Addressing the risks of invasive plants through spatial predictive modelling
Lindgren, Cory John
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The objective of this dissertation is to extend the use of spatial predictive modelling for use by biosecurity agencies to help prevent the introductions of new and emerging invasive plants (i.e., pests). A critical review of international and national policy instruments found that they did not effectively articulate how spatial predictive modelling could be incorporated into the biosecurity toolbox. To determine how spatial predictive modelling could be extended I modelled the potential distribution of Tamarix and Lythrum salicaria in Prairie Canada using a genetic algorithm. New seasonal growth data was used to interpolate a growing degree-day’s risk surface for L. salicaria. Models were developed using suites of predictive variables as well as different data partitioning methods and evaluated using different performance measures. Expert evaluation was found to important in final model selection. The results indicated that both invasive plants have yet to reach their potential distribution in Prairie Canada. The spatial models can be used to direct risk-based surveillance efforts and to support biosecurity policy decisions. The results of this dissertation conclude that spatial predictive modelling is an informative tool that needs to be incorporated into the biosecurity toolbox. A phytosanitary standard is proposed to guide toolbox development.