Amanda Zellmer’s research focuses on the utility and development of computational methods for studying spatial ecological and evolutionary processes, particularly in the context of conservation biology.
Her research uses an integrative approach combining computational analyses with next-generation sequencing, field observations, and experimental data to address questions in spatial ecology, landscape genetics, and phylogeography. The main computational methods used in her research include Machine Learning techniques, including Species Distribution Modeling, Least-Cost Path and Resistance Modeling, and Multivariate Analyses and Model Selection. Her work is primarily focused on amphibians, although also includes many other types of organisms such as carnivorous pitcher plants, rocky reef fish and invertebrates, birds, and humans.