Rate My Professor Erin Landguth

Erin Landguth is a Professor in the School of Public and Community Health Sciences at the University of Montana, where she also serves as an affiliate of the Center for Population Health Research. She earned a Bachelor’s degree in Mathematics and a Master’s degree in Atmospheric Sciences from the South Dakota School of Mines and Technology, followed by a PhD in Mathematical and Computational Ecology from the University of Montana in 2010. Her doctoral work centered on mathematical and computational applications in disease and landscape ecology. Landguth is Co-Director of the Computational Ecology Lab and Co-Director of the Data and Modeling Core at the Center for Population Health Research. She teaches courses including PUBH 591: Communicable Disease Epidemiology and Control, PUBH 613: Spatial Epidemiology Applications in GIS, and BIOB 595: Distributed Graduate Seminar in Landscape Genetics.

Landguth's research focuses on computational landscape ecology, where she develops, optimizes, and applies simulation programs such as CDPOP, UNICOR, and CDMetaPOP to explore relationships between biological processes and population patterns across landscapes. She also advances air pollution exposure models and examines factors influencing respiratory health, particularly for rural populations in Montana. Her highly cited publications include "Quantifying the lag time to detect barriers in landscape genetics" (Molecular Ecology, 2010; 616 citations), "Spurious correlations and inference in landscape genetics" (Molecular Ecology, 2010; 335 citations), "Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes" (Molecular Ecology, 2016; 316 citations), "Why replication is important in landscape genetics: American black bear in the Rocky Mountains" (Molecular Ecology, 2011; 253 citations), and "cdpop: A spatially explicit cost distance population genetics program" (Molecular Ecology Resources, 2010; 247 citations). Additional contributions cover the delayed effects of wildfire particulate matter on influenza-like illness (2020), genetic connectivity in wildlife, and climate adaptation. These works have significantly influenced landscape genetics methodologies and public health responses to environmental factors.