dorothy's summer phd project plus intro to previous work
DESCRIPTION
Dorothy gives an intro seminar to her work and proposed work at Woods Hole/SMAST summer 2008TRANSCRIPT
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• Intro to harvest rules
– why an HCR?
• Intro to Dorothy
• Management model = biological + stakeholder model
– current manuscript
– GB haddock case study
• Milestones
• AFS symposium
Outline
SSB
F
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Harvest Control Rules (HCRs)decision-making framework of a management strategy currently used for some fish stocks, including:
Norwegian spring spawning herring, Northeast Arctic cod, some mackerel stocks
despite increasing practical use, theorectical research is lacking
Why an HCR? Stakeholder and mgmt objectives can be translated into such a rule
SSB
F
stable SSBconstant Fconstant catchconstant escapementprotective measure
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meet Dorothy
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(me)
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I live in
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Bergen
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but come from
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Indiana
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I like to
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&
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I support
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and I have a blog…
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So friends & family can stay updated
www.dorothydankel.blogspot.com
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and where interestedpeople cancomment on topics
www.dorothydankel.blogspot.com
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I am a biologist…
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and a PhDstudent in fisheriesmanagement
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I am very interested in the social and economic sides of fisheries
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And I want to make my work in science relevant to those it affects…
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we know there are conflicts of interest in marine resource management
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I want to explore ways conflicts of objectives in fisheries can be resolved
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Utility functions can serve as common language between stakeholders
uti
lity
my fish
uti
lity
my fish
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but, stakeholders have differentideas about how fish can be useful!
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vs.
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therefore, natural conflicts of objectives between stakeholders arise
uti
lity
healthy fishstock
uti
lity
catch
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Then Ray Hilborn wrote a paperabout fisheries conflicts…
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Fishing Effort
Benefits(utility)
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
yield
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
yieldprofit
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
employmentyieldprofit
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
employmentyieldprofit
ecosystem preservation
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
employmentyieldprofit
ecosystem preservation
zone of traditionalfisheries
management
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
employmentyieldprofit
ecosystem preservation
zone of newconsensus
zone of traditionalfisheries
management
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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Fishing Effort
Benefits(utility)
employmentyieldprofit
ecosystem preservation
zone of newconsensus
zone of traditionalfisheries
management
0 population crash
Hilborn (2007) ”Defining success in fisheries and conflicts in objectives”
Marine Policy
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zone of traditionalfisheries
management
Fishing Effort
Benefits(utility)
zone of newconsensus
0 population crash
Dorothy asked herself:
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zone of traditionalfisheries
management
Fishing Effort
Benefits(utility)
employmentyield
zone of newconsensus
0 population crash
Can I model this? Does the zone of consensus really exist?
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I thought this would make a great summer project…
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and Ulf and Mikko thought so, too!
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and Ulf and Mikko thought so, too!
Let’s bring Dorothy down to IIASA this summer.
Mmmm…Ok.
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So Dorothy stayed 90 days and 90 nights at the Schloss in Austria…
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(not exactly this one, but similar…)
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and came up with an idea that she wants to share with stakeholders, scientists and managers
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+ =Management
model
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A model that quantitively describesRay Hilborn’s discussion on conflictsof interests in fisheries
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In order to answer this question:
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Can stakeholder conflicts of objectives be reconciled in
marine fisheries management?
