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Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model

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  • Perez, Liliana
  • Dragicevic, Suzana

Abstract

Forest insect disturbances have an ecological impact and are the cause of partial or complete stands mortality; hence they influence the forest cover change. The modeling of ecological processes such as insect disturbance is challenging due to the complexity of insect outbreaks in forest ecological systems, thus diverse spatial scales need to be considered in order to effectively represent these dynamic spatial phenomena. The objective of the study is to develop a hybrid model that combines swarm intelligence (SI), agent-based modeling (ABM) and cellular automata (CA) with geographic information systems (GIS) for simulating tree mortality patterns introduced by insect infestations at a landscape spatial scale. The focus is on lodgepole pine, Pinus contorta, tree mortality patterns caused by infestations of mountain pine beetle (MPB), Dendroctonus ponderosae Hopkins. The complexity of the insects’ behavior during forest disturbances can be captured and simulated by an intelligent ABM. Agents represent insects that have the ability to behave and adapt according to their interactions within the forest environment at a very fine spatial scale at tree-level, and with the use of swarming intelligence approach. However, due to computational complexity such model is not operational at landscape and regional spatial scales where the consequences of infestation phenomenon are most obvious. Therefore, the integration of the ABM with CA approach is proposed to handle modeling at both fine and large spatial scales. The discrete nature of CA enables integration with raster-based geospatial datasets in GIS, and can also be beneficial when modeling complex ecological processes that evolve over time. The developed model includes factors such as wind directions and elevation to demonstrate their influence in the spread patterns of the outbreaks at a landscape spatial scale. The model outcomes provide “what if” scenarios that can assist studying and controlling MPB forest disturbance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:ecomod:v:231:y:2012:i:c:p:53-64
    DOI: 10.1016/j.ecolmodel.2012.01.020
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    References listed on IDEAS

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    1. Ernst Gebetsroither & Alexander Kaufmann & Ute Gigler & Andreas Resetarits, 2006. "Agent-Based Modelling of Self-Organisation Processes to Support Adaptive Forest Management," Contributions to Economics, in: Francesco C. Billari & Thomas Fent & Alexia Prskawetz & Jürgen Scheffran (ed.), Agent-Based Computational Modelling, pages 153-172, Springer.
    2. 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.
    3. Trucano, T.G. & Swiler, L.P. & Igusa, T. & Oberkampf, W.L. & Pilch, M., 2006. "Calibration, validation, and sensitivity analysis: What's what," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1331-1357.
    4. Mathey, Anne-Hélène & Krcmar, Emina & Dragicevic, Suzana & Vertinsky, Ilan, 2008. "An object-oriented cellular automata model for forest planning problems," Ecological Modelling, Elsevier, vol. 212(3), pages 359-371.
    5. Yassemi, S. & Dragićević, S. & Schmidt, M., 2008. "Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour," Ecological Modelling, Elsevier, vol. 210(1), pages 71-84.
    6. McDonald, A.D. & Little, L.R. & Gray, R. & Fulton, E. & Sainsbury, K.J. & Lyne, V.D., 2008. "An agent-based modelling approach to evaluation of multiple-use management strategies for coastal marine ecosystems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 401-411.
    7. Bonnell, Tyler R. & Sengupta, Raja R. & Chapman, Colin A. & Goldberg, Tony L., 2010. "An agent-based model of red colobus resources and disease dynamics implicates key resource sites as hot spots of disease transmission," Ecological Modelling, Elsevier, vol. 221(20), pages 2491-2500.
    8. Chion, Clément & Lamontagne, P. & Turgeon, S. & Parrott, L. & Landry, J.-A. & Marceau, D.J. & Martins, C.C.A. & Michaud, R. & Ménard, N. & Cantin, G. & Dionne, S., 2011. "Eliciting cognitive processes underlying patterns of human–wildlife interactions for agent-based modelling," Ecological Modelling, Elsevier, vol. 222(14), pages 2213-2226.
    9. Daniel G. Brown & Rick Riolo & Derek T. Robinson & Michael North & William Rand, 2005. "Spatial process and data models: Toward integration of agent-based models and GIS," Journal of Geographical Systems, Springer, vol. 7(1), pages 25-47, October.
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