Date of Award
Master of Science (MS)
Mathematics and Statistics
Understanding the spatial and temporal dynamics of plant populations has important implications for the fields of ecology and conservation. A rich body of mathematical modeling approaches, including reaction-diffusion equations and integrodifference equations, have been developed to mechanistically model population spread based on species demography and seed dispersal characteristics. However, with over 390,000 plant species on Earth, it is not feasible to collect complete information on all species for the purpose of drawing generalized conclusions. One means of overcoming such a problem is through trait-based modeling, which seeks to represent realistic combinations of organismal traits rather than focusing on individual species. In this report, I present a multivariate Bayesian model for plant trait space fit using sparse trait data synthesized from diverse sources. This model will be used as the backbone of a broader virtual-species-based simulation study to investigate global distributions of plant population spread rates and risk of movement-related extinction risk under global change.
Bogen, Sarah, "A Bayesian Hierarchical Approach for Modeling Virtual Species with Realistic Functional Trait Relationships" (2022). All Graduate Plan B and other Reports. 1670.
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