Simulating the effects of the southern pine beetle on regional dynamics 60 years into the future
Abstract
We developed a spatially explicit model that simulated future southern pine beetle (Dendroctonus frontalis, SPB) dynamics and pine forest management for a real landscape over 60 years to inform regional forest management. The SPB has a considerable effect on forest dynamics in the Southeastern United States, especially in loblolly pine (Pinus taeda) stands that are managed for timber production. Regional outbreaks of SPB occur in bursts resulting in elimination of entire stands and major economic loss. These outbreaks are often interspersed with decades of inactivity, making long-term modeling of SPB dynamics challenging. Forest management techniques, including thinning, have proven effective and are often recommended as a way to prevent SPB attack, yet the robustness of current management practices to long-term SPB dynamics has not been examined. We used data from previously documented SPB infestations and forest inventory data to model four scenarios of SPB dynamics and pine forest management. We incorporated two levels of beetle pressure: a background low level, and a higher level in which SPB had the potential to spread among pine stands. For each level of beetle pressure, we modeled two scenarios of forest management: one assuming forests would be managed continuously via thinning, and one with a reduction in thinning. For our study area in Georgia, Florida, and Alabama, we found that beetle pressure and forest management both influenced the landscape effects of SPB. Under increased SPB pressure, even with continuous management, the area of pine forests affected across the region was six times greater than under baseline SPB levels. However, under high SPB pressure, continuous management decreased the area affected by nearly half compared with reduced management. By incorporating a range of forest and SPB dynamics over long time scales, our results extend previous modeling studies, and inform forest managers and policy-makers about the potential future effects of SPB. Our model can also be used to investigate the effects of additional scenarios on SPB dynamics, such as alternative management or climate change.