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

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  • Fahse, Lorenz
  • Heurich, Marco

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.

Suggested Citation

  • Fahse, Lorenz & Heurich, Marco, 2011. "Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level," Ecological Modelling, Elsevier, vol. 222(11), pages 1833-1846.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:11:p:1833-1846
    DOI: 10.1016/j.ecolmodel.2011.03.014
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    References listed on IDEAS

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    1. Seidl, Rupert & Baier, Peter & Rammer, Werner & Schopf, Axel & Lexer, Manfred J., 2007. "Modelling tree mortality by bark beetle infestation in Norway spruce forests," Ecological Modelling, Elsevier, vol. 206(3), pages 383-399.
    2. W. A. Kurz & C. C. Dymond & G. Stinson & G. J. Rampley & E. T. Neilson & A. L. Carroll & T. Ebata & L. Safranyik, 2008. "Mountain pine beetle and forest carbon feedback to climate change," Nature, Nature, vol. 452(7190), pages 987-990, April.
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    1. Honkaniemi, Juha & Ojansuu, Risto & Kasanen, Risto & Heliövaara, Kari, 2018. "Interaction of disturbance agents on Norway spruce: A mechanistic model of bark beetle dynamics integrated in simulation framework WINDROT," Ecological Modelling, Elsevier, vol. 388(C), pages 45-60.
    2. Kautz, Markus & Schopf, Reinhard & Imron, Muhammad Ali, 2014. "Individual traits as drivers of spatial dispersal and infestation patterns in a host–bark beetle system," Ecological Modelling, Elsevier, vol. 273(C), pages 264-276.
    3. Strohm, S. & Reid, M.L. & Tyson, R.C., 2016. "Impacts of management on Mountain Pine Beetle spread and damage: A process-rich model," Ecological Modelling, Elsevier, vol. 337(C), pages 241-252.
    4. Ogris, Nikica & Ferlan, Mitja & Hauptman, Tine & Pavlin, Roman & Kavčič, Andreja & Jurc, Maja & de Groot, Maarten, 2020. "Sensitivity analysis, calibration and validation of a phenology model for Pityogenes chalcographus (CHAPY)," Ecological Modelling, Elsevier, vol. 430(C).
    5. Wildemeersch, Matthias & Franklin, Oskar & Seidl, Rupert & Rogelj, Joeri & Moorthy, Inian & Thurner, Stefan, 2019. "Modelling the multi-scaled nature of pest outbreaks," Ecological Modelling, Elsevier, vol. 409(C), pages 1-1.
    6. Uchmański, Janusz, 2019. "Cyclic outbreaks of forest insects: A two-dimensional individual-based model," Theoretical Population Biology, Elsevier, vol. 128(C), pages 1-18.
    7. Perez, Liliana & Dragicevic, Suzana, 2012. "Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model," Ecological Modelling, Elsevier, vol. 231(C), pages 53-64.

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