Ecological phenomena like insect infestation behave as complex systems, where spatial patterns at larger scales emerge from interactions among individuals at the local level. The complexity is difficult to capture using conventional top-down approaches such as statistical or equation-based models which can be limiting in representing individual interactions, non-linearity, local dynamics, spatial heterogeneity and variation. The main objective of this study is to develop a suite of geographic automata approaches including cellular automata (CA) and agent-based modeling (ABM) to model insect infestation outbreaks over space and time. The proposed approaches were developed using emerald ash borer (EAB) infestation in Ontario as a case study. Obtained results indicate that the developed approaches capture local complex spatio-temporal EAB behavior and reproduce larger scale spatial patterns of infestation. This research advances insect infestation modeling and provides a tool to aid in the surveillance, eradication, and biosecurity to EAB infestation.
Copyright is held by the author.
The author granted permission for the file to be printed and for the text to be copied and pasted.
Supervisor or Senior Supervisor
Thesis advisor: Dragicevic, Suzana
Member of collection