Spatially explicit multi-objective mathematical model for invasive species management.
Invasive species have long been difficult and expensive to eradicate, raising the need to develop more efficient and optimal management strategies. This paper presents a bi-objective mathematical model for controlling invasive species, combined with geospatial visualizations to aid with actionable strategy. The optimization model employs a multi-objective approach that incorporates functional connectivity of the infested sites to achieve an optimal specified minimum control level for a given invasive plant species. Subsequently, the model serves as a decision tool to identify optimal Invasive Species Management (ISM) strategies when mapped with GIS. This paper applies the framework to the case of Chinese privet (Ligustrum sinense) control on 317 acres of conservation land in Chattanooga, Tennessee, at Reflection Riding Arboretum and Nature Center. The proposed model simultaneously optimizes two objectives and provides an optimal configuration for species control by maintaining functional connectivity. Results display how changes in model parameters (namely, the decision maker's preference of objective functions and desired minimum control level) create variation in optimal solutions based on these inputs, while reflecting on desired options. The research indicates multi-objective optimization contributes to complex decision-making in ISM, and placing these mathematical models in a geographic context provides insight into potential improvement in ISM practices.