Effective resource allocation to combat invasions of the spotted lanternfly (Lycorma delicatula) and similar pests

TL;DR

This paper develops an optimized resource allocation model for controlling the invasive spotted lanternfly, emphasizing strategic deployment of stage-specific controls to minimize population growth and improve management outcomes.

Contribution

It extends existing models to determine optimal control deployment strategies under various effort-response scenarios, including resource constraints and diminishing returns.

Findings

Exhaustive sequential deployment of controls is optimal when effects are proportional to effort.

Formulas for switching controls are derived for diminishing returns scenarios.

Numerical optimization strategies outperform random deployment, enhancing management effectiveness.

Abstract

The spotted lanternfly is rapidly establishing itself as a major insect pest with global implications. Despite significant management efforts, its spread continues in invaded regions, and refined management strategies are required. A recent study introduced a model that generalized the results of empirical control efficacy studies by incorporating population dynamics and incomplete delivery. In particular, a generalized population growth formula was derived, providing the minimum proportion of a population that must be treated with a given control to induce population decline. However, this model could not address the more relevant question of how best to deploy a control to minimize population growth. Here, we extend this model and formula to address this question in various settings. When the effect of control is proportional to effort, we show that exhaustive sequential deployment of stage-specific controls, ordered by efficacy, is optimal. When control effects exhibit diminishing returns with effort, we derive a formula for when to switch controls, providing an effective strategy in situations where management resources may vary or be cut at any time. We also use numerical global optimization methods to obtain strategies when resources are fixed a priori. Both strategies outperform random deployment, which can result in disastrous outcomes. Our results demonstrate that adopting an effective strategy for deploying stage-specific controls is essential for managing the spotted lanternfly. However, we found no papers addressing this topic in the lanternfly literature, nor information on whether such strategies are used. Given the limited resources available to combat the lanternfly, it is critical that they are used effectively. The approach introduced here, along with other optimization methods used in related fields, can contribute to this goal.