Dorothy J. Dankel1,2
, Ulf Dieckmann1
& Mikko Heino1,2,3
1Evolution & Ecology Program, International Institute of Applied Systems Analysis (IIASA) Laxenburg, Austria
2Pelagic Research Group, Institute of Marine Research (IMR) Bergen, Norway
3Evolutionary Fisheries Ecology Program, University of Bergen, Norway
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Utility modelPopulation model
+ =
Management modelSimplified modelling situation: don’t take terminology too seriously
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What they care about:The stakeholders:
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Fishermen ”industrial””artisanal”
Society ”employment-oriented””profit-oriented”
Conservationists
What they care about:The stakeholders:
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What they care about:The stakeholders:
Fishermen
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Society
What they care about:The stakeholders:
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Society
What they care about:The stakeholders:
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Conservationists
What they care about:The stakeholders:
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Conservationists
What they care about:The stakeholders:
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Each stakeholder has a preferencefor each of the 4 utility components
based on stakeholder consultation
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Stakeholder preferences
assumptions: stakeholder group consensus
YIELD (tons)
EMPLOYMENT(days-year)
PROFIT (€)
STOCK LEVEL(spawning stock biomass, tons)
FISHERMEN”industrial”
0.2 0 0.8 0
”artisanal” 0.4 0 0.4 0.2
SOCIETY”employment-
oriented”0.3 0.3 0.1 0.3
”profit-oriented” 0.2 0.1 0.7 0
CONSERVATIONISTS 0.1 0.1 0 0.8
uti
lity
component
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YIELD (tons)
EMPLOYMENT(days-year)
PROFIT (€)
STOCK LEVEL(spawning stock biomass, tons)
FISHERMEN”industrial”
0.2 0 0.8 0
”artisanal” 0.4 0 0.4 0.2
SOCIETY”employment-
oriented”0.3 0.3 0.1 0.3
”profit-oriented” 0.2 0.1 0.7 0
CONSERVATIONISTS 0.1 0.1 0 0.8
uti
lity
component
Stakeholder preferences
assumptions: stakeholder group consensus
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Caveat: stated stakeholder preferences do not always
equal revealed stakeholder preferences…
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So, back to Dorothy’s research question:
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So, back to Dorothy’s research question:
is there a basis for reconciling conflicting objectives?
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Results: generalized & stock-specific
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Utility components & their tradeoffswith higher fishing levels
0.0
0.5
1.0
0.0 0.5 1.0Proportion harvested
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Utility components & their tradeoffswith higher fishing levels
0.0
0.5
1.0
0.0 0.5 1.0Proportion harvested
profit
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Utility components & their tradeoffswith higher fishing levels
0.0
0.5
1.0
0.0 0.5 1.0Proportion harvested
yield
profit
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Utility components & their tradeoffswith higher fishing levels
0.0
0.5
1.0
0.0 0.5 1.0Proportion harvested
yield
profit
employment based on effort
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Utility components & their tradeoffswith higher fishing levels
0.0
0.5
1.0
0.0 0.5 1.0Proportion harvested
yield
employment based on effort
profit
stock level
employment based on catch
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
Stakeholder utilities
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"industrialfishery"
"artisanal fishery"
Fishermen
Stakeholder utilities
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
“employment-oriented"
“profit-
oriented”
Stakeholder utilities
Society
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"conservationists"
Stakeholder utilities
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"conservationists"
"industrialfishery"
"artisanal fishery"
Stakeholder utilities
“employment-oriented"
“profit-
oriented”
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"conservationists"
"industrialfishery"
"artisanal fishery"
Stakeholder utilities
“employment-oriented"
“profit-
oriented”
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"conservationists"
"industrialfishery"
"artisanal fishery"
Stakeholder utilities
“employment-oriented"
“profit-
oriented”
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"conservationists"
"industrialfishery"
"artisanal fishery"
Stakeholder utilities
“employment-oriented"
“profit-
oriented”
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-1.5
-1.0
-0.5
0.0
0.5
1.0
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90
Uti
lity
Proportion harvested
"conservationists"
"industrialfishery"
"artisanal fishery"
Stakeholder utilities
even with weight on employment , the”zone of new consensus” is clear
“employment-oriented"
“profit-
oriented”
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2 differentlife historysimulations
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Results with a min size limit
• short-lived stock tolerates more F than medium-lived stock• minimum size limits have an effect and can buffer against high F
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Conclusions
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The ”zone of new consensus” is illustratedin Dorothy’s simplified model even whenemployment is considered
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• the foundation of democracy is to include the needs of interest groups as much as possible in public policy
• the policy goal of consensus among stakeholders is realistic
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So, what’snext?
