Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level

Lorenz Fahse and Marco Heurich

Ecological Modelling, 2011, vol. 222, issue 11, 1833-1846

Abstract: Outbreaks of bark beetles in forests can result in substantial economic losses. Understanding the factors that influence the development and spread of bark beetle outbreaks is crucial for forest management and for predicting outbreak risks, especially with the expected global warming. Although much research has been done on the ecology and phenology of bark beetles, the complex interplay between beetles, host trees, beetle antagonists and forest management makes predicting beetle population development especially difficult. Using the recent infestations of the European Spruce Bark Beetle (Ips typographus L. Col. Scol.) in the Bavarian Forest National Park (Germany) as a case study, we developed a spatially explicit agent-based simulation model (SAMBIA) that takes into account individual trees and beetles. This model primarily provides a tool for analysing and understanding the spatial and temporal aspects of bark beetles outbreaks at the stand scale. Furthermore, the model should allow an estimation of the effectiveness of concurrent impacts of both antagonists and management to confine outbreak dynamics in practice. We also used the model to predict outbreak probabilities in various settings. The simulation results indicated a distinct threshold behaviour of the system in response to pressure by antagonists or management of the bark beetle population. Despite the different scenarios considered, we were able to extract from the simulations a simple rule of thumb for the successful control of an outbreak: if roughly 80% of individual beetles are killed by antagonists or foresters, outbreaks will rarely take place. Our model allows the core dynamics of this complex system to be reduced to this inherent common denominator.

Keywords: Bark beetle; Ips typographus; Outbreaks; Management; Antagonists; Spatial simulation model; Threshold behaviour (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:222:y:2011:i:11:p:1833-1846

DOI: 10.1016/j.ecolmodel.2011.03.014

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