Integrated Bioeconomic Modeling of Invasive Species Management

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Integrated Bioeconomic Modeling of Invasive
Species Management

• David FinnoffJason Shogren
• John Tschirhart
• University of Wyoming
• Chad Settle
• University of Tulsa
• Brian Leung
• McGill University
• David Lodge
• University of Notre Dame
• Michael Roberts
• ERS/USDA
• August 2004
• ERS

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• Progressworking toward integrating specific
  modeling approaches into one general framework
• Application to leafy spurge

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Phase I Endogenous Risk with discounting and
risk aversion,

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Endogenous Risk

• Captures risk-benefit tradeoffs
• Stresses that management priorities depend
  crucially on
• The tastes of the manager
• over time and risk bearing
• The technology of risk reduction
• prevention, control, and adaptation
• Managers with different preferences will likely
  make different choices on the mix of prevention
  and control.

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• Investigate how changes in a managers
  preferences over time and over risk affect the
  optimal strategy mix
• Explore comparative statics on how changing
  tastes affect the technology mix.
• 2. Implement the model to a specific
  application of managing zebra mussels in a lake.

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Schematic of the Invasion Process
IH
qH3
IH
IL
(1-qH3)
q2
IH
qL3
I
IL
IL
p1
(1-q2)
(1-qL3)
IH
I
(1-p1)
q3
p2
t0
N
IL
(1-q3)
(1-p2)
t1
I
p3
N
t2
(1-p3)
N
t3
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Dynamic Endogenous Risk
Stage 1
Stage 2
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Comparative Statics Risk Aversion
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Simulation Results 1
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Simulation Results 2
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Leafy Spurge Application

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Conclusions

• Explored how changes in a managers preferences
  for time and risk-bearing influence optimal
  strategy mix
• Impacts are species-specific rest on whether
  direct effects dominate the other through
  indirect effects
• less risk averse managers who are far sighted,
  invest more in prevention, less in control, and
  require less private adaptation

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• Reduced risk aversion on the part of the manager
  yields lower probabilities of invasion, lower
  invader populations, and increased welfare
• Risk aversion induces a manager to want to avoid
  riskboth from the invader and from the input
  used - go with the safer betcontrol
• More exploration into the underlying preferences
  of managers may be worthwhile to better
  understand how such effects might influence
  invasives management

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Phase IIGeneral Equilibrium, Competition,
the Influence of Fundamental Resources
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GEEM


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Temperature


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Predictions

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Invasion 1
Biomass, Plant 2
Biomass, Plant 1
Biomass, Plant 3
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Invasion 2
Biomass, Plant 6
Biomass, Plant 4
Biomass, Plant 5 (Invader)
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Humans
Biomass Harvests
Herbicide
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Conclusions

• Theory of plant competition based in individual
  plant physiological parameters and maximizing
  behavior
• Theory starts prior to the population dynamics
  and builds on a behavioral basis
• Captures redundancy in the plant community
• Species with max expected valued of SS SEL
  parabola(s) are only non-redundant species
• If invading species is non-redundant it will
  dominate
• Limitations
• Only addresses resource competition
• Omits mutualism only considers mature plants
  lacks age structure

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• Phase III
• Optimal Control Model

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Optimal Control

• Determines Paths to Steady State under different
  scenarios, with
• no action by ranchers/farmers land managers
• action taken only by ranchers/farmers
• action taken by both
• Accounts for the impact of actions taken by
  ranchers/farmers

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• Flexibility to account for first-best path and
  welfare losses under second-best paths
• Allows for economically viable and non-viable
  harvesting of invasive
• Includes benefits/costs between steady states
  instead of simply a comparison of steady states

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Species Equations of Motion
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Representative Rancher/Farmer
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Land Manager as a Social Planner
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Conclusions

• Illustrate how accounting for actions by
  ranchers/farmers and feedbacks affect predictions
  on species populations
• Show how the various paths to a steady state are
  altered by activity/inactivity of each party
• Explore optimal action by land managers given
  model assumptions

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Remaining tasks

• Phase IV Leafy spurge in Thunder Basin
  Grasslands
• Phase V Implications
• Phase VI Supermodel validation