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What if I tried to model a real stock?
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Like Georges Bank haddock
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Developing Fisheries Harvest Policies: Georges Bank haddock
Dorothy J. Dankel
PhD student, fisheries management
Pelagic Research Group, Institute of Marine Research (IMR) Bergen, Norway
Supervisors: Dr. Steve Cadrin (SMAST)
Dr. Liz Brooks (NEFSC Woods Hole)
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GB haddock: Key inputs to the model
• Biological characteristics– von Bert. growth model, mortality, recruitment
• Stakeholder landscape
– different views, gears, behavior patterns?
• Objectives for fishery– what are the scientific, managerial and stakeholder goals?
Is there room for consensus?
academic single stock, multi-stakeholder management
model
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I look forward to hearing your feedback
Modelling recruitment: 2 step function
Brodziak et al (2006) Northeast Fisheries Science Center Reference Document 06-11
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Brodziak et al (2006) Northeast Fisheries Science Center Reference Document 06-11
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Brodziak et al (2006) Northeast Fisheries Science Center Reference Document 06-11
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• Week 27-31: meet & greet. Collect of biological life history parameter data for Georges Bank haddock
• Week 32-33: Be a sponge at the GARM in Woods Hole & meet more stakeholders
• Week 34: AFS (Ottawa, Canada) theme session: Harvest Control Rules: Experiences in Modelling and Application
• Week 35-40: Simulate different management rules incorporating management objectives
• Disseminate results in a manuscript to be submitted for publication
Project Milestones
SSB
F
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HCRs - is backwards the best way forwards? - South African experiences
Doug Butterworth
The Evolution of HCRs in Europe
Laurence Kell , Martin Pastoors, Beatriz Roel
Precautionary Harvest Policies and the Uncertainty Paradox
Steve Cadrin, Martin Pastoors
General properties of harvest rules: the theoretical approach
Dorothy Jane Dankel
Evaluating harvest control rules when life history varies: the case of lake whitefish in the Great Lakes
Jonathan Deroba, James Bence
Are threshold harvesting strategies evolutionarily sustainable?
Katja Enberg, Erin S. Dunlop, Mikko Heino, Ulf Dieckmann
Development, evaluation and implementation of harvest control rules for Northeast Arctic cod, haddock and saithe
Bjarte Bogstad, Harald Gjøsæter, Asgeir Aglen, Sigbjørn Mehl
Integrating stakeholder perspectives with management objectives: a modeling approach for recreational fisheries
Fiona Johnston, Robert Arlinghaus, Ulf Dieckmann
Harvest control rules and user-group agendas: making the two compatible
Joseph Powers, Elizabeth Brooks
Influence of sources of variation on the performance of a harvest control rule
James Bence, Jonathan Deroba, Weihai Liu
Long term agreed management plan for western horse mackerel; “If history repeats itself, and the unexpected always happens, how incapable must Man be of learning from experience.”
Ciaran Kelly
Harvest Control Rules: Experiencesin modelling & application AFS 2008
SSB
F
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Background slides
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Population model
(N0, …, Nam-1, Nam
, …, Namax)
immature mature
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Population model
(N0, …, Nam-1, Nam
, …, Namax)
immature mature
spawning
biological assumptions: a cod-like stock
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Population model
(N0, …, Nam-1, Nam
, …, Namax)
immature mature
spawning
Manaturalmortality
fishing mortality
Fa+
biological assumptions: a cod-like stock
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Population model
Utility components• yield (tons)• profit (€)• employment (days)• stock biomass (tons)
(N0, …, Nam-1, Nam
, …, Namax)
immature mature
spawning
Manaturalmortality
fishing mortality
Fa
Uti
lity
of
com
po
ne
nt
Component
biological assumptions: a cod-like stock
+