Ecopath, Ecosim, and fisheries management??

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Ecopath, Ecosim, and fisheries management??
Realist
Believer
Non believer
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Some terminology

• ECOPATH - Builds a food web
• ECOSIM - One way to make this web dynamic
• ECOSPACE - An attempt at spatial modeling
• EwE (from www.ecopath.org) is one implementation.
• Semi-black box
• This useful for initial work (data exploration,
  basic tradeoffs, in other words, ecological
  priors)
• Currently insufficient for extensive formal
  confrontation of models and data
• Most work here was performed with Ecosim
  algorithms, outside of the black box

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Model distribution

• EwE (from www.ecopath.org) is one implementation.
• Semi-black box
• This is v. powerful for some uses (data
  exploration, tradeoffs)
• Currently insufficient for extensive formal
  confrontation of models and data
• Our aim is to build in both of these areas
  (current use and better tools).

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In the beginning was DYNUMES...

• ECOPATH
• Began with Polovina 1984, updated by Christensen
  and Pauly (early 1990s) - statistics added until
  current (year 2000) version. But basic equations
  are unchanged (and well-examined) for over 10
  years.
• ECOSIM (and ECOSPACE)
• Recent work to make a food web dynamic, theory
  and practice new (some is un-reviewed with ad-hoc
  corrections).
• Unified (open?) format is strength

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Why try to use the whole food web in a
predictive model?

• Eastern Bering Sea

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What is the use of a mass-balance ecosystem
model, anyway?

• First and foremost, stock-scale (usually annual)
  data integration, hypothesis exploration.

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Use may be a qualitative communication of
trade-offs

• This model may do whatever you want, there are
  good and bad examples.
• But what you have to do to get what you want may
  be very instructive.
• Dont mistake the explorations for yield
  predictions.

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Not a single species replacement used in
conjunction

• First steps to large marine scale predator/prey
  management
• Climate shifts vs. noise (pulses) vs.
  interspecies vs. fishing.
• The secret life of metrics (total system biomass?
  T.L. of catch?)
• Ecological theory.
• Sensitive (but mysterious) species issues.
• Predator culling is a real issue
• current back-of-the-envelope approaches may be
  worse (these models show culling may or may not
  work). But models are the only way...
• Data quality
• Reconciliation, sensitivity, and targeting new
  data.
• Will more data help (the predator culling issue).
• Radical re-design of working an ecosystem.
• Command, control, or along for the ride?

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Criticisms

• Its a model
• So is everything

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Criticisms

• Its a model on the wrong scale
• Stocks, not processes

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Criticisms

• Its a biomass dynamics model
• Its one tool among many.

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Biomass dynamics are poor dynamics???

• Its our conceptual basis (MSY).
• Replace one set of assumption (constant Ms) with
  another (simplified age structure).
• A balance between necessary complexity across
  species.
• A complement to age-structured (single or
  multi-species) models.
• The why wont our hypothesis work with simple
  models challenge.
• Where it breaks down, detail may be added (delay
  difference etc.).

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Comparison (deterministic forecast)

• Single species
• M(age) fixed, estimated
• Growth/Bio fixed or DD at age
• Recruit(0) f(N, B)
• Partial recruitment to fishery, spawning
• climate, other spp added through external
  parameters
• MSFOR
• M(age) f(pred(age), prey(age))
• Growth/Bio fixed or DD at age
• Recruit(0) f(N,B)
• Partial recruitment to fishery, spawning,
  ontogenetic (given data)
• Climate external
• Ecosim
• One or two pools -2 pools have internal delay
  structure
• M(juv,adu) f(Bpred,Bprey)
• Growth/Bio(juv/adu) f(Bpred,B prey)
• Recruit(0) f(Bpred, Bprey)
• (If one pool, recruit is fixed prop. Cost of
  growth)
• Knife-edged recruit to fishery, spawning,
  ontogenetic, climate still external

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Criticisms

• Its an equilibrium biomass dynamics model
• Mass-balance is a perturbable starting point
• Mass-balance is not an equilibrium assumption.
• (First, a look at the mass balance process).
• In moving from Ecopath to Ecosim, an equilibrium
  is built.
• This confrontation is the major work to discuss.
• (Overcompensatory functional responses, etc.).

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A single trophic relationship
Bi
Q/BjDCijBj
P/BjBj
Bj
P/BjBj Ii Ei - SjQ/BjDCjBj - Other
loss
0 (Mass Balance)
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Solving each unknown

• P/BiBiEEi FBi SjQ/BjDCjBj i
• P/B, EE unknown
• top down (demand) solution.
• Q/B unknown, B unknown
• top down / one prey item
• Catch (FB) should be known.
• Diet composition must be known.
• Generalized inverse for over- or under-determined
  models.

