pacific hake management strategy evaluation
DESCRIPTION
Pacific Hake Management Strategy Evaluation. Joint Technical Committee Northwest Fisheries Science Center, NOAA Pacific Biological Station, DFO School of Resource and Environmental Management, SFU. Main Results. - PowerPoint PPT PresentationTRANSCRIPT
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Pacific Hake Management Strategy Evaluation
Joint Technical CommitteeNorthwest Fisheries Science Center, NOAA
Pacific Biological Station, DFOSchool of Resource and Environmental Management, SFU
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Main Results
- Default harvest control rule results in 2021-2030 median average depletions of ~28% for all cases and mean average depletions of ~36%.
- Median average catches range 217-284 t- Incorrect year class estimates often
produce forecast errors- Annual vs Biennial survey benefits are
marginal
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Outline
• Introduction• Review the MSE workplan objectives• Methods• Example simulations • Describe the behavior of the existing management
procedure• Performance metrics • Summary figures • Discussion and Conclusion
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Introduction
Stock Assessment
Data
Harvest control rule
Catch recommendation
Catch that comes out of water
Examples of some decisions
Management Procedure
-survey design/frequency-sampling protocols-converting backscatter to index
- sensitivities-selectivity shape-obs/process error-areas/gender/seasons
- mathematical form- target harvest rate- percentiles
- Maximum catch- Carry-over
- spatial restrictions- individual quotas- other opportunities
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Management strategy evaluation
Fishery objectivesStakeholders
Managers
Management procedureHistorical Data
Future dataAssessment method
Decision-rule
EvaluationOperating model scenarios
Performance measuresClosed-loop simulation
Peer-review
CommunicationPerformance
Trade-offsRevision
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MSE Workplan Objectives
• Introduce the MSE process to Pacific hake– Computer simulation (most work in 2012)– Consultation (limited in 2012, but more in 2013+…)
• Base simulations on the 2012 base model and current harvest control rule to evaluate:– Annual acoustic surveys– Bienniel acoustic surveys– *Alternative Fspr% values
• Performance measured using specific statistics
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Operating ModelStock dynamicsFishery dynamicsTrue population
Management Strategy* Data choices* Stock
Assessment* Harvest control
rule
CatchData
Performance Statistics* Conservation
objectives* Yield objectives* Stability
objectivesFeedback
Loop
Evaluation Phase
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------Conditioning period ------(2012 assessment)
Short2013-15
Med2016-20
Long2021-30
<-- Simulation period -->
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Cases Considered
• No fishing• Perfect Information Case• Annual Survey • Biennial Survey• Alternative FSPR% (with perfect info)
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No fishing case
• Set catches to zero, no assessment model• Exists to provide the first reference case to
describe how the stock will behave in the absence of fishing
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Perfect Information Case
• We created a reference, perfect information case where the catch applied in the management strategy was the catch given by applying the F40%-40:10 rule to the operating model.
• No assessment model is fit, simulated catches come from the application of the control rule to the true stock “known” by the operating model (i.e., what if we didn’t have uncertain data and stock assessment errors?)
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Biennial Survey Case• Every year operating model simulates dynamics of the stock (i.e.
recruitments, stock size etc)• Every odd year operating model simulates and assessment
model fits:– catch– survey age-composition data– commercial age-composition data– survey biomass
• In even years operating model simulates and assessment model fits– catch– commercial age composition data
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Example Simulations
• These will be single iterations of the management procedure from 2013-2030
• Want to illustrate some iterations of the simulation to give you a more intuitive feeling for how the simulations work.
