The final installment of our series on new lab members! Sarah has a range of experiences in developing data-driven ecological models, including developing models to study White‐Nose Syndrome in bats, epidemiology and economic impact of Johne’s disease on commercial dairy farms, and within‐host developmental cycle of Chlamydia. Sarah will continue her interest in data-driven ecological modeling to estimate extinction risk of plant species under climate change.
What is your research focus?
Seed dispersal is an important mechanism plants use to respond to climate change. It allows populations to migrate to areas with cooler temperatures and also influences diversity. Factors such as human-induced habitat fragmentation, however, interfere with this process. My research aims to identify species that are most susceptible to extinction due to climate change. I will utilize data on plant dispersal, demography, and functional traits along with a variety of theoretical modeling approaches.
How did you get interested in this kind of research?
I started college as an athletic training major but moved to the math department after two weeks when I noticed how excited I was about going to my 8am, non-required Calculus II class. I found that I also greatly enjoyed my introductory biology laboratory. Everything seemed to click into place when I attended a guest lecture about mathematically modeling a cholera outbreak. It amazed me that one project could involve so many topics that interested me. I was hooked – I began looking for opportunities to try mathematical biology for myself. Since then I have explored a variety of corners of the math-bio world, but I keep feeling drawn back to ecology. I love the richness of being able to walk outside and think about the mechanisms underlying everything around me. Ecology also provides great opportunities to engage with projects involving multi-scale phenomena, stochasticity, and data-driven modeling approaches.
Can you describe some of your past research?
My research has allowed me to work with a several quantitative techniques in several different biological sub-fields. For my first undergraduate project, I created a spatial and temporal model for the spread of white-nose syndrome in North American bat populations. I also spent a summer developing an agent-based model for Johne’s disease in dairy cows. My late undergraduate and early graduate work involved genomics and a variety of projects at the cellular and molecular levels. Most recently, my work at Nationwide Children’s Hospital in Columbus focused on the study of the genetics of mental health through linkage analysis.
What made you choose Utah State University/the Beckman Research Group?
I knew that I wanted to join a research group that combined field scientists and computational scientists and had strong ties to both the mathematical and ecological communities on campus. I was also looking for a supportive work environment that encouraged professional development as well as research-based skill sets. I attended a Beckman group meeting during a visit to campus and knew it was what I was looking for. The mountain views didn’t scare me away, either!
What are your goals after you’re done here?
I would like a career that allows me utilize and expand my scientific knowledge while working closely with and serving people. I would love to teach at the undergraduate level, but I am also interested in career paths in science communication and science policy.
What do you like to do in your free time?
My favorite hobbies are improvisational comedy and live storytelling. I obsessively follow Olympic sports year-round – especially gymnastics, figure skating, and swimming. I am also an avid listener of Broadway soundtracks and a variety of podcasts.
Tell me your best field work/research-related story.
A few years ago I attended a systems biology “boot camp.” Most of the participants were math majors. We tried out several molecular biology and biochemistry techniques, watched tadpole embryos divide in real time, and spent several hours in the dark learning about advanced microscopy. We also realized just how much better suited we are to computational work than wet lab work. Tiny DNA pellets that we isolated from cell samples crumbled, electrophoresis gel wells overflowed and ran together, and test tubes broke in the centrifuge. At one point we managed to get a negative UV spectrophotometer reading, which has no actual physical meaning. While humbling at times, boot camp provided valuable insight into the experimental world that I’ve carried with me ever since.