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Sources of dissipation
(Q/B)
(P/B)
(1-G)
(1-EE)
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Sources of dissipation (EE is the key).

• EE is what you dont know about the system.
• May include known time trends in the accounting
  (BA biomass accumulation).

QGEE
(Q/B)
(P/B)
(1-G)
(1-EE)
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Mass-balance (Ecopath step) reconciles data - not
in itself an equilibrium

• Data issues
• always a mix of good, bad, and ugly
• a different way of reconciling conflicts
• Combine and compare
• Harvest/stock assessments
• Diet data
• Bioenergetics/growth
• Mortality/rate studies
• Lower trophic level production

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The (black) art ofmodel balancing

• Benefit you start to see the trade-offs
  (necessary correlations).
• Its where you first address data quality.
• Reconciliation of scales, techniques, and
  sources.
• What must you do to reconcile multiple single
  species assessments
• Like the black art of Bayesian priors

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The equilibrium question

• All models have an equilibrium.
• Ecosim starts there its an Ecopath to Ecosim
  transition issue.
• Fast rebound (overcompensation) may be tuned.
• Sensitivity approach may be implemented to fix
  this (spin up approach).

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Bioenergetics
B P/B Q/B DC EE Catch BA etc. (mass accounting)
Alternate stable states??
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ECOPATH to ECOSIM

• From a zero-dimensional equilibrium state to a
  zero-dimensional dynamic equation

Q/BBj
Prey
P/BBi
Predator
EE
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Dynamics of overlap - (one predator one prey)
Its cold down there!
V
Bj
B-V
aijVijBj
vij (Bi-Vij)
Bi - Vij
Vij
Assume fast equilibrium for Vij
vijVij
dVij /dt vij(Bi-Vij) - vijVij - aijVijBj
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The appearance of Density Dependence

• dVij /dt vij(Bi-Vij) - vijVij - aijVijBj 0
• Vij vijBi/(2 vij aijBj)
• Cij (Bi,Bj) aijvijBiBj
• (2 vij aijBj)

Prey biomass
Cij (or Minstant)
Cij /Bj
Predator Biomass
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Mathematically, halfway between the trickle and
the vat

• Cij (Bi,Bj) vijBi
• ( 2vij 1 )
• aijBj
• Integrate limited smaller spatial and temporal
  dynamics (more or less)
• Single vulnerability parameter X 2v/aBj ratio
• AGE STRUCTURE
• Possible example good evidence for this
  functional response, both by age (e.g. pollock)
  and by density-dependence (e.g. halibut).

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One predator, many prey

• Prey switching exists as a complex of 3 variables
  
• base diet, vulnerability, feeding time to modify
  suitabilities
• Captures some age-structure dynamics without the
  age structure
• Basic assumption is that biomass is not
  independent of diet, age structure.
• Switch or die?
• Invasions/vast changes not captured.

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Age-structure simulation
Smaller biomass implies younger age structure
through changing relative vulnerability set by
v parameters.
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MSFOR vs. Ecosim?

• Different sides of the same coin
• Simplify age structure (Ecosim) or simplify
  consumption (MSVPA).
• MSVPA assumes fixed suitabilities at age.
• Ecosim assumes changing suitabilities with
  biomass (and therefore with age and foraging
  combined).
• Hybrid methods are quite possible.

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Fishing in Ecosim

• By individual species or gear type
• may apply to a species directly, or as an effort
  multiplier to gear.
• Gear type applies exploitation rate on multiple
  species group...bycatch is tied to gear effort.

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Model behavior

• Top-down (fishing) experiments
• Apex predators behave as single-species models
  with (over?) compensatory growth of prey.
• Pella-Tomlinson form if prey is fixed.
• Cascades appear below apex predators.
• Middle and lower trophic level fishing results
  are unpredictable.

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MSY and overcompensation in base scenarios
Phytoplankton
Zooplankton
Fish

• (Aydin 2001 submitted)

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The effect of vulnerability on MSY
Phytoplankton
Zooplankton
Fish

• Fish
• Catch
• Zoop
• B/B0

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age-structure and bioenergetics

• Some basic decisions in the model need to be
  revisited in the next generation.
• Coordination with MSVPA
• Energy partitioning
• Myers et al.
• Bioenergetics decisions.
• But led to compesation/depensation.

