Spatial optimization of invasive species control informed by management practices

Area of Science:

• Ecology
• Conservation Biology
• Wildlife Management

Background:

• Invasive species control is vital but budget-limited, often requiring extensive surveys.
• Efficient spatial resource allocation is key for successful invasive species management.

Purpose of the Study:

• To develop a novel framework for optimizing spatial capture effort allocation using state-space population models.
• To apply this framework to an invasive snapping turtle control program to minimize population density.

Main Methods:

• Devised a framework for spatially explicit optimization of capture effort.
• Utilized state-space population models based on past capture records.
• Applied the model to an invasive snapping turtle control program.

Main Results:

• Spatially heterogeneous density dependence and capture pressure influence snapping turtle abundance.
• Optimal effort allocation significantly improved control effects, with improvements increasing with total effort.
• A fourfold increase in total effort plus spatial optimization was necessary to meet management goals.

Conclusions:

• Combining state-space models with optimization enhances adaptive invasive species management and decision-making.
• The developed method is broadly applicable to wildlife and pest control programs using removal data.
• Rapid population response to optimal management is driven by high growth rates and density-dependent regulation.