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Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Optimal surveillance against bioinvasions: a sample average approximation method applied to an agent-based spread

Hoa-Thi-Minh Nguyen1, Pham Van Ha1, Tom Kompas2

  • 1Crawford School of Public Policy, Australian National University, Crawford Building (132), Lennox Crossing, Canberra, Australian Capital Territory, 2601, Australia.

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Summary

Optimizing invasive species surveillance, like the Papaya Fruit Fly (PFF), requires balancing early detection costs and future damages. A new model suggests a 0.7 km trap grid is optimal for PFF in Queensland, significantly reducing outbreak costs.

Keywords:
agent-based modelearly detectionoptimal surveillanceoptimizationpapaya fruit flies (Bactrocera papayae)sample average approximationspatial-dynamic processstochastic programming

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Area of Science:

  • Ecology
  • Agricultural Science
  • Operations Research

Background:

  • Invasive species pose significant economic threats, necessitating effective early detection and control strategies.
  • Optimizing surveillance for invasive species involves complex trade-offs between detection timing and control costs.
  • Current surveillance methods often lack the precision to balance these economic considerations effectively.

Purpose of the Study:

  • To develop a computationally efficient model for optimizing invasive species surveillance strategies.
  • To determine the optimal surveillance (trap grid) density for the Asian Papaya Fruit Fly (PFF) in Queensland, Australia.
  • To compare the economic outcomes of the proposed optimal surveillance strategy against current practices.

Main Methods:

  • Utilized a stochastic programming model combined with a sample average approximation (SAA) approach and parallel processing.
  • Developed an agent-based model (ABM) to simulate PFF spread, calibrated with high-resolution land-use and weather data.
  • Validated the ABM against a historical PFF outbreak to ensure accuracy.

Main Results:

  • The optimal economic trap grid size for PFF in Queensland was determined to be approximately 0.7 km, substantially smaller than the current 5 km grid.
  • The optimal policy, despite a higher annual surveillance cost ($2.08 million), significantly reduces the expected total outbreak cost to roughly $7.74 million.
  • The current policy's expected total outbreak cost is estimated at $23.92 million.

Conclusions:

  • The integration of SAA with ABM provides a robust framework for optimizing invasive species management under uncertainty.
  • A denser surveillance grid (0.7 km) is economically superior for PFF control in Queensland, despite higher initial investment.
  • Implementing the optimized surveillance strategy can lead to substantial savings in mitigating the economic impact of invasive species outbreaks.