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MSY and bioenergetic overcompensation

• Another example passive vs. active metabolism in
  zooplankton

Fish
Phytoplankton
Zooplankton
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Fit to single species?
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Additional data anomalies in consumption

• Systematic anomalies in consumption rates?
• Food habits
• Predator size
• Prey size
• abundant year classes
• Age class models
• Run the model backwards? Too much noise!
• Evidence of alternate stable states?

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Recruitment

• A delay-difference equation with juveniles
  divided into monthly pools
• Size vs. age at recruitment tuneable
• Energy apportionment strategies
• Individual growth rates
• Knife edge recruitment to fishery, spawning, and
  ontogenetic switch.
• Spawning biomass is indirect measure.
• This is a primary simplification (also for
  afternoon discussion).

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Model behavior

• Bottom-up (forcing) experiments
• Time scale (frequency) is important.
• Who responds the fastest?
• Invasions are not predictable.
• Explanations may be dangerous
• External (climate) hypotheses must exist
• (EBS climate fitting as case-study afternoon)
• climate image

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mesoscale and migrations

• Mesoscale
• Reasonable as single-species models for fishing
  experiments
• Seasonal changes, aggregations on prey may lead
  to detectable systematic changes in foraging
  parameters
• Migrations
• Model may be damped by external food sources.

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Needed to make ECOSIM rigorous

• Many of the problems listed (prey switching,
  etc.) are not specific to Ecosim.
• Basic fitting exists.
• Thorough peer-reviewed testing against
  single-species, MSVPA models.
• An improved statistical framework.
• This is the next major development (come see the
  quantitative seminar!).

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Fitting 1979-2000

• First
• Vul fitting indicates low vuls (vlt0.05) fits
  better (recruitment dominated??)
• Kept vuls at 0.3

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The confrontation can it be done, what do we
learn?

• Ecopath as priors.
• Specification of full-scale problem in progress
  (balancing importance and covariance of
  bioenergetics, foraging, mortality).

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Bioenergetics
B P/B Q/B DC EE Catch BA etc. (mass accounting)
Still Blowing up at 3 am
Ecopath as priors to examine correlation using
population and life history trade-offs, some
single-species models
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Meanwhile, culling in a simple model

• Can we reasonable predict the results of a
  removal of the top predator?
• Groundfish are near MSY
• FM
• 80 of M from mammals
• 15 of M from pred. Fish
• 5 unidentified
• Can we increase yield (while holding effort
  constant) by removing mammals?

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Yes (made to happen)
(Truism killing an animal will stop it from
eating but where does the energy end up?)
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Our confidence?

• Perform 1000s of draws, allowing start out of
  equlibrium drawing
• Diets from uniform 30
• Vuls from range between 0.1 and 0.6
• All others (P/B, Q/B, passive/active respiration)
  from uniform 10

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Results often down, not up
Biomass after 50 years/start biomass

• Mammal vs. predatory fish fish wins
• Improving diet data unlikely to help this
  picture.
• Possibility of improving mammals through lower
  fishing also uncertain.
• Admission this is a simple, tightly-wired web
  (vuls tightly wired??).
• What about more complex webs?
• What about climate variability?
• What about the unmodeled, inedible predator?
• WHAT ABOUT PROCESS UNCERTAINTY INCREASE???

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Command, control, or along for the ride?

• If we cant predict manipulations (esp. in light
  of added climate variability), we should aim/add
  to our objectives the minimization of
  unpredictable cascades, rather than the
  optimization of multispecies yields or specific
  trophic-based rebuilding plans.
• A healthy ecosystem (without homeostasis).
• How much did all fish go through regimes before
  we fished them?

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Laundry list 1

• Model savvy in current uses
• Endangered (im)possibilities (restore S.S.L.s
  through prey?)
• Climate and causality seeking.
• Seeking key/critical species interactions and
  uncertainties.
• Model behavior and improvement.
• Radical rethinking (the impossible MSY and
  variability?)

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Laundry List for management discussion (some may
work or may have worked)

• First steps to large marine scale predator/prey
  management
• Necessary in a loosely/tightly wired system?
• Climate shifts vs. noise vs. interspecies vs.
  fishing.
• The secret life of metrics (total system biomass?
  T.L. of catch?)
• Ecological theory (cultivation/depensation).
• Communication of alternatives.
• Endangered and HAPC species Issues.
• Predator culling is a real issue
• current back-of-the-envelope approaches may be
  worse (these models show culling may or may not
  work).
• Data quality issues
• Reconciliation.
• Sensitivity/targeting new data.
• Radical re-design of working an ecosystem.
• Command, control, or along for the ride?