world’s fisheries demand a fundamental change in management and fishing practices.”

Describing the fisheries problem

“An integrated solution to the complexity of managing wild resources seems not to have been achieved.”

What is fisheries management?

• The quest for sustainable use of marine resources1. Objectives

Dialogue between stakeholders, managers & scientists

2. Strategies A plan how to realize objectives

3. Tactics Regulations (mesh size, min size, area

closures, etc)

“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.”

Describing the fisheries problem

The fishery system Charles 2001

•Complexity & Diversity!•Human system is integral

Interdisciplinary science

Natural ecosystem

Human system

Management system

What are we dealing with? Scientific paradigms

Normal scienceDefinition by Thomas S. Kuhn

and elaborated in The Structure of Scientific Revolutions– the relatively routine work of

scientists experimenting within a paradigm, not challenging that paradigm

– "puzzle-solving”

Post-normal scienceDefinition Silvio Funtowicz and

Jerome Ravetz– a methodology of inquiry for

cases where "facts are uncertain, values in dispute, stakes high and decisions urgent".

– since values are embedded in science, post-normal science should integrate stakeholders in an extended peer-community

Normal science Post-normal science

Academic Academic & social

Mono-disciplinary Trans-disciplinary

Technocratic Participative

Certain Uncertain

Predictive Exploratory

Visualizing scientific paradigms

Not exactly a scientific

revolution, but more a

response to mgmt questions

• Fisheries provide food, jobs, money & heritage for society

• But, resource base is finite

Motivations for fisheries management

How can we manage for sustainability?

Why should we be concerned about fisheries?

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 theby-catch for later?

EVALUATING CURRENT MANAGEMENT PRACTICES

Paper I

Evaluating fisheries management (I)

Evaluating fisheries management (I)

Conclusions: learning from the past (I)

Problematic stocks: Greenland halibut, Southern bluefin tuna, Patagonian toothfish

• Overcapacity of low-fecund stocks

Need fleet control• Muliti-nation management• High market demand

Market coop. control of demand(?)

Success stocks: Alaskan sockeye salmon, South African cape hakes, Pacific halibut

• Relative coastal isolation

• Fleet control (single nation management)

• Stakeholder involvement leading to consensus of a management strategy

Conclusions: learning from the past (I)

INTEGRATING STAKEHOLDER OBJECTIVES

Paper II

Stakeholders are diverse

YielYieldd

ProfitProfit Ecosystem Ecosystem EmploymentEmployment

Examples of utility components

Stakeholders & diverse preferences

YieldYield ProfitProfit Ecosystem Ecosystem EmploymentEmployment

ecosystem preservation

Fishing Effort

Benefits(utility)

employmentyieldprofit

zone of new consensus

zone of traditional fisheries

management

0 population crash

Motivation for Paper IIHilborn, R. (2007). "Defining success in fisheries and conflicts in objectives." Marine Policy 31: 153-158.

Can we Can we quantify this quantify this zone of zone of consensus?consensus?

• Faciltate the formation of compatible objectives towards successful management • Increase user participation & dialogue

- less focus on negotiations- build user buy-in

WHY?

?

• Biological model– Northeast Arctic cod– Barents sea capelin

• Socio-economic model– Industrial fleet costs, revenues & effort/employment

relationship estimated from the Norwegian Fisheries Directorate Profitability surveys (Lønnsomhetsundersøkelsen 2008)

• Stakeholder model– 5 heterogenic interest groups

Quantifying the zone of consensus: (II)

Stakeholder preferences

YIELD EMPLOYMENT PROFIT STOCK LEVEL(spawning stock

biomass)

FISHERMEN”industrial” 0.3 0 0.7 0

”artisanal” 0.5 0.1 0.1 0.3SOCIETY

”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

assumption: stakeholder group consensus

Quantifying stakeholder utilities

Quantifying the zone of consensus

Area of joint satisfaction

Most likely zone of consensus

Stakeholder A Stakeholder B

Harvest proportion (%)

Min

imum

siz

e (c

m)

status quo

Zone of Consensus

Capelin Cod

70%consensus

90%consensus

HARVEST RULES AS A TOOL TOWARDS A MANAGEMENT STRATEGY

Paper III

Harvest control rule (HCR)

• 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)

• Concrete tool for realizing a management strategy• Flexible & practical (potential platform for interdisciplinary

studies)• Should be tailored to each stock(s) & objectives

Generic examples of HCRs

BiomassFish

ing

mor

talit

y

constant F proportional threshold

escapement

= parameter

1) Every effort shall be made to maintain a level of Spawning Stock Biomass (SSB) greater than the 800 000 tonnes (Blim). 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. 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: 0.25 – (0.15*(1,300,000‐SSB)/500,000) for 2 ringers and older, and

0.12 – (0.08*(1,300,000‐SSB)/500,000) for 0‐1 ringers. 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. 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. 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. 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 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 9) A review of this arrangement shall take place no later than 31 December 2007 .

10) This arrangement enters in to force on 1 January 2005.

