Designing optimal strategies for surveillance and control of invasive forest pests.

Abstract

This thesis focuses on the theme of detecting and managing invasive forest pests. First, we model optimal detection of sub-populations of invasive species that establish ahead of an advancing front. We find that the uninfested landscape is divided into two zones, characterized by different dynamically optimal management plans: a suppression zone and an eradication zone. In the suppression zone, optimal detection effort increases with distance from the front. At the distance where the suppression zone yields to the eradication zone, optimal detection effort plateaus at its maximum level. Second, we develop a model of optimal surveillance and control of forest pathogens and apply it to the case of oak wilt in a region within Anoka County, Minnesota. We develop a cost curve associated with the expected fraction of healthy trees saved from becoming infected. We also explore characteristics of sites selected for surveillance. In particular, we examine the characteristics of sites that make them high-priority sites for surveillance when the budget level is relatively low. We find that the best surveillance strategy is to prioritize sites with relatively low expected unit surveillance cost per tree saved from infection. Our results offer practical guidance to managers in charge of deciding how and where to spend limited public dollars when the goal is to reduce the number of trees newly infected by oak wilt. Third, we model a private landowners' forest protection problem, in which each landowner decides among three possible strategies: prevention, monitoring and treatment, and no treatment. We find that the proportion of landowners taking preventive and no action increases as the accuracy of monitoring decreases; monitoring ceases to be chosen when monitoring accuracy declines below a threshold value. We also investigate the possible effects of a policy that raises the accuracy of monitoring on social welfare in both the landowners' equilibrium and the full information social optimum. We find that the policy closes the gap in social welfare between the landowners' equilibrium and the full information social optimum. However, it decreases social welfare in the full information social optimum.