In an effort to showcase and amplify the voices of early career researchers in ecology, evolution, and behavior, we are sharing their stories, in their own words.
Dr. Bob Week
Post-doctoral Researcher, Michigan State University
Can you give us the rundown on your ECR journey thus far, from what type of undergraduate institution you went to, to your current position?
My journey into science began at Clark Community College in Vancouver, Washington. I had developed an anxious curiosity for mathematics and electronics, but was undecided about my career path. So I focused on my passions, taking coursework in mathematics, physics and electrical engineering. I enjoyed the smaller class sizes at the community college and the relationships I developed with the faculty. Towards the end of my time at Clark I decided to pursue a bachelors in electrical engineering at the University of Idaho. I chose Idaho for its smaller size (hoping to retain a similar experience to the community college) and because its electrical engineering program was (and I am sure still is) well respected. However, I was caught off-guard by my interests in mathematics and a growing interest in how mathematics can be applied to understand biological pattern formation. At the time the University of Idaho had a program for Undergraduate research in Biology and Mathematics (UBM). I inquired about an open position and the organizer introduced me to Professor Scott Nuismer, a mathematical evolutionary ecologist studying coevolutionary theory. Scott and I really enjoyed working together and I became fascinated by the world of mathematical evolutionary ecology.
The experience I gained from working with Professor Nuismer inspired me to switch from electrical engineering to traditional mathematics during my final year. My only regret is not taking any biology during my undergraduate education. In the last steps towards gaining my bachelors, Scott asked if I would be interested in pursuing a PhD with him in the Bioinformatics and Computational Biology (BCB) program at the University of Idaho. I was honored to be given such an opportunity and my family was awestruck (I am the first to pursue graduate school in my family). The five years that followed were as challenging as they were rewarding. I enjoyed the breadth of coursework required (including courses from biology, computer science and statistics), but also the flexibility for crafting a unique education. In particular, I was able to get credit for taking several graduate-level mathematics courses, which continue to serve as the foundation for my research. The BCB program is also unique in that it requires a lab-rotation. For my lab rotation I spent three weeks gaining experience working with pollination ecologists at the Rocky Mountain Biological Laboratory (RMBL), hosted by Professor Paul CaraDonna.
Aside from learning how to set up a transect, take field observations of pollinators and estimate percent cover, I also had the opportunity to engage with a wonderful community of ecologists and explore the incredible landscape of the Elk Mountains. Returning to Idaho, my attention switched back to math. One of the projects I hoped to include as a dissertation chapter involved relating the processes of random genetic drift and demographic stochasticity in the context of quantitative traits. The approach I settled on naturally lead to stochastic partial differential equations, an unfortunately technical topic. However, Professor Steve Krone, a mathematical geneticist at the University of Idaho, happened to have expertise in this area. I am indebted to Steve for the countless hours spent discussing this material, ultimately empowering me to investigate evolutionary ecology from a perspective I deeply enjoy.
After successfully defending my dissertation in June 2020, I applied for a postdoctoral research position with Professor Gideon Bradburd at Michigan State University, which I saw advertised on the Twitter. Gideon hired me and I started work remotely in October 2020. Unfortunately, the COVID-19 pandemic and associated complications have waylaid my move to Michigan. In spite of this, I have thoroughly enjoyed my time as a ‘ghostdoc’ in the Department of Integrative Biology at MSU and I am excited to be there in person soon.
Can you tell us a bit about your research?
My research involves developing mathematical and computational models of evolutionary and ecological processes. In particular, I focus on coevolution between pairs of interacting species and coevolution among sets of species in an ecological community. I develop these models for two different purposes (statistical inference and exploration) and the nature of the model (complexity, analytical tractability, etc) is tailored to its purpose. My ultimate goal is to develop models that form the back-bone of statistical methods capable of utilizing phenotypic or genotypic data to measure coevolution in the wild. In particular, my undergraduate work with Scott Nuismer lead to a paper in Ecology Letters introducing a maximum likelihood approach to infer parameters of a coevolutionary model from spatially structured trait data. However, I have also used models to explore new phenomena and processes that may not be tractable to study using experiments conducted in a laboratory or measurements taken in the field. For example, in a recent contribution to The American Naturalist, I developed a model that predicts the outcome of coevolutionary arms races between a pair of mutualists, discovering that mutualism can be maintained depending on the phenotypic interface mediating the interaction. Currently, my work with Professor Gideon Bradburd at Michigan State University focuses on understanding patterns of genetic diversity resulting from coevolution between a pair of interacting species distributed continuously in space. Our goal is to identify the spatial signature of coevolution on genomic data in order to inform the development of future coevolutionary methods.
What sparked your interest in your field of study?
My initial interests in biological pattern formation were sparked by video feedback loops. By pointing a camera at a monitor and running the output of the camera to the monitor, one can achieve some curiously organic forms. This inspired me to think about developmental biology, but once I realized evolutionary ecology is biological pattern formation on a larger scale all the enthusiasm transferred. During my time at Clark Community College, Professor John Mitchell would give me mini-lectures on differential geometry which I found incredibly inspiring for pursuing higher math. However, it was my PhD adviser Scott Nuismer who taught me how to think like a biologist and inspired me to pursue a career in mathematical evolutionary ecology.
Outside of research, do you have other scientific interests you are pursuing, like teaching, policy work, or outreach? How do you find opportunities to develop those skills and interests?
Outside of research, I enjoy outreach and teaching. For outreach I have used my skills in generative art to create interactive projections that simulate ecological and evolutionary processes. Typically, I set up the projections at community art events with a controller so that attendees can change model parameters (such as effective population size and strength of selection) in real time. Engaging with local communities in this fashion is very rewarding. These sorts of opportunities can often be found by chatting with local artists at events or with curators of local galleries. For teaching I enjoyed tutoring mathematics at Clark Community College. I found the job by asking the faculty I had taken courses from if there were any openings. The mathematics tutoring center was a big room with whiteboards on each wall and a set of desks for students. Whenever a student raised their hand we tutors would do our best to help regardless of the topic. The most rewarding aspect of the job was not teaching math per se, but giving students the tools and space they needed to experience the discovery of mathematical results and succeed in their coursework. Helping students overcome their fear of math and pursue higher education was a very moving experience.
What is one piece of advice would you give to a starting graduate student?
It is never too early to develop work-life balance. Finding balance is a skill and I wish had started developing that skill when I started graduate school.
What hobbies or activities do you enjoy outside of science?
Outside of science I enjoy spending time with my little corgi (Lola), hiking (especially near Mt. St. Helens), making techno on synthesizers, riding bikes (I used to race in a velodrome), drinking a good pilsner and being around people.
ASN Graduate Council 