Erich Seamon, Ph.D

Education

• Ph.D., University of Idaho
• M.S., Bowling Green State University

Bio

Erich Seamon is a quantitative climatologist and spatiotemporal modeler, who has an appointment as an Assistant Professor at Baylor University’s Department of Environmental Science. Dr. Seamon has a M.S. in Geosciences from Bowling Green State University and a Ph.D. in Natural Resources from the University of Idaho, with research focusing on statistical modeling techniques to explore natural system spatiotemporal relationships that intersect with topical areas such as: agricultural insurance and associations with climate, social determinants of health and COVID-19, and machine learning applications related to human development and environmental factors. He publishes in a number of journals, including PloS One, Environmental Science, and BMC Public Health. He additionally integrates his research with differing spatiotemporal visualization methods, including mixed and augmented reality.

An additional aspect of Dr. Seamon’s research focuses on scientific reproducibility and its’ applications to data intensive, collaborative team environments. In that context, he has worked on several multi-year research team collaborations, including: the University of Idaho’s USDA-funded Regional Approaches to Climate Change for Pacific Northwest Agriculture (REACCHPNA – http://www.reacchpna.org), as well as Oregon State University’s Climate Impacts Research Consortium (http://pnwcirc.org), a NOAA-funded Pacific Northwest Regional Integrated Science Assessment (RISA) team, led by scientists from Oregon State, University of Idaho, and the University of Washington. He is currently a co-PI on a 5-year 6M NSF funded climate and underserved populations project (https://wherewelive.org), as well as senior personnel on a 5-year, 20M NSF multi-institutional project which focuses on climate associations to water and energy systems (https://idahocrews.org).

Lab

Baylor Health, Agriculture and Climate Laboratory (HACLab)

Publications

• Seamon, E., Miller, C.R., Johnson-Leung, J., Ridenhour, B.J. (2025) “Spatial Modeling of Sociodemographic Risk for COVID-19 Mortality” BMC Public Health.  Under review. https://doi.org/10.1101/2023.07.21.23292785   

• Williams, P. Jones-Crank, J.L., Daher, B., Thomas, A., Cortus, E. Seamon, E., Kliskey, A. “Meta-Synthesis and R Analysis of Stakeholder Engagement in Food, Energy and Water Literature” (2025). Nature Sustainability. Under Review

• Seamon E., Mattera, J., Keim, S.A., Leerkes, E.M., Rennels, J.L., Kayl, A.J., Kulhanek, K.M., Narvaez, D., Sanborn, S.M., Grandits J.B., Schetter, C.D., Coussons-Read, M., Tarullo, A.R., Schoppe-Sullivan, S.J., Thomason, M.E., Braungart-Rieker, J.M., Lumeng, J.C., Lenze, S.N., Christian, L.M., Saxbe, D.E., Stroud, L.R., Rodriguez, C.M., Anzman-Frasca, S., Gartstein. (2024). Leveraging Machine Learning to Study How Temperament Scores Predict Pre-Term Birth Status. Global Pediatrics. Volume 9, 2024, 100220, ISSN 2667-0097, https://doi.org/10.1016/j.gpeds.2024.100220

• Moxley TA, Johnson-Leung J, Seamon E., Williams C, Ridenhour BJ (2024) Application of elastic net regression for modeling COVID-19 sociodemographic risk factors. PLoS ONE 19(1): e0297065. https://doi.org/10.1371/journal.pone.0297065

• Seamon E., Gessler PE, Abatzoglou JT, Mote PW, Lee SS. Climatic Damage Cause Variations of Agricultural Insurance Loss for the Pacific Northwest Region of the United States. Agriculture. (2023). 13(12):2214. https://doi.org/10.3390/agriculture13122214

• Seamon, E., Megheib, M., Williams, C. J., Murphy, C. F., & Brown, H. F. (2023). Estimating county level health indicators using spatial microsimulation. Population, Space and Place, e2647.
  https://doi.org/10.1002/psp.2647

• Adhikari, S., Seamon, E., Wu, Y., Sadeghi, S.E., Eigenbrode, S.D. (2022). “Do Invasive and Naturalized Aphid Pest Populations Respond Differently to Climatic and Landscape Factors?” Journal of Economic Entomology. https://doi.org/10.1093/jee/toac044

• Seamon, E., Gessler, P., Abatzoglou, J., Mote, P., & Lee, S. (2022). A climatic random forest model of agricultural insurance loss for the Northwest United States. Environmental Data Science, 1, E29. https://doi.org/10.1017/eds.2022.27

• Gartstein, M.A., Seamon, E., Mattera, J., Bosquet-Enlow, M., Rosalind J. Wright, Perez-Edgar, K., Buss, K.,  LoBue, V., Bell, M.A., Calkins, S.D., Goodman S.H., Spieker, S., Bridgett, D.J.,  Salisbury A.L.,  Mliner S.B., Gunnar, M.R., Muzik, M., Stifter, C.A., Planalp, E.M., Mehr, S.A., Spelke, E.S., Lukowski, A.F., Groh, A.M., Lickenbrock, D.M., Santelli, R., Du Rocher Schudlich, T., Anzman-Frasca S., Thrasher, C., Diaz, A., Dayton C., Moding, K.J., Jordan, E.M. (2022). “Using Machine Learning to Understand Age and Gender Differences in Infant Temperament”.  PLOS One https://doi.org/10.1371/journal.pone.0266026

• Ridenhour, B., Sarathchandra, D., Seamon, E., Brown, H., Leung, F.Y., Johnson-Leon, M., Megheib, M., Miller, C., Johnson-Leung, J. (2022). “Effects of trust, risk perception, and health behavior on COVID-19 disease burden: Evidence from a multi-state US survey” PLoS One. https://doi.org/10.1371/journal.pone.0268302