Economics of controlling invasive species: A stochastic optimization model for a spatial-dynamic process

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Abstract

We analyze the dynamic process of invasive-species control in a spatially explicit and stochastic setting. An integer optimization model is applied to identify optimal strategies to deal with invasive species at a steady state. Optimal strategies depend on the spatial location of invasion as well as on stochastic characteristics of spread and control. Previous studies of invasive-species control have been stochastic or spatial, but not both. We model a landscape as consisting of multiple cells, each of which may be subject to border control or eradication within the cell. Optimal strategies from the model are characterized as eradication, containment, or abandonment of control. Representing the rate of species spread as stochastic rather than deterministic results in less-intensive control becoming optimal at equilibrium. The optimal strategy may switch from eradication to containment or from containment to abandonment. If an infestation occurs at the boundary of the region within which it may spread, it is more likely to be optimal to eradicate or contain the species, compared to an infestation in the interior of the region. If the effectiveness of border control is stochastic, then containment is not feasible in the long term, but it is still optimal as a temporary measure in some scenarios.

Original languageEnglish
Pages (from-to)123-139
Number of pages17
JournalAmerican Journal of Agricultural Economics
Volume99
Issue number1
DOIs
Publication statusPublished - 1 Jan 2017

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Introduced Species
invasive species
Economics
economics
cells
Stochastic optimization
Dynamic process
Optimization model
Invasive species
Optimal strategy
Eradication

Cite this

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title = "Economics of controlling invasive species: A stochastic optimization model for a spatial-dynamic process",
abstract = "We analyze the dynamic process of invasive-species control in a spatially explicit and stochastic setting. An integer optimization model is applied to identify optimal strategies to deal with invasive species at a steady state. Optimal strategies depend on the spatial location of invasion as well as on stochastic characteristics of spread and control. Previous studies of invasive-species control have been stochastic or spatial, but not both. We model a landscape as consisting of multiple cells, each of which may be subject to border control or eradication within the cell. Optimal strategies from the model are characterized as eradication, containment, or abandonment of control. Representing the rate of species spread as stochastic rather than deterministic results in less-intensive control becoming optimal at equilibrium. The optimal strategy may switch from eradication to containment or from containment to abandonment. If an infestation occurs at the boundary of the region within which it may spread, it is more likely to be optimal to eradicate or contain the species, compared to an infestation in the interior of the region. If the effectiveness of border control is stochastic, then containment is not feasible in the long term, but it is still optimal as a temporary measure in some scenarios.",
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AU - Chalak, Morteza

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N2 - We analyze the dynamic process of invasive-species control in a spatially explicit and stochastic setting. An integer optimization model is applied to identify optimal strategies to deal with invasive species at a steady state. Optimal strategies depend on the spatial location of invasion as well as on stochastic characteristics of spread and control. Previous studies of invasive-species control have been stochastic or spatial, but not both. We model a landscape as consisting of multiple cells, each of which may be subject to border control or eradication within the cell. Optimal strategies from the model are characterized as eradication, containment, or abandonment of control. Representing the rate of species spread as stochastic rather than deterministic results in less-intensive control becoming optimal at equilibrium. The optimal strategy may switch from eradication to containment or from containment to abandonment. If an infestation occurs at the boundary of the region within which it may spread, it is more likely to be optimal to eradicate or contain the species, compared to an infestation in the interior of the region. If the effectiveness of border control is stochastic, then containment is not feasible in the long term, but it is still optimal as a temporary measure in some scenarios.

AB - We analyze the dynamic process of invasive-species control in a spatially explicit and stochastic setting. An integer optimization model is applied to identify optimal strategies to deal with invasive species at a steady state. Optimal strategies depend on the spatial location of invasion as well as on stochastic characteristics of spread and control. Previous studies of invasive-species control have been stochastic or spatial, but not both. We model a landscape as consisting of multiple cells, each of which may be subject to border control or eradication within the cell. Optimal strategies from the model are characterized as eradication, containment, or abandonment of control. Representing the rate of species spread as stochastic rather than deterministic results in less-intensive control becoming optimal at equilibrium. The optimal strategy may switch from eradication to containment or from containment to abandonment. If an infestation occurs at the boundary of the region within which it may spread, it is more likely to be optimal to eradicate or contain the species, compared to an infestation in the interior of the region. If the effectiveness of border control is stochastic, then containment is not feasible in the long term, but it is still optimal as a temporary measure in some scenarios.

KW - Dynamics

KW - Invasive species

KW - Optimal control

KW - Spatially explicit

KW - Stochastic

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