Date: May 13, 2019

Time: 9:00am

Location: 3105, Lambton Tower

 

We took a computational modelling and simulation approach to studying biological invasions, characterized by the movement of organisms to novel locations where they cause impact. First, we explored the impact of genetic diversity of introduced populations on their establishment success using EcoSim. Our results demonstrated that an environment with low and heterogeneous resources mediated a relationship between genetic diversity and establishment success. Our results also corroborated the evolutionary imbalance hypothesis and a mechanical explanation for it, and Allee effects were observed in our digital organisms. Secondly, genetic metabarcoding is becoming increasingly popular to study species richness and detect invasive species, but it requires some amount of computational genetic sequence processing. Optimal processing parameters, and the consequences of poor parameterization, are poorly understood. We determined the optimal parameterization of a common sequence processing pipeline for both early detection of aquatic invasive species and conducting species richness assessments. We simulated inoculation of sequences into community samples to assess performance of optimized pipelines. We found that early detection requires relatively lenient processing parameters and that optimality depended on the research goal. Further, we established effects of parameterization on detectability and sensitivity of the pipeline.

 

Thesis Committee: