Detection Strategies in Invasive Species Management

As concern regarding the environmental and economic impacts of non-native invasive species (NIS) grows, governments are devoting greater resources to NIS management. Yet, management agencies continue to face limited resources as they handle an increasing number of diverse nonindigenous species. Substantial damages from certain invaders have fueled the widely-accepted perspective that prevention is the optimal management strategy. Unfortunately, it is not always possible due to the highly uncertain nature of potentially invasive species coupled with the need to manage existing invasive species. Thus, agencies must constantly detect and control species after they have arrived. This detection stage, and its relationship to the management activities, is often overlooked by existing literature which focuses on the prevention and control stages. This paper analyzes the optimal management strategies for government agencies after the species has been introduced. Using a two-stage stochastic dynamic model, we capture the stochastic nature of successful detection of a species. The probability of detection depends on the interaction between the chosen search intensity and the species' population density. While high levels of search and control are optimal for invasive species with high damages, such as the Emerald Ash Borer, the optimal management levels are often much lower for less invasive or less damaging species. The paper also examines the effect of uncertainty in various parameters to assess the optimal resource allocation between management strategies.