Development of a fuzzy-constrained GIS-based cellular automata model of dynamic complex systems: A case study of forest insect infestations

Cellular automata (CA) are suitable for modelling complex geographic and ecological processes such as forest insect infestations; however, problems exist with understanding the complexity of insect-host interactions through geospatial data. The objective of this research was to develop a fuzzy-constrained approach for a GIs-based CA model of forest insect infestations. The methodology was tested with a case study of the mountain pine beetle, Dendroctonus ponderosae Hopkins, in the central interior of British Columbia, Canada. Fuzzy sets were used for obtaining information on the susceptibility of trees to attack, while CA was employed for modelling MPB-induced patterns of tree mortality. This research contributes in the advancement of CA models by using fuzzy sets and GIs for addressing uncertainty of dynamic spatial phenomena, and provides a novel approach for modelling MPB outbreaks that is useful to forest management.