Empirical example: North Sea herring

Biomass (tons)

Fishing mortality

Blim 800 000

900 000 1.3 mill

0.25

0.13

Tips & tricks for HCRs

• If you can’t code it, it’s not good enough– HCRs need to be tested!– Should be ”fool-proof”, not flexible for

interpretations/negotiations over meanings• Example: the HCR should ensure that the TAC is

within sustainable levels in the long-term– The TAC in what year? When is the data

collected and when are the decisions made?– What are ”sustainable levels”?– What is the ”long-term”? 10 years? 50 years?

Understanding harvest control rules for modern management (III)

Objective: how do HCR parameters affect/react to various stock components?

Method: • apply a range of harvest rules to 2 modelled fish

populations• look for patterns of rule behavior given a range of HCR

parameter values

HCR parameter variation

Biomass at time, t

C0

1:1trigger biomass, Btrigger

0 trigger( )t tTAC C B B

constant catch α = 0constant F α = C0/Btrig

constant escapement α = 1

0 triggertrigger

;tt

BC B BB

NOTE: Very difficult to visualize 4 dimensionsOver from a scientific presenation to a stakeholder

presention

Evaluating generic HCRs: output according to parameter levels


Lowest CV Lowest biol. risk

All rules the same

Lowest CVHighest catch

Preliminary summary (III)

• We have developed a toolbox to which we can add (recruitment periodicities, more uncertainties, etc.)

• 3 parameter model covers a large range of HCRs– Can scan over and get a lot of information & identify

interesting areas

For the current parameterization:• Constant harvest rate is best in regards to high & relatively

stabile catches• ”Constant catch” gives lowest CV around 60-75% of maximum

catches & is best in regards to avoiding biologicial risk

PUTTING IT TOGETHER: MAPPING OUT MANAGEMENT SCENARIOS FOR GEORGES BANK

Paper IV

Study area: Georges Bank, NW Atlantic

Fig. 2. Status of 19 groundfish stocks in 2007 with respect to FMSY and BMSY or their proxies based on the GARM III review (NOAA 2008).

2007 Status of Northeast groundfish

Georges Bank

Separator trawl

Ruhle trawlOtter trawl

Trawl types for NE groundfishery

• based on Mixed-Species Yield-per-Recruitment Analyses Accounting for Technological Interactions (Murawski 1984)

• Program non-equilibrium single stock projection models using population estimates for 9 groundfish stocks from 2004

• Use catchability coefficients to integrate single stock projection models to produce a mixed-species model

Jacobson et al. Mixed-species yield model

An interdisciplinary aid to inform decision makers (IV)

Problem:– Georges Bank haddock has recovered, but current

legislation prevents fishing it (managing by the weakest link)

Objective:– Assess the bio-socio-economic consequences of

fishing with new more selective trawlsMethods:

– a model incorporating dynamic aspects of single-spp. projections with gear interactions for mixed-spp. evaluations.

– 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.

Scenario results for haddock (IV)

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Summary: Building blocks of sustainability for fisheries management

I have outlined some techniques that can be used to promote more sustainable fisheries through 4 papers:

I. Evaluates & benchmarks current management situationsII. Quantification of stakeholder objectives for clarification of

consensus in managementIII. Understanding properties of harvest control rules to

strengthen the scientific base of this modern management tool

IV. Facilitating the bio-socio-economic evaluation of new gear technology

Take home messages• Stakeholder conflicts may not be so conflicting as thought

– our modelled cod had stronger consensus than capelin– room for an integrated solution in management

• Bio-socio-economic models shed light on utilities that matter to society & reflect the fishery system in a post-normal science paradigm

– the data are there, use them!

• For true sustainability, scientific rationale used in management should be understood by its users

– dialogue, observability & scientific facilitation– harvest rules as an interdisciplinary tool– scenario mapping sparks & assists the dialogue

Acknowledgements

Funding: the Norwegian Research Council & an extra grant from IIASA through the EU project FishACE

Advising: Mikko Heino, Dankert Skagen, Øyvind Ulltang, Ulf Dieckmann, Steve Cadrin

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)

Zone of Zone of consensusconsensus

Harvest proportion (%)

Min

imum

sIz

e (c

m)

Stakeholder utility results using 2 regulations

Zone of consensus = minimum

stakeholder whinge

Use more imaginary example

Ruhle trawl results from Beutel et al. 2006


Biomass at time, t

C0

1:10 trigger( )t tTAC C B B



similar

trigger biomass, Btrigger


Biomass at time, t

C0

1:10 trigger( )t tTAC C B B



similar

similar

trigger biomass, Btrigger

Not a simple task to visualize

4 dimensionsOver from a scientific to

a stakeholder presentation


Lowest CV Lowest biol. risk

compromise btwn building up stock

and protecting with thres. B

All rules the same

Lowest CVHighest catch

Too much protection that it is hard for B to > thres. B

Scenario results for all species (IV)

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Education

Dorothy's fisheries management dissertation