Optimizing pest management strategies: a framework applied to pine wilt disease

Pine wilt disease (PWD) constitutes a severe forest pest crisis causing widespread pine mortality globally. Developing effective, economically viable management policies remains challenging because of data scarcity and complex ecological dynamics. This study aims to bridge this gap by establishing a multidisciplinary framework that combines meta-analysis, field experiments, and mathematical modeling to optimize PWD control strategies.

A meta-analysis of 102 regional data sets evaluates the relative performance of 8 control policy combinations. The integration of physical removal, trunk injection, and vector control is identified as the most effective strategy, although vector control alone offered the highest cost-efficiency. Field experiments and a parameterized discrete susceptible-infected-dead (SID) model provide support for these patterns and show consistent trends; the SID model also shows satisfactory agreement with independent external data. Furthermore, the model-derived basic reproduction number identifies physical removal as a prerequisite for eradication. The developed model predictive control provides targeted management recommendations for site-specific scenarios.

Integrated empirical and model-based analyses indicate that physical removal is a prerequisite for PWD eradication, whereas trunk injection and vector control are critical supplementary measures to accelerate disease suppression. This research advances the field by transitioning from static efficacy evaluations to a dynamic, economically optimized decision-making framework, providing forestry managers with actionable, model-driven strategies to combat this invasive pest. © 2026 Society of Chemical Industry.