• We’ll talk about the aggregate performance later
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Example Simulations Biennial survey
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Annual Survey Case
• Every year operating model simulates stock dynamics (i.e. recruitments, numbers at age, etc)
• Every year operating model simulates the following data:– catch– survey age composition data– commercial age composition data– survey biomass
• The assessment model fits these data and returns the exploitable biomass
• The harvest control rule takes the exploitable biomass calculates a catch
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------Conditioning period ------(2012 assessment)
Short2013-15
Med2016-20
Long2021-30
<-- Simulation period -->
But remember – starting points are not the same for each MSE run
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Annual Survey
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What we learned about the current management procedure
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The assessment sometimes chases the latest survey observation
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Assessment errors are frequent
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Aggregate Performance• Outcomes
– catches– How variable the catch is– Proportion of years in specific zones (below 10%, between 10 and 40%,
greater than 40% etc.)– The proportion of years that a management procedure closes the fishery
• Probability– How often does this occur?
• Time frame– Short term (2012-2015)– Medium term (2016-2020)– Long term (2021-2030)
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Statistics Break - Medians vs Means
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Average Annual Variability in Catch (illustration)
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Comparisons of Depletion, Catch and AAV for All Cases
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No fishing
Perfect infoAnnual surveyBiennial survey
10% of B0
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MinimumCatch
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Summary for long-term depletion
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Summary for long term AAV
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Summary for long-term catch
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Key Performance Statistics
Short Term
Medium Term
Long Term
Percentage of years: Per Ann Bie Per Ann Bie Per Ann Bie
Depletion above 40% 34.30% 35.90% 35.64% 28.95% 31.29% 32.67% 27.07% 29.54% 31.06%
Depletion below 10% 4.44% 6.61% 6.87% 0.94% 7.17% 8.59% 0.39% 5.39% 7.04%
Depletion between 10 and 40% 61.26% 57.49% 57.49% 70.11% 61.54% 58.74% 72.54% 65.08% 61.90%
MS closes fishery 0.00% 4.70% 3.90% 0.00% 8.51% 8.21% 0.00% 10.11% 13.61%
Table A.6 pp 135
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Key Performance Statistics II
Short Term
Medium Term
Long Term
Medians of: Per Ann Bie Per Ann Bie Per Ann Bie
Average catch 251 284 273 216 226 217 230 217 218
Average depletion 31.7% 31.4% 31.6% 27.9% 26.9% 27.8% 27.6% 27.3% 28.0%
AAV in catch (%) 36.6% 35.5% 32.5% 23.1% 34.1% 34.7% 23.3% 32.5% 33.2%
Table A.7 pp 135
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Analysis of alternative target harvest rates
• The hake treaty doesn't specify a target depletion level, only a target harvest rate (F40%) and a control rule (40-10).
• This makes it difficult to evaluate the efficacy of the control rule (i.e. relative to what?)
• One additional curiosity that we considered was what would the target harvest rate have to be in order to achieve a range of target depletion levels
• The MSE can be used to explore how changes to the target harvest rate might affect depletion, AAV, and average catch.
• This is an exploration of trade-offs, not a proposal to change the hake treaty.
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Alternative target harvest rates
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Discussion and Conclusion
• The current management strategy (assessment model formulation and F40%-40:10 rule) performs as follows:– Median average depletion on the 7-17 year time horizon
~28%, mean average depletion ~37%• Benefits of annual survey marginal• Assessment design results in chasing most recent
data– Since the survey is itself variable, this produces a high
probability of assessment error
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Future work
• It’s not an MSE until objectives have been defined and the performance of alternative management strategies evaluated against them.
• The definition of these objectives and the JMC’s key interests will determine if we consider:– Operating models that consider more complicated hake
life-history (i.e. movement, Canada and US areas)– Alternative management procedures to damp
variability– Etc.
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Extra Slides
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Other available performance metrics
• First quartile depletion• Third quartile depletion• Median final depletion• Median of lowest depletion• Median of lowest perceived depletion• First quartile of lowest depletion• Third quartile of lowest depletion• First quartile of AAV in catch• Third quartile of AAV in catch• First quartile of average catch• Third quartile of average catch• Median of lowest catch levels• First quartile of lowest catch levels• Third quartile of lowest catch levels• Proportion with any depletion below SB10%• Proportion perceived to have any depletion below SB10%
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