Midwest Mathematical Biology Conference


Two weekends ago, I was lucky enough to attend the Midwest Mathematical Biology Conference.

This meeting was hosted by the University of Wisconsin-La Crosse and was the first time for the event. Overall, the meeting was great. I enjoyed the great keynote speakers. Meetings like this help inspire me because I enjoy seeing how other people solve problems. I also enjoy the networking and collaborations formed between researchers.

The keynote address that stood out most to me as the one by Carlos Castillo-Chavez. Carlos provided a great overview on epidemiology modeling and to use multiple scales of modeling together. He summarized a project that used an Individual-based Model to examine how disease spread at the city-level and then scaled up the results to a national level. These results were also compared traditional SIR models. The research does a great job illuminating where people catch infection disease during outbreaks. Surprisingly, most people get sick at home. This happens because people have the most contact with others when they are at home. However, when school is not in session, outbreaks are less likely to occur.

Besides the other great talks, my postdoc mentor had a great observation. He realized the USGS has very few mathematicians and all of them are doing geology (or at least non-biology) research. We wished we had more mathematical support. Furthermore, the Midwest Mathematical Biology Meeting expanded his view of biomath. Even if I gained nothing else from the meeting, having my postdoc mentor appreciate math more made it all worth while! However, I did gain more. So, the meeting was great opportunity!

Meet a Quantitative Ecologist


“So, what does a quantitative ecologist do?”

This is the first question most people ask me when I rattle off my job title. Basically, I use math to study and solve ecological problems. I am living a giant math story problem and enjoying it! I use ecological model, computational mathematics, and advanced statistics to not only solve problems, but also define them. For those of you familiar with the term, I consider myself a quant. Unlike most quants, I primarily study the environment. On any given day, I might be modeling where a species occurs or studying how a chemicals affect wildlife. In addition to the environment, I also dabble in medical biostatistics and quantifying risk for business. Statistics and mathematics allow me to “play” in many different field’s backyards.

How might one become a Quantitative Ecologist do you ask?

Growing up, I always enjoyed the outdoors. As a family, my parents, brother and I would go on hikes and bike rides often. Through scouting, I went on many a camping trip ranging from backyards and pastures to wilderness areas. This led me to restore a prairie for my Eagle Scout project with a wildlife biologist. My project motivated me to study wildlife ecology  for my undergraduate major. However, the wildlife job market is very tough! So, I chose to go to grad school for environmental toxicology.

Okay, so I see you’re why you’re an ecologist, but where does the “quantitative” part fit in?

Growing up, I always liked to play computer games and enjoyed math until it became hard in high school (I still hate calculus to this day!). I did not link the two interests formally until grad school. I developed a mosquito/dengue model for my MS research. One of my MS committee members, and future PhD co-adviser, told me that I needed to learn mathematics if I wanted to model. Begrudging and almost whimsically, I followed this advice and eventually even took it to heart. Two years of coursework later, I completed a doctoral minor in mathematics. This coursework helped me to completed my doctoral research where I studied the effects of pesticides on Daphnia.

I saw a posting on the TWS Biometrics Working Group email list adverting a postdoctoral position to study the effects of wind energy on cave bats. I applied for the position, and am now a “Quantitative Ecologist”.



“Nothing in the world of living things is permanently fixed.”
Hans Zinnser — Rats, Lice and History, 1935

Our world is ever-changing. Stock prices go up and down. Seas and temperatures are rising. New chemicals emerge from the lab that may either be a deadly poison or a modern miracle or possibly both. Search engines must scan a constantly changing web. Even the American pass time of baseball uses sabermetrics to choose and evaluate players.

These situations are all dynamic. “Dynamic” simply means things are changing rather than staying constant or “static.” Understanding these situations requires the use of models. More specifically, quantitative models. Hence the title of this blog: “Quantitative Dynamics”.

This blog is about quantitative dynamics. We’re going to cover topics ranging from cave bats to health care. I’ll also talk about other things that strike my fancy. Mainly these topics will be about environmental science and ecology, but I have a broad interest in how models may be applied across our lives (e.g,. FiveThirtyEight.com). I am writing this blog for several reasons: to share my research with non-scientists, to write down ideas/techniques so that I do not forget them, and to learn about blogging. Last, I enjoy teaching and will use this blog to share what I am learning both on and off the job.