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Herring HCR accounting for its role as forage

US New England Fishery Management Council Herring MSE

Sarah Gaichas
Ecosystem Dynamics and Assessment
Northeast Fisheries Science Center

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Are any Atlantic herring harvest control rules good for both fisheries and predators?

Harvest control rules are:

  • plans for changing fishing based on stock status
  • pre-determined

"Which harvest control rules best consider herring's role as forage?"

  • DESIGN a harvest control rule (HCR):
    • balancing fishing benefits and ecological services
    • addressing diverse stakeholder interests
  • TRANSPARENTLY within management time frame!
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The MSE process

First MSE within US Council
(Feeney, Boelke, Deroba, Gaichas, Irwin, and Lee, 2018) Scope: annual stockwide HCR Open stakeholder meetings (2)

  • ID objectives, uncertainties
  • ID acceptable performance
  • more diverse, interactive than "normal" process

Uncertainties identified

  • herring mortality (M)
  • environmental effects on herring
  • predator response to herring abundance
  • assessment uncertainty
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Operating models and uncertainties

Operating Model Name Herring Productivity Herring Growth Assessment Bias
LowFastBiased Low: high M, low h (0.44) 1976-1985: fast 60% overestimate
LowSlowBiased Low: high M, low h (0.44) 2005-2014: slow 60% overestimate
LowFastCorrect Low: high M, low h (0.44) 1976-1985: fast None
LowSlowCorrect Low: high M, low h (0.44) 2005-2014: slow None
HighFastBiased High: low M, high h (0.79) 1976-1985: fast 60% overestimate
HighSlowBiased High: low M, high h (0.79) 2005-2014: slow 60% overestimate
HighFastCorrect High: low M, high h (0.79) 1976-1985: fast None
HighSlowCorrect High: low M, high h (0.79) 2005-2014: slow None
   

Implementation error was included as year-specific lognormal random deviations: Fa,y=ˉFySaeεθ,yσ2θ2εθN(0,σ2θ)

Assessment error was modeled similarly, with first-order autocorrelation and an optional bias term ρ: ˆNa,y=[Na,y(ρ+1)]eεϕ,yσ2ϕ2εϕ,y=ϑεϕ,y1+1ϑ2τyτN(0,σ2ϕ)

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Linked models matching stakeholder-identified objectives

The Dream:1 Convert the effects of control rules on 4 user groups to dollars:

  1. Users of landed herring (Demand)
    • Lobster industry, aquariums
  2. Herring harvesters (Supply)
  3. Direct users of herring in the ocean (not people)
    • Terns and Whales
    • Striped Bass, Dogfish
  4. Indirect users of herring in the ocean (people, Derived Demand)
    • Bird- and whale-watchers
    • Recreational and Commercial Fishing
The Reality
  • 8 herring operating models linked to simple predator and economic models, developed in parallel
  • limited range of predator response
  • limited economic effects, directed fishery only
(Deroba, Gaichas, Lee, et al., 2018)

1 Credit: Min-Yang Lee

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ternpoptrend

Time constraints forced:

  • selection of predators with previous modeling and readily available data
  • selection of single strongest herring-predator relationship
  • models ignoring high variance in prey-predator relationships
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Results summary

Three HCR types were rejected at the second stakeholder meeting for poor fishery and predator performance.

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Managing tradeoffs under uncertainty: What control rules give us 90% of everything we want?

  • Tern productivity at 1.0 or above more than 90% of the time
  • Herring biomass more than 90% of SSBmsy
  • Fishery yield more than 90% of MSY  
  • AND fishery closures (F=0) less than 1% of the time (plot on right).

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Lessons:

Complex food web, generalist predators

  • Herring is one of several important prey
  • Assess multiple prey together for stronger effects on predator productivity
  • Tern/Tuna/Groundfish/Mammal productivity also affected by predators, weather, and other uncertain factors
  • Still showed which herring control rules were poor
  • Managers selected a harvest control rule considering a wide range of factors!

NEUSfw

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Conclusions: robust harvest control rules in a changing environment

  • Herring MSE peer review said next time:

    • Consider non-stationarity in herring parameters
    • Mis-specify reference points
    • Consider climate change
    • Include assessment model
    • Include full food web, lots more economic info
  • NOAA Fisheries MSE support

    • Dedicated analyst in each region
    • Climate related MSEs
      • California coastal pelagics
      • Pacific hake
      • Pacific sablefish
      • New England groundfish
  • NOAA Climate and EBFM Roadmaps

    • Scenario planning
    • MSE
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References

Deroba, J. J, S. K. Gaichas, M. Lee, et al. (2018). "The dream and the reality: meeting decision-making time frames while incorporating ecosystem and economic models into management strategy evaluation". In: Canadian Journal of Fisheries and Aquatic Sciences. ISSN: 0706-652X. DOI: 10.1139/cjfas-2018-0128. URL: http://www.nrcresearchpress.com/doi/10.1139/cjfas-2018-0128 (visited on Jul. 20, 2018).

Feeney, R. G, D. V. Boelke, J. J. Deroba, et al. (2018). "Integrating Management Strategy Evaluation into fisheries management: advancing best practices for stakeholder inclusion based on an MSE for Northeast U.S. Atlantic herring". In: Canadian Journal of Fisheries and Aquatic Sciences. ISSN: 0706-652X. DOI: 10.1139/cjfas-2018-0125. URL: http://www.nrcresearchpress.com/doi/10.1139/cjfas-2018-0125 (visited on Nov. 09, 2018).

Additional resources

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Are any Atlantic herring harvest control rules good for both fisheries and predators?

Harvest control rules are:

  • plans for changing fishing based on stock status
  • pre-determined

"Which harvest control rules best consider herring's role as forage?"

  • DESIGN a harvest control rule (HCR):
    • balancing fishing benefits and ecological services
    • addressing diverse stakeholder interests
  • TRANSPARENTLY within management time frame!
2 / 11
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