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Integrating Prevention and Control of Invasive Species: The Case of the Brown Treesnake. Kimberly Burnett, Brooks Kaiser, Basharat A. Pitafi, James Roumasset University of Hawaii, Manoa, HI Gettysburg College, Gettysburg, PA. Objectives.

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Integrating prevention and control of invasive species the case of the brown treesnake l.jpg

Integrating Prevention and Control of Invasive Species: The Case of the Brown Treesnake

Kimberly Burnett, Brooks Kaiser,

Basharat A. Pitafi, James Roumasset

University of Hawaii, Manoa, HI

Gettysburg College, Gettysburg, PA


Objectives l.jpg
Objectives Case of the Brown Treesnake

  • Illustrate dynamic policy options for a highly likely invader that has not established in Hawaii

  • Find optimal mix of prevention and control activities to minimize expected impact from snake


Boiga irregularis l.jpg
Boiga irregularis Case of the Brown Treesnake


Methodology l.jpg
Methodology Case of the Brown Treesnake

  • First consider optimal control given N0 (minimized PV of costs and damages) =>Nc*

  • We define prevention to be necessary if the population falls below Nmin (i.e., Nc*< Nmin)

  • Determine optimal prevention expenditures (to decrease probability of arrival) conditional on the minimized PV from Nc*


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N Case of the Brown Treesnake0 ≥Nmin

Nc* = Best stationary N without prevention

Nc* Nmin

Nc*<Nmin

We have a winner!

N* = Nc*

Choose y to min cost of removal/prevention cycle

Z(Nc*)

V(Nmin)

N* = Min (Z,V)


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Algorithm to minimize Case of the Brown Treesnakecost + damage

=> V* => Nc*


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PV costs + damage if Case of the Brown TreesnakeNc* < Nmin

  • If N*c <Nmin, we must then consider the costs of preventing re-entry.

Z =


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Prevention/eradication cycle Case of the Brown Treesnake

  • Expected present value of prevention and eradication:

  • p(y): probability of successful introduction with prevention expenditures y. Minimizing Z wrt y results in the following condition for optimal spending y:


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N Case of the Brown Treesnake0 ≥Nmin

Nc* = Best stationary N without prevention

Nc* Nmin

Nc*<Nmin

We have a winner!

N* = Nc*

Choose y to min cost of removal/prevention cycle

Z(Nc*)

V(Nmin)

N* = Min (Z,V)


Choose optimal population l.jpg
Choose optimal population Case of the Brown Treesnake

  • If N* Nmin, same as existing invader case

    • Control only

  • If N* < Nmin,

    • Iterative prevention/removal cycle


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Case study: Hawaii Case of the Brown Treesnake

  • Approximately how many snakes currently reside in Hawaii?

  • Conversations with expert scientists: between 0-100


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Growth Case of the Brown Treesnake

  • Logistic: b=0.6, K=38,850,000


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Damage Case of the Brown Treesnake

  • Power outage costs: $121.11 /snake

  • Snakebite costs: $0.07 /snake

  • Biodiversity: $0.32 – $1.93 /snake

  • Total expected damages:


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Biodiversity Case of the Brown TreesnakeLosses


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Control cost Case of the Brown Treesnake

  • Catching 1 out of 1: $1 million

  • Catching 1 out of 28: $76,000

  • Catching 1 out of 39m: $7


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Probability of arrival a Case of the Brown Treesnakefunction of spending


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Results Case of the Brown Treesnake

  • Aside from prevention, eradicate to zero and stay there.

  • Since prevention is costly, reduce population from 28 to 1 and maintain at 1


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First period cost Case of the Brown Treesnake

Annual cost

PV costs

Annual damages

NPV damages

PV losses

Status quo

$2.676 m

$2.676 m

$133.8 m

$4.5 b

$145.9 b

$146.1 b

Opt.

policy

$2.532 m

$227,107

$13.88 m

$121

$9,400

$13.89 m

Snake policy: status quo vs. optimal (win-win)

NPV of no further action: $147.3 billion


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Summary Case of the Brown Treesnake

  • Re-allocation between prevention and control may play large role in approaching optimal policy even at low populations

  • Eradication costs increased by need for prevention, which must be considered a priori

  • Catastrophic damages from continuation of status quo policies can be avoided at costs much lower than current spending trajectory


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Uncertainties Case of the Brown Treesnake

  • Range of snakes currently present (0-100?)

    • 8 captured

    • More may’ve gotten away

    • Not much effort looking

  • Probability of reproduction given any pop’n level

    • Don’t know, need to look at range of possibilities

    • Here all control

    • If N*<Nmin, prevention makes sense

    • Need to find optimal mix


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