Coupled Human-Environment Dynamics of Forest Pest Spread and Control in a Multi-Patch, Stochastic Setting

Area of Science:

• Ecology
• Invasive Species Management
• Mathematical Modeling

Background:

• Non-native forest pests, such as Asian long-horned beetle (ALB) and emerald ash borer (EAB), pose significant threats to North American forests.
• Preventing the long-distance transport of infested firewood is critical due to the difficulty of eradicating established invasive species.

Purpose of the Study:

• To develop a stochastic simulation model analyzing the interplay between forest pest infestations and human decisions on firewood transportation.
• To identify key factors influencing the spread of forest pests via human movement of firewood.

Main Methods:

• A simulation model was created with 10 patches (5 low visitor volume, 5 high visitor volume).
• Infestation spread was modeled within and between patches, considering firewood transportation probabilities.
• Human decisions on firewood transport were based on cost, social norms, social learning, and infestation concern.

Main Results:

• Patch infestation time is nonlinearly dependent on model parameters; increased tree removal, public concern, or decreased local firewood cost significantly delays spread.
• Lower visitor volume patches benefit more from firewood movement restrictions.
• Cross-patch infestations can intensify existing outbreaks, with high-volume patches experiencing more severe long-term infestations.

Conclusions:

• Effective prevention of long-distance pest spread hinges on the interaction between pest dynamics and human behavior.
• Model-driven insights can optimize strategies for preventing invasive forest pest spread, but require empirical validation.