PerezDragicevic2012

Référence

Perez, L., Dragicevic, S. (2012) Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model. Ecological Modelling, 231:53-64. (Scopus )

Résumé

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. © 2012 Elsevier B.V.

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@ARTICLE { PerezDragicevic2012,
    AUTHOR = { Perez, L. and Dragicevic, S. },
    TITLE = { Landscape-level simulation of forest insect disturbance: Coupling swarm intelligent agents with GIS-based cellular automata model },
    JOURNAL = { Ecological Modelling },
    YEAR = { 2012 },
    VOLUME = { 231 },
    PAGES = { 53-64 },
    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. © 2012 Elsevier B.V. },
    ADDRESS = { Spatial Analysis and Modeling Laboratory, Department of Geography, Simon Fraser University, 8888 University Drive, Burnaby, BC, V5A 1S6, Canada },
    COMMENT = { Cited By (since 1996):1 Export Date: 18 February 2014 Source: Scopus },
    KEYWORDS = { Agent-based model, Cellular automata, Forest disturbances, Mountain pine beetle (MPB), Spatiotemporal modeling, Swarm intelligence },
    OWNER = { Luc },
    TIMESTAMP = { 2014.02.18 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-84857403503&partnerID=40&md5=6bc35fdfa92894ebafee84edf3913a3